case study on higher education institutions

How to transform higher-education institutions for the long term

Higher-education institutions in the United States are facing unprecedented challenges. Even before the COVID-19 pandemic, higher-education operating models were under tremendous pressure. Many institutions, experiencing declining enrollment, watched expenses outpace revenues and tapped into their endowments to cover shortfalls.

The COVID-19 pandemic has exacerbated the pressures that higher-education institutions face . Even some of the most notable and stable institutions are experiencing significant declines in tuition and auxiliary revenues as well as increasing budget shortfalls. Our analysis suggests  that, before any government or philanthropic intervention, up to 57 percent of public four-year institutions and up to 77 percent of private not-for-profit four-year institutions could suffer budgetary shortfalls of more than 5 percent. The more than $35 billion provided by the federal government to higher education in relief acts to date has helped institutions and students address some of the near-term challenges, but the enrollment headwinds will likely affect university budgets for years to come. 1 Relief included about $14 billion in the March CARES Act and about $23 billion in the December Coronavirus Response and Relief Supplemental Appropriations Act of 2021. Indeed, according to the National Student Clearinghouse data, declines in first-time college enrollment in fall 2020 were stark, 2 For more on the fall 2020 admissions cycle, see Hamilton Boggs, Charag Krishnan, Samvitha Ram, and Jimmy Sarakatsannis, “ Best practices for an unusual US admissions cycle amid coronavirus ,” April 30, 2020. with greater than 10 percent declines in public four-year institutions and 8 percent declines in private not-for-profit four-year institutions, 3 “National Student Clearinghouse Research Center’s monthly update on higher education enrollment,” National Student Clearinghouse Research Center, November 12, 2020, nscresearchcenter.org. significantly affecting most universities’ top revenue source. While fundraising remained flat in academic year 2020, 4 “Charitable giving to US colleges and universities reached $49.50 billion, virtually unchanged from last fiscal year,” Council for Advancement and Support of Education, February 9, 2021, case.org. institutions are projecting steep fundraising declines in 2021, 5 “EAB survey points to dramatic decline in university fundraising,” GlobeNewswire, June 8, 2020, globenewswire.com. meaning fiscal challenges won’t be easing anytime soon.

A transformation approach that enables institutions to operate more flexibly and resiliently in the long term can help institutions emerge on a stronger footing from today’s challenges and brace for those of the future. A true transformation often improves operating surplus by 20 percent or more—money that can then be reinvested into an institution’s mission. But such a transformation requires an intense, operations-wide program focused on improving student outcomes and boosting organizational health and performance. In our experience, there are five common features of the most successful transformation efforts. While many leaders are aware of such efforts, implementation success has varied. We provide five inspiring case examples that prove a transformation approach is not only possible but also essential for the long-term success of institutions.

A transformation approach that enables institutions to operate more flexibly and resiliently in the long term can help institutions emerge on a stronger footing from today’s challenges.

Educational institution transformation best practices and case examples

While a reasonable degree of cost management is necessary to address fiscal challenges and make change, it’s perhaps more important for institutions to focus on improving student outcomes and identifying new ways to diversify and grow revenues. As core decision makers—including presidents, chancellors, provosts, and CFOs or COOs—embark on a transformation, they can reflect on their alignment with five factors to measure how prepared they are and determine where they need to focus their efforts.

Ensure leadership is engaged and empowered to support the organization to reach its full potential

The best predictor of the success of a transformation is leadership that is willing to embrace new and innovative approaches, recognizes the importance of institutional performance and health, and is prepared to take a self-confident leap instead of incremental steps. A few actions can help core decision makers ensure leadership is on board.

• Develop an aspirational, shared vision. Establish a vision for the future of the organization and frame all conversations with the leadership team around it.
• Establish a data-driven organizational baseline. Assess operational and cultural performance to discover opportunities to expand mission impact and set targets.
• Create a sense of urgency for bold action. Share stories about how other institutions are responding to the moment to inspire action.
• Get everyone involved. Activate all levels of the organization to brainstorm innovative changes and help achieve the vision by following a proven approach that gathers broad stakeholder inputs and enables ownership and accountability for improvement ideas.

The leadership team of a large network of higher-education institutions wanted to identify the full potential of the organization and build a shared vision for change. As they began their transformation journey in 2018, the system leadership met with each institution’s leadership team to form a shared vision of the future of their network. These conversations helped the leaders recognize when they weren’t performing at their best and, most importantly, the detrimental impact that had on students. Consequently, the collective leadership set an ambitious goal to improve organizational health, 6 Organizational health refers to an organization’s ability to align around and achieve its strategic goals. To learn more about measuring and improving organizational health, see McKinsey’s Organizational Health Index . increase student enrollment and retention, and reduce costs in the interest of better serving students. The system leadership then structured the transformation efforts to empower institution leaders to own and drive the transformation at their institutions. While the approach and leaders involved throughout the effort varied, each leader was committed to pursuing the shared aspiration of improved student experience and outcomes.

The transformation increased enrollment in both new and existing programs by about 5 percent over approximately 16 months since the start of the effort—through a combination of increased new enrollments and improved persistence of existing students. Further, the cost-improvement efforts have helped these institutions limit tuition increases and offer additional financing options so students can complete their education even in times of uncertainty, such as those brought on by the COVID-19 crisis.

Ensure the board prioritizes the transformation

Board support and commitment is integral to the success of a transformation. The COVID-19 pandemic and associated financial and societal pressures have created an even greater imperative for boards to actively define the strategic direction of their higher-education institutions and to push leaders to make substantive and sustainable operational changes to achieve financial stability and resilience. As such, core decision makers should consider involving the board in three ways.

• Leverage the board’s advisory role and fiduciary duties. Harness the board’s unique position to push university leadership for actionable plans to adjust the status quo.
• Build in accountability. Task a board subcommittee with supporting management with problem solving and track the change through regular progress updates that focus on measurable outcomes.
• Ensure the board is grounded in current higher-education trends. Most boards, rightfully, comprise members from a diverse set of business and philanthropic backgrounds. Many trustees won’t be as familiar with the pressures facing higher education. Educating the board on the trends in higher education by sharing literature improves transparency on the institution’s challenges and finances.

A midsize liberal arts university was facing a crisis of declining enrollments and net tuition, and its operating deficits forced the university to double what it typically drew from endowments for four subsequent years. Due to these financial concerns, the university’s accreditation organization alerted it of the need for immediate action to avoid the risk of probation and possible loss of accreditation. The university needed a strategy that would enable it to make rapid and significant changes without sacrificing the quality of the education.

The board took responsibility for shaping the transformation goals, unifying key stakeholders, and building momentum throughout the university. The board oversaw a short review of the school’s key metrics and plotted a course that placed as much emphasis on student success and enrollment-driven revenue growth as cost management. Next, it supported the university leadership to encourage faculty, staff, and students to play active roles in this transformation by creating a compelling change story and providing transparency that inspired people to think and behave differently. The board and leadership relayed this change story through carefully planned internal and external communications. To continually reinforce its crucial role in this process, a subcommittee of the board committed to meet biweekly to monitor progress over the entire transformation period.

The university’s first-year class increased by 30 percent the first year of the transformation, and it saw similar increases the following two years. In addition, retention from the first to second year of school improved from 77 to 85 percent, the university’s financial health significantly improved, and for the first time in nearly a decade, it had a balanced budget in 2019. Moreover, the new processes renewed a culture of continuous improvement and put the institution in a much better position to weather the COVID-19 crisis.

Translate financial outcomes to the institution’s mission when setting transformation targets

To maximize outcomes for students, faculty, staff, and the broader community, higher-education institutions need to be financially sustainable and efficient. Drawing the link between financial goals and an institution’s mission serves as a powerful rallying cry in support of transformative change. Two related actions can help.

• Emphasize mission impact over financial impact in messaging to the campus. Share impact and successes—for example, when additional financial aid has been allocated to Pell-eligible students to support their success, focus on the impact of improved persistence rates rather than the increased revenues from student retention.
• Communicate small but impactful vignettes. For instance, spotlight additional research funding secured due to strategic investment in grant writers. Such stories personalize the change for the community.

The CFO and provost of a large flagship public university both recognized the need for change. Their operating expenses were outgrowing their operating revenues, and state funding had precipitously declined amid budget pressures. Though the university was not yet in distress, the leaders wanted to act before circumstances became more dire. Leaders were aware, however, that the university had undertaken several large initiatives over the preceding three years, and the community was wary of another significant effort. To help tie together what had previously been more siloed efforts, the university linked the financial transformation to prior initiatives tied to the teaching and research mission. Leaders linked every opportunity area that was explored—such as research, student success, and marketing optimization—to how it was enabling a greater “return on mission” for the university. Ultimately, through the community rallying around their common goal of teaching, research, and the public good, the community developed initiatives to generate and implement innovative ideas to support the institution.

In the first year of the transformation, the university realized more than $30 million of revenue generation or cost savings, and it put itself on the path to almost $100 million in improvements the following year. More importantly, this net benefit to the university also enabled investments in critical mission activities to support research growth, student advising and wellness, and more flexibility for students through expanded summer offerings.

Take a comprehensive approach across both growth and efficiencies

Cost-reduction measures can often lead to decreased employee morale and can impact student outcomes. But targeting strategic growth can expand the impact of an institution’s mission and establish a more financially resilient university.

In response to the COVID-19 crisis, many universities turned to cost savings as immediate opportunities to improve their near-term financial outlook. While this was necessary, cost-reduction measures can often lead to decreased employee morale, and, in the worst case, they can impact student outcomes. Targeting strategic growth, in a few ways, can help provide inspiration for the community, expand the impact of an institution’s mission, and establish a more financially resilient university.

• Review student outcomes and revenue-generating and operating activities. Conduct a comprehensive review and analyze the findings to understand opportunities to grow. Key areas to explore include the program portfolio, endowment returns, and student support and service (exhibit).
• Ensure messaging to the community focuses on strategic growth ambitions as well as efficiency. University stakeholders require inspiration to help them overcome financial strain. Areas of growth can provide an optimistic outlook to help the community through the required change.

In recent years, a midsize not-for-profit religious university had faced a decreasing surplus with declining enrollment and retention paired with steady increases in costs, which was only exacerbated by the COVID-19 pandemic. Leaders wanted to solidify the university’s financial situation for future mission-based investments while diversifying its student base through targeted growth. But prior implementation of cost measures had been met with significant resistance from university faculty and staff.

University leaders realized they needed to implement a comprehensive approach focused on not only costs but also revenue; in addition to transparently framing the need to save costs to pursue future priorities, they highlighted detailed plans for strategic revenue generation. The president rallied the community for an all-hands-on-deck effort to solve the financial gap while maintaining student experience. They instituted a clear process to evaluate the ideas generated by the community and to allow for quick decisions. Ultimately, through reframing what it meant to “put the community first” and providing community members with inspirational initiatives in addition to the more challenging efforts, the president and school leaders were able to implement decisions with stakeholder support.

Indeed, within just four months, the administration was able to present a detailed outline to meet savings goals, and the university achieved 3 to 5 percent annual budget value improvement within four months of acting on this plan.

Build muscle for change

Throughout the COVID-19 pandemic, many institutions have relied on short-term efforts that may help them survive the crisis but will not change their long-term trajectory. An effective transformation builds the capacity for sustained change and continuous improvement rather than implementing short-term changes to survive a crisis.

• Establish a central transformation team. Use this team to provide support to overcome barriers and accountability to achieve objectives; run a regular cadence to ensure timely execution.
• Detail a transparent and objective decision-making process. Clearly detail what information is required to evaluate an idea and communicate how leadership will use this information to determine what moves forward. The clarity builds confidence within the community around a fair and objective process that all can participate in.
• Improve organizational capabilities. Invest in growing individual and collective capacity through dedicated training aimed at expanding the talent bench and ensuring the longevity of the transformation.

Leaders at a large Research I public university drove a transformation around the four best practices previously described to fundamentally alter their operating model. In the first 12 months, they succeeded in establishing new, objective ways to evaluate and execute on ideas. In the final six months of the transformation, the university focused on sustainability and established a team to help maintain the new habits and procedures. This central implementation team not only continues to drive the transformation forward but also is adapting the process for other parts of the organization—for example, evaluating new budget requests—thus broadening the impact and ingraining the change throughout the organization.

Higher-education institutions are under tremendous pressure and time constraints as they work to keep their students, faculty, and staff safe while they deliver on their missions to educate, conduct research, and contribute to their communities, society, and the public good. In a sector that is already feeling stretched, the prospects of a comprehensive transformation might sound overwhelming to leaders and the communities they lead. But the effort will be worth it.

Leaders can inspire their communities with a more resilient future state that allows them to see beyond the pandemic to focus on improving the well-being of individuals and society through inspired learning, growth, and change. By implementing an ambitious set of projects to inspire the entire team, foster new areas of growth, and change the university’s trajectory, these institutions can continue to influence and impact generations of learners and their communities.

Hamilton Boggs is an associate partner in McKinsey’s Denver office, Rachel Boroditsky is a consultant in the Chicago office, Charag Krishnan is a partner in the New Jersey office, and Jimmy Sarakatsannis is a partner in the Washington, DC, office.

The authors would like thank Claudio Brasca, Leah Farmer, Jack Guest, and Mark Hojnacki for their contributions to this article.

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The Role of Higher Education Institutions in the Transformation of Future-Fit Education

Education is a critical driver of the 2030 Agenda . Higher Education Institutions (HEIs) including universities and colleges worldwide are preparing future professionals, conducting meaningful research, and engaging with the community and stakeholders to tackle local, national, regional, and global challenges. These HEIs are at the forefront of the solutions required to advance the Sustainable Development Goals, which underscores the fundamental role of education in creating healthy and inclusive societies as envisioned in the 2030 Agenda. 

The role of HEIs is not confined to that exclusively of higher education per se. In practice, the contribution of HEIs is quite significant to creating a continuum between all levels of education while training future and current teachers, making curricula adjustments and developing new curricula, nurturing ideas and new pedagogical approaches, instilling fundamental values through various learning methods and platforms, and cultivating innovations -including technological ones- to improve the educational experience and educational outcomes.

The debate about the education we need for the future largely depends on the complexities we face and the several conflicting crises and emergencies around us. In this sense, universities and colleges are very well placed to assess such challenges and how they can be addressed. To analyze this, the  United Nations Academic Impact (UNAI)  within the context of the Transforming Education Summit convened by the United Nations, co-organized this event to be hosted by the Center for Global Affairs of New York University , a UNAI member institution in the United States:

Topic: THE ROLE OF HIGHER EDUCATION INSTITUTIONS IN THE TRANSFORMATION OF FUTURE-FIT EDUCATION

Date:  Thursday, 22 September 2022

Time:  10am - 12:30pm (EDT/New York time)

Venue: New York University (United States), with broadcast (further details to be announced prior to the event)

RSVP/Registration form:   Click here

Those who would like to attend this event in-person will need to upload proof of vaccination and booster if eligible to the New York University (NYU) portal and show a "Green" Daily Screener pass upon entry to the campus. Attendees will also be required to follow any mask requirements or COVID-19-related protocols in place. Attendees will receive more information via e-mail about accessing the campus 1-2 weeks before the event.

As of now, registrations for attending in-person are no longer possible.

Please note that UNAI cannot cover travel-related expenses to attend this event, if you decide to do so in-person. 

No certificate of attendance or participation will be provided.

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First panel:   The role of higher education in the transformation of education for the realization of the SDGs

• Mr. Robert Skinner , Deputy Director and Chief of Partnerships and Global Engagement at the Outreach Division of the United Nations Department for Global Communications

Presenters:

• Dr. Carolyn Kissane , Clinical Professor, Academic Director of the graduate programs in Global Affairs and Global Security, Conflict and Cybercrime at the Center for Global Affairs, and Director of the SPS Energy, Climate Justice and Sustainability Lab of New York University (United States)
• Mr. Sarmad Khan , Board Director of the Academic Council on the United Nations System. Co-author of the upcoming book The Sustainable University of the Future: Reimagining Higher Education and Research . Former Head and Senior Policy Adviser of the Resident Coordinator System Leadership Branch at the United Nations Development Operations Coordination Office.  
• Dr. Patrick Paul Walsh , Vice President of Education and Director of the SDG Academy at the Sustainable Development Solutions Network. Professor of International Development Studies and Director of the Centre for Sustainable Development Studies at the University College Dublin (Ireland)
• Dr. Mette Morsing , Head of Principles for Responsible Management Education - PRME) at the United Nations Global Compact. Previous Professor, Misum Chair and Executive Director of the Misum Center for Sustainable Markets, Stockholm School of Economics (Sweden)
• Dr. Priyadarshani Joshi , Senior Research Officer at the Global Education Monitoring Report of the United Nations Educational, Scientific and Cultural Organization – UNESCO. Specialist on Non-State Actors in Education and Education’s Role in the Sustainable Development Goals

Second panel:   Best practices and case studies from the UNAI SDG Hubs

• Dr. Waheguru Pal Singh , Clinical Professor and Director of the United Nations Specialization at the Center for Global Affairs of New York University (United States). Co-Author of the book The Future of Global Affairs Managing Discontinuity, Disruption and Destruction [2021]
• Prof. Juan José Vásquez , Legal Advisor and Professor of Conflict Resolution, Peace and Mediation at the University for Peace (Costa Rica) / SDG Hub for Goal 12
• Prof. Katja Enberg , Professor at the Department of Biological Sciences of the University of Bergen (Norway) / SDG Hub for Goal 14
• Prof. Sheryl Hendriks , Professor and Head of the Department of Agricultural Economics, Extension and Rural Development at the University of Pretoria (South Africa) / SDG Hub for Goal 2
• Dr. Jonas Richard , Professor and Head of the Department of Social Work at Kristu Jayanti College (India) / SDG Hub for Goal 1

Goal of the Month | May 2024: Goal 15 - Life on Land

How UNAI SDG Hub 7 is setting a tree planting initiative against climate change

Since 2020, the National and Kapodistrian University of Athens, Energy Policy and Development Centre (KEPA) has led a tree planting initiative to celebrate the anniversary of the United Nations. In its first phase includes the planting of 4,984 trees that correspond to more than 105 tons of sequestrated CO2 per year, showcasing that trees are the silent allies for facing climate change. KEPA continues to serve as UNAI SDG Hub 7, to participate in the efforts to ensure access to clean and affordable energy for all.  

Panel discussion on "Strengthening Gender Equality in Generative AI"

This event aimed to facilitate a discourse on academic research related to generative AI with a specific focus on advancing, promoting, and safeguarding gender equality. It will delve into the incorporation of human flaws, such as gender bias, into generative AI systems and emphasize the responsibility of academia and users in ensuring gender equality within these applications.

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• Research article
• Open access
• Published: 24 April 2023

Artificial intelligence in higher education: the state of the field

• Helen Crompton   ORCID: orcid.org/0000-0002-1775-8219 1 , 3 &
• Diane Burke 2  

International Journal of Educational Technology in Higher Education volume  20 , Article number:  22 ( 2023 ) Cite this article

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This systematic review provides unique findings with an up-to-date examination of artificial intelligence (AI) in higher education (HE) from 2016 to 2022. Using PRISMA principles and protocol, 138 articles were identified for a full examination. Using a priori, and grounded coding, the data from the 138 articles were extracted, analyzed, and coded. The findings of this study show that in 2021 and 2022, publications rose nearly two to three times the number of previous years. With this rapid rise in the number of AIEd HE publications, new trends have emerged. The findings show that research was conducted in six of the seven continents of the world. The trend has shifted from the US to China leading in the number of publications. Another new trend is in the researcher affiliation as prior studies showed a lack of researchers from departments of education. This has now changed to be the most dominant department. Undergraduate students were the most studied students at 72%. Similar to the findings of other studies, language learning was the most common subject domain. This included writing, reading, and vocabulary acquisition. In examination of who the AIEd was intended for 72% of the studies focused on students, 17% instructors, and 11% managers. In answering the overarching question of how AIEd was used in HE, grounded coding was used. Five usage codes emerged from the data: (1) Assessment/Evaluation, (2) Predicting, (3) AI Assistant, (4) Intelligent Tutoring System (ITS), and (5) Managing Student Learning. This systematic review revealed gaps in the literature to be used as a springboard for future researchers, including new tools, such as Chat GPT.

A systematic review examining AIEd in higher education (HE) up to the end of 2022.

Unique findings in the switch from US to China in the most studies published.

A two to threefold increase in studies published in 2021 and 2022 to prior years.

AIEd was used for: Assessment/Evaluation, Predicting, AI Assistant, Intelligent Tutoring System, and Managing Student Learning.

Introduction

The use of artificial intelligence (AI) in higher education (HE) has risen quickly in the last 5 years (Chu et al., 2022 ), with a concomitant proliferation of new AI tools available. Scholars (viz., Chen et al., 2020 ; Crompton et al., 2020 , 2021 ) report on the affordances of AI to both instructors and students in HE. These benefits include the use of AI in HE to adapt instruction to the needs of different types of learners (Verdú et al., 2017 ), in providing customized prompt feedback (Dever et al., 2020 ), in developing assessments (Baykasoğlu et al., 2018 ), and predict academic success (Çağataylı & Çelebi, 2022 ). These studies help to inform educators about how artificial intelligence in education (AIEd) can be used in higher education.

Nonetheless, a gap has been highlighted by scholars (viz., Hrastinski et al., 2019 ; Zawacki-Richter et al., 2019 ) regarding an understanding of the collective affordances provided through the use of AI in HE. Therefore, the purpose of this study is to examine extant research from 2016 to 2022 to provide an up-to-date systematic review of how AI is being used in the HE context.

Artificial intelligence has become pervasive in the lives of twenty-first century citizens and is being proclaimed as a tool that can be used to enhance and advance all sectors of our lives (Górriz et al., 2020 ). The application of AI has attracted great interest in HE which is highly influenced by the development of information and communication technologies (Alajmi et al., 2020 ). AI is a tool used across subject disciplines, including language education (Liang et al., 2021 ), engineering education (Shukla et al., 2019 ), mathematics education (Hwang & Tu, 2021 ) and medical education (Winkler-Schwartz et al., 2019 ),

Artificial intelligence

The term artificial intelligence is not new. It was coined in 1956 by McCarthy (Cristianini, 2016 ) who followed up on the work of Turing (e.g., Turing, 1937 , 1950 ). Turing described the existence of intelligent reasoning and thinking that could go into intelligent machines. The definition of AI has grown and changed since 1956, as there has been significant advancements in AI capabilities. A current definition of AI is “computing systems that are able to engage in human-like processes such as learning, adapting, synthesizing, self-correction and the use of data for complex processing tasks” (Popenici et al., 2017 , p. 2). The interdisciplinary interest from scholars from linguistics, psychology, education, and neuroscience who connect AI to nomenclature, perceptions and knowledge in their own disciplines could create a challenge when defining AI. This has created the need to create categories of AI within specific disciplinary areas. This paper focuses on the category of AI in Education (AIEd) and how AI is specifically used in higher educational contexts.

As the field of AIEd is growing and changing rapidly, there is a need to increase the academic understanding of AIEd. Scholars (viz., Hrastinski et al., 2019 ; Zawacki-Richter et al., 2019 ) have drawn attention to the need to increase the understanding of the power of AIEd in educational contexts. The following section provides a summary of the previous research regarding AIEd.

Extant systematic reviews

This growing interest in AIEd has led scholars to investigate the research on the use of artificial intelligence in education. Some scholars have conducted systematic reviews to focus on a specific subject domain. For example, Liang et. al. ( 2021 ) conducted a systematic review and bibliographic analysis the roles and research foci of AI in language education. Shukla et. al. ( 2019 ) focused their longitudinal bibliometric analysis on 30 years of using AI in Engineering. Hwang and Tu ( 2021 ) conducted a bibliometric mapping analysis on the roles and trends in the use of AI in mathematics education, and Winkler-Schwartz et. al. ( 2019 ) specifically examined the use of AI in medical education in looking for best practices in the use of machine learning to assess surgical expertise. These studies provide a specific focus on the use of AIEd in HE but do not provide an understanding of AI across HE.

On a broader view of AIEd in HE, Ouyang et. al. ( 2022 ) conducted a systematic review of AIEd in online higher education and investigated the literature regarding the use of AI from 2011 to 2020. The findings show that performance prediction, resource recommendation, automatic assessment, and improvement of learning experiences are the four main functions of AI applications in online higher education. Salas-Pilco and Yang ( 2022 ) focused on AI applications in Latin American higher education. The results revealed that the main AI applications in higher education in Latin America are: (1) predictive modeling, (2) intelligent analytics, (3) assistive technology, (4) automatic content analysis, and (5) image analytics. These studies provide valuable information for the online and Latin American context but not an overarching examination of AIEd in HE.

Studies have been conducted to examine HE. Hinojo-Lucena et. al. ( 2019 ) conducted a bibliometric study on the impact of AIEd in HE. They analyzed the scientific production of AIEd HE publications indexed in Web of Science and Scopus databases from 2007 to 2017. This study revealed that most of the published document types were proceedings papers. The United States had the highest number of publications, and the most cited articles were about implementing virtual tutoring to improve learning. Chu et. al. ( 2022 ) reviewed the top 50 most cited articles on AI in HE from 1996 to 2020, revealing that predictions of students’ learning status were most frequently discussed. AI technology was most frequently applied in engineering courses, and AI technologies most often had a role in profiling and prediction. Finally, Zawacki-Richter et. al. ( 2019 ) analyzed AIEd in HE from 2007 to 2018 to reveal four primary uses of AIEd: (1) profiling and prediction, (2) assessment and evaluation, (3) adaptive systems and personalization, and (4) intelligent tutoring systems. There do not appear to be any studies examining the last 2 years of AIEd in HE, and these authors describe the rapid speed of both AI development and the use of AIEd in HE and call for further research in this area.

Purpose of the study

The purpose of this study is in response to the appeal from scholars (viz., Chu et al., 2022 ; Hinojo-Lucena et al., 2019 ; Zawacki-Richter et al., 2019 ) to research to investigate the benefits and challenges of AIEd within HE settings. As the academic knowledge of AIEd HE finished with studies examining up to 2020, this study provides the most up-to-date analysis examining research through to the end of 2022.

The overarching question for this study is: what are the trends in HE research regarding the use of AIEd? The first two questions provide contextual information, such as where the studies occurred and the disciplines AI was used in. These contextual details are important for presenting the main findings of the third question of how AI is being used in HE.

In what geographical location was the AIEd research conducted, and how has the trend in the number of publications evolved across the years?

What departments were the first authors affiliated with, and what were the academic levels and subject domains in which AIEd research was being conducted?

Who are the intended users of the AI technologies and what are the applications of AI in higher education?

A PRISMA systematic review methodology was used to answer three questions guiding this study. PRISMA principles (Page et al., 2021 ) were used throughout the study. The PRISMA extension Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Protocols (PRISMA-P; Moher et al., 2015 ) were utilized in this study to provide an a priori roadmap to conduct a rigorous systematic review. Furthermore, the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA principles; Page et al., 2021 ) were used to search, identify, and select articles to be included in the research were used for searching, identifying, and selecting articles, then in how to read, extract, and manage the secondary data gathered from those studies (Moher et al., 2015 , PRISMA Statement, 2021 ). This systematic review approach supports an unbiased synthesis of the data in an impartial way (Hemingway & Brereton, 2009 ). Within the systematic review methodology, extracted data were aggregated and presented as whole numbers and percentages. A qualitative deductive and inductive coding methodology was also used to analyze extant data and generate new theories on the use of AI in HE (Gough et al., 2017 ).

The research begins with the search for the research articles to be included in the study. Based on the research question, the study parameters are defined including the search years, quality and types of publications to be included. Next, databases and journals are selected. A Boolean search is created and used for the search of those databases and journals. Once a set of publications are located from those searches, they are then examined against an inclusion and exclusion criteria to determine which studies will be included in the final study. The relevant data to match the research questions is then extracted from the final set of studies and coded. This method section is organized to describe each of these methods with full details to ensure transparency.

Search strategy

Only peer-reviewed journal articles were selected for examination in this systematic review. This ensured a level of confidence in the quality of the studies selected (Gough et al., 2017 ). The search parameters narrowed the search focus to include studies published in 2016 to 2022. This timeframe was selected to ensure the research was up to date, which is especially important with the rapid change in technology and AIEd.

The data retrieval protocol employed an electronic and a hand search. The electronic search included educational databases within EBSCOhost. Then an additional electronic search was conducted of Wiley Online Library, JSTOR, Science Direct, and Web of Science. Within each of these databases a full text search was conducted. Aligned to the research topic and questions, the Boolean search included terms related to AI, higher education, and learning. The Boolean search is listed in Table 1 . In the initial test search, the terms “machine learning” OR “intelligent support” OR “intelligent virtual reality” OR “chatbot” OR “automated tutor” OR “intelligent agent” OR “expert system” OR “neural network” OR “natural language processing” were used. These were removed as they were subcategories of terms found in Part 1 of the search. Furthermore, inclusion of these specific AI terms resulted in a large number of computer science courses that were focused on learning about AI and not the use of AI in learning.

Part 2 of the search ensured that articles involved formal university education. The terms higher education and tertiary were both used to recognize the different terms used in different countries. The final Boolean search was “Artificial intelligence” OR AI OR “smart technologies” OR “intelligent technologies” AND “higher education” OR tertiary OR graduate OR undergraduate. Scholars (viz., Ouyang et al., 2022 ) who conducted a systematic review on AIEd in HE up to 2020 noted that they missed relevant articles from their study, and other relevant journals should intentionally be examined. Therefore, a hand search was also conducted to include an examination of other journals relevant to AIEd that may not be included in the databases. This is important as the field of AIEd is still relatively new, and journals focused on this field may not yet be indexed in databases. The hand search included: The International Journal of Learning Analytics and Artificial Intelligence in Education, the International Journal of Artificial Intelligence in Education, and Computers & Education: Artificial Intelligence.

Electronic and hand searches resulted in 371 articles for possible inclusion. The search parameters within the electronic database search narrowed the search to articles published from 2016 to 2022, per-reviewed journal articles, and duplicates. Further screening was conducted manually, as each of the 138 articles were reviewed in full by two researchers to examine a match against the inclusion and exclusion criteria found in Table 2 .

The inter-rater reliability was calculated by percentage agreement (Belur et al., 2018 ). The researchers reached a 95% agreement for the coding. Further discussion of misaligned articles resulted in a 100% agreement. This screening process against inclusion and exclusion criteria resulted in the exclusion of 237 articles. This included the duplicates and those removed as part of the inclusion and exclusion criteria, see Fig.  1 . Leaving 138 articles for inclusion in this systematic review.

(From: Page et al., 2021 )

PRISMA flow chart of article identification and screening

The 138 articles were then coded to answer each of the research questions using deductive and inductive coding methods. Deductive coding involves examining data using a priori codes. A priori are pre-determined criteria and this process was used to code the countries, years, author affiliations, academic levels, and domains in the respective groups. Author affiliations were coded using the academic department of the first author of the study. First authors were chosen as that person is the primary researcher of the study and this follows past research practice (e.g., Zawacki-Richter et al., 2019 ). Who the AI was intended for was also coded using the a priori codes of Student, Instructor, Manager or Others. The Manager code was used for those who are involved in organizational tasks, e.g., tracking enrollment. Others was used for those not fitting the other three categories.

Inductive coding was used for the overarching question of this study in examining how the AI was being used in HE. Researchers of extant systematic reviews on AIEd in HE (viz., Chu et al., 2022 ; Zawacki-Richter et al., 2019 ) often used an a priori framework as researchers matched the use of AI to pre-existing frameworks. A grounded coding methodology (Strauss & Corbin, 1995 ) was selected for this study to allow findings of the trends on AIEd in HE to emerge from the data. This is important as it allows a direct understanding of how AI is being used rather than how researchers may think it is being used and fitting the data to pre-existing ideas.

Grounded coding process involved extracting how the AI was being used in HE from the articles. “In vivo” (Saldana, 2015 ) coding was also used alongside grounded coding. In vivo codes are when codes use language directly from the article to capture the primary authors’ language and ensure consistency with their findings. The grounded coding design used a constant comparative method. Researchers identified important text from articles related to the use of AI, and through an iterative process, initial codes led to axial codes with a constant comparison of uses of AI with uses of AI, then of uses of AI with codes, and codes with codes. Codes were deemed theoretically saturated when the majority of the data fit with one of the codes. For both the a priori and the grounded coding, two researchers coded and reached an inter-rater percentage agreement of 96%. After discussing misaligned articles, a 100% agreement was achieved.

Findings and discussion

The findings and discussion section are organized by the three questions guiding this study. The first two questions provide contextual information on the AIEd research, and the final question provides a rigorous investigation into how AI is being used in HE.

RQ1. In what geographical location was the AIEd research conducted, and how has the trend in the number of publications evolved across the years?

The 138 studies took place across 31 countries in six of seven continents of the world. Nonetheless, that distribution was not equal across continents. Asia had the largest number of AIEd studies in HE at 41%. Of the seven countries represented in Asia, 42 of the 58 studies were conducted in Taiwan and China. Europe, at 30%, was the second largest continent and had 15 countries ranging from one to eight studies a piece. North America, at 21% of the studies was the continent with the third largest number of studies, with the USA producing 21 of the 29 studies in that continent. The 21 studies from the USA places it second behind China. Only 1% of studies were conducted in South America and 2% in Africa. See Fig.  2 for a visual representation of study distribution across countries. Those continents with high numbers of studies are from high income countries and those with low numbers have a paucity of publications in low-income countries.

Geographical distribution of the AIEd HE studies

Data from Zawacki-Richter et. al.’s ( 2019 ) 2007–2018 systematic review examining countries found that the USA conducted the most studies across the globe at 43 out of 146, and China had the second largest at eleven of the 146 papers. Researchers have noted a rapid trend in Chinese researchers publishing more papers on AI and securing more patents than their US counterparts in a field that was originally led by the US (viz., Li et al., 2021 ). The data from this study corroborate this trend in China leading in the number of AIEd publications.

With the accelerated use of AI in society, gathering data to examine the use of AIEd in HE is useful in providing the scholarly community with specific information on that growth and if it is as prolific as anticipated by scholars (e.g., Chu et al., 2022 ). The analysis of data of the 138 studies shows that the trend towards the use of AIEd in HE has greatly increased. There is a drop in 2019, but then a great rise in 2021 and 2022; see Fig.  3 .

Chronological trend in AIEd in HE

Data on the rise in AIEd in HE is similar to the findings of Chu et. al. ( 2022 ) who noted an increase from 1996 to 2010 and 2011–2020. Nonetheless Chu’s parameters are across decades, and the rise is to be anticipated with a relatively new technology across a longitudinal review. Data from this study show a dramatic rise since 2020 with a 150% increase from the prior 2 years 2020–2019. The rise in 2021 and 2022 in HE could have been caused by the vast increase in HE faculty having to teach with technology during the pandemic lockdown. Faculty worldwide were using technologies, including AI, to explore how they could continue teaching and learning that was often face-to-face prior to lockdown. The disadvantage of this rapid adoption of technology is that there was little time to explore the possibilities of AI to transform learning, and AI may have been used to replicate past teaching practices, without considering new strategies previously inconceivable with the affordances of AI.

However, in a further examination of the research from 2021 to 2022, it appears that there are new strategies being considered. For example, Liu et. al.’s, 2022 study used AIEd to provide information on students’ interactions in an online environment and examine their cognitive effort. In Yao’s study in 2022, he examined the use of AI to determine student emotions while learning.

RQ2. What departments were the first authors affiliated with, and what were the academic levels and subject domains in which AIEd research was being conducted?

Department affiliations

Data from the AIEd HE studies show that of the first authors were most frequently from colleges of education (28%), followed by computer science (20%). Figure  4 presents the 15 academic affiliations of the authors found in the studies. The wide variety of affiliations demonstrate the variety of ways AI can be used in various educational disciplines, and how faculty in diverse areas, including tourism, music, and public affairs were interested in how AI can be used for educational purposes.

Research affiliations

In an extant AIED HE systematic review, Zawacki-Richter et. al.’s ( 2019 ) named their study Systematic review of research on artificial intelligence applications in higher education—where are the educators? In this study, the authors were keen to highlight that of the AIEd studies in HE, only six percent were written by researchers directly connected to the field of education, (i.e., from a college of education). The researchers found a great lack in pedagogical and ethical implications of implementing AI in HE and that there was a need for more educational perspectives on AI developments from educators conducting this work. It appears from our data that educators are now showing greater interest in leading these research endeavors, with the highest affiliated group belonging to education. This may again be due to the pandemic and those in the field of education needing to support faculty in other disciplines, and/or that they themselves needed to explore technologies for their own teaching during the lockdown. This may also be due to uptake in professors in education becoming familiar with AI tools also driven by a societal increased attention. As the focus of much research by education faculty is on teaching and learning, they are in an important position to be able to share their research with faculty in other disciplines regarding the potential affordances of AIEd.

Academic levels

The a priori coding of academic levels show that the majority of studies involved undergraduate students with 99 of the 138 (72%) focused on these students. This was in comparison to the 12 of 138 (9%) for graduate students. Some of the studies used AI for both academic levels: see Fig.  5

Academic level distribution by number of articles

This high percentage of studies focused on the undergraduate population was congruent with an earlier AIED HE systematic review (viz., Zawacki-Richter et al., 2019 ) who also reported student academic levels. This focus on undergraduate students may be due to the variety of affordances offered by AIEd, such as predictive analytics on dropouts and academic performance. These uses of AI may be less required for graduate students who already have a record of performance from their undergraduate years. Another reason for this demographic focus can also be convenience sampling, as researchers in HE typically has a much larger and accessible undergraduate population than graduates. This disparity between undergraduates and graduate populations is a concern, as AIEd has the potential to be valuable in both settings.

Subject domains

The studies were coded into 14 areas in HE; with 13 in a subject domain and one category of AIEd used in HE management of students; See Fig.  6 . There is not a wide difference in the percentages of top subject domains, with language learning at 17%, computer science at 16%, and engineering at 12%. The management of students category appeared third on the list at 14%. Prior studies have also found AIEd often used for language learning (viz., Crompton et al., 2021 ; Zawacki-Richter et al., 2019 ). These results are different, however, from Chu et. al.’s ( 2022 ) findings that show engineering dramatically leading with 20 of the 50 studies, with other subjects, such as language learning, appearing once or twice. This study appears to be an outlier that while the searches were conducted in similar databases, the studies only included 50 studies from 1996 to 2020.

Subject domains of AIEd in HE

Previous scholars primarily focusing on language learning using AI for writing, reading, and vocabulary acquisition used the affordances of natural language processing and intelligent tutoring systems (e.g., Liang et al., 2021 ). This is similar to the findings in studies with AI used for automated feedback of writing in a foreign language (Ayse et al., 2022 ), and AI translation support (Al-Tuwayrish, 2016 ). The large use of AI for managerial activities in this systematic review focused on making predictions (12 studies) and then admissions (three studies). This is positive to see this use of AI to look across multiple databases to see trends emerging from data that may not have been anticipated and cross referenced before (Crompton et al., 2022 ). For example, to examine dropouts, researchers may consider examining class attendance, and may not examine other factors that appear unrelated. AI analysis can examine all factors and may find that dropping out is due to factors beyond class attendance.

RQ3. Who are the intended users of the AI technologies and what are the applications of AI in higher education?

Intended user of AI

Of the 138 articles, the a priori coding shows that 72% of the studies focused on Students, followed by a focus on Instructors at 17%, and Managers at 11%, see Fig.  7 . The studies provided examples of AI being used to provide support to students, such as access to learning materials for inclusive learning (Gupta & Chen, 2022 ), provide immediate answers to student questions, self-testing opportunities (Yao, 2022 ), and instant personalized feedback (Mousavi et al., 2020 ).

Intended user

The data revealed a large emphasis on students in the use of AIEd in HE. This user focus is different from a recent systematic review on AIEd in K-12 that found that AIEd studies in K-12 settings prioritized teachers (Crompton et al., 2022 ). This may appear that HE uses AI to focus more on students than in K-12. However, this large number of student studies in HE may be due to the student population being more easily accessibility to HE researchers who may study their own students. The ethical review process is also typically much shorter in HE than in K-12. Therefore, the data on the intended focus should be reviewed while keeping in mind these other explanations. It was interesting that Managers were the lowest focus in K-12 and also in this study in HE. AI has great potential to collect, cross reference and examine data across large datasets that can allow data to be used for actionable insight. More focus on the use of AI by managers would tap into this potential.

How is AI used in HE

Using grounded coding, the use of AIEd from each of the 138 articles was examined and six major codes emerged from the data. These codes provide insight into how AI was used in HE. The five codes are: (1) Assessment/Evaluation, (2) Predicting, (3) AI Assistant, (4) Intelligent Tutoring System (ITS), and (5) Managing Student Learning. For each of these codes there are also axial codes, which are secondary codes as subcategories from the main category. Each code is delineated below with a figure of the codes with further descriptive information and examples.

Assessment/evaluation

Assessment and Evaluation was the most common use of AIEd in HE. Within this code there were six axial codes broken down into further codes; see Fig.  8 . Automatic assessment was most common, seen in 26 of the studies. It was interesting to see that this involved assessment of academic achievement, but also other factors, such as affect.

Codes and axial codes for assessment and evaluation

Automatic assessment was used to support a variety of learners in HE. As well as reducing the time it takes for instructors to grade (Rutner & Scott, 2022 ), automatic grading showed positive use for a variety of students with diverse needs. For example, Zhang and Xu ( 2022 ) used automatic assessment to improve academic writing skills of Uyghur ethnic minority students living in China. Writing has a variety of cultural nuances and in this study the students were shown to engage with the automatic assessment system behaviorally, cognitively, and affectively. This allowed the students to engage in self-regulated learning while improving their writing.

Feedback was a description often used in the studies, as students were given text and/or images as feedback as a formative evaluation. Mousavi et. al. ( 2020 ) developed a system to provide first year biology students with an automated personalized feedback system tailored to the students’ specific demographics, attributes, and academic status. With the unique feature of AIEd being able to analyze multiple data sets involving a variety of different students, AI was used to assess and provide feedback on students’ group work (viz., Ouatik et al., 2021 ).

AI also supports instructors in generating questions and creating multiple question tests (Yang et al., 2021 ). For example, (Lu et al., 2021 ) used natural language processing to create a system that automatically created tests. Following a Turing type test, researchers found that AI technologies can generate highly realistic short-answer questions. The ability for AI to develop multiple questions is a highly valuable affordance as tests can take a great deal of time to make. However, it would be important for instructors to always confirm questions provided by the AI to ensure they are correct and that they match the learning objectives for the class, especially in high value summative assessments.

The axial code within assessment and evaluation revealed that AI was used to review activities in the online space. This included evaluating student’s reflections, achievement goals, community identity, and higher order thinking (viz., Huang et al., 2021 ). Three studies used AIEd to evaluate educational materials. This included general resources and textbooks (viz., Koć‑Januchta et al., 2022 ). It is interesting to see the use of AI for the assessment of educational products, rather than educational artifacts developed by students. While this process may be very similar in nature, this shows researchers thinking beyond the traditional use of AI for assessment to provide other affordances.

Predicting was a common use of AIEd in HE with 21 studies focused specifically on the use of AI for forecasting trends in data. Ten axial codes emerged on the way AI was used to predict different topics, with nine focused on predictions regarding students and the other on predicting the future of higher education. See Fig.  9 .

Predicting axial codes

Extant systematic reviews on HE highlighted the use of AIEd for prediction (viz., Chu et al., 2022 ; Hinojo-Lucena et al., 2019 ; Ouyang et al., 2022 ; Zawacki-Richter et al., 2019 ). Ten of the articles in this study used AI for predicting academic performance. Many of the axial codes were often overlapping, such as predicting at risk students, and predicting dropouts; however, each provided distinct affordances. An example of this is the study by Qian et. al. ( 2021 ). These researchers examined students taking a MOOC course. MOOCs can be challenging environments to determine information on individual students with the vast number of students taking the course (Krause & Lowe, 2014 ). However, Qian et al., used AIEd to predict students’ future grades by inputting 17 different learning features, including past grades, into an artificial neural network. The findings were able to predict students’ grades and highlight students at risk of dropping out of the course.

In a systematic review on AIEd within the K-12 context (viz., Crompton et al., 2022 ), prediction was less pronounced in the findings. In the K-12 setting, there was a brief mention of the use of AI in predicting student academic performance. One of the studies mentioned students at risk of dropping out, but this was immediately followed by questions about privacy concerns and describing this as “sensitive”. The use of prediction from the data in this HE systematic review cover a wide range of AI predictive affordances. students Sensitivity is still important in a HE setting, but it is positive to see the valuable insight it provides that can be used to avoid students failing in their goals.

AI assistant

The studies evaluated in this review indicated that the AI Assistant used to support learners had a variety of different names. This code included nomenclature such as, virtual assistant, virtual agent, intelligent agent, intelligent tutor, and intelligent helper. Crompton et. al. ( 2022 ), described the difference in the terms to delineate the way that the AI appeared to the user. For example, if there was an anthropomorphic presence to the AI, such as an avatar, or if the AI appeared to support via other means, such as text prompt. The findings of this systematic review align to Crompton et. al.’s ( 2022 ) descriptive differences of the AI Assistant. Furthermore, this code included studies that provide assistance to students, but may not have specifically used the word assistance. These include the use of chatbots for student outreach, answering questions, and providing other assistance. See Fig.  10 for the axial codes for AI Assistant.

AI assistant axial codes

Many of these assistants offered multiple supports to students, such as Alex , the AI described as a virtual change agent in Kim and Bennekin’s ( 2016 ) study. Alex interacted with students in a college mathematics course by asking diagnostic questions and gave support depending on student needs. Alex’s support was organized into four stages: (1) goal initiation (“Want it”), (2) goal formation (“Plan for it”), (3) action control (“Do it”), and (4) emotion control (“Finish it”). Alex provided responses depending on which of these four areas students needed help. These messages supported students with the aim of encouraging persistence in pursuing their studies and degree programs and improving performance.

The role of AI in providing assistance connects back to the seminal work of Vygotsky ( 1978 ) and the Zone of Proximal Development (ZPD). ZPD highlights the degree to which students can rapidly develop when assisted. Vygotsky described this assistance often in the form of a person. However, with technological advancements, the use of AI assistants in these studies are providing that support for students. The affordances of AI can also ensure that the support is timely without waiting for a person to be available. Also, assistance can consider aspects on students’ academic ability, preferences, and best strategies for supporting. These features were evident in Kim and Bennekin’s ( 2016 ) study using Alex.

Intelligent tutoring system

The use of Intelligent Tutoring Systems (ITS) was revealed in the grounded coding. ITS systems are adaptive instructional systems that involve the use of AI techniques and educational methods. An ITS system customizes educational activities and strategies based on student’s characteristics and needs (Mousavinasab et al., 2021 ). While ITS may be an anticipated finding in AIED HE systematic reviews, it was interesting that extant reviews similar to this study did not always describe their use in HE. For example, Ouyang et. al. ( 2022 ), included “intelligent tutoring system” in search terms describing it as a common technique, yet ITS was not mentioned again in the paper. Zawacki-Richter et. al. ( 2019 ) on the other hand noted that ITS was in the four overarching findings of the use of AIEd in HE. Chu et. al. ( 2022 ) then used Zawacki-Richter’s four uses of AIEd for their recent systematic review.

In this systematic review, 18 studies specifically mentioned that they were using an ITS. The ITS code did not necessitate axial codes as they were performing the same type of function in HE, namely, in providing adaptive instruction to the students. For example, de Chiusole et. al. ( 2020 ) developed Stat-Knowlab, an ITS that provides the level of competence and best learning path for each student. Thus Stat-Knowlab personalizes students’ learning and provides only educational activities that the student is ready to learn. This ITS is able to monitor the evolution of the learning process as the student interacts with the system. In another study, Khalfallah and Slama ( 2018 ) built an ITS called LabTutor for engineering students. LabTutor served as an experienced instructor in enabling students to access and perform experiments on laboratory equipment while adapting to the profile of each student.

The student population in university classes can go into the hundreds and with the advent of MOOCS, class sizes can even go into the thousands. Even in small classes of 20 students, the instructor cannot physically provide immediate unique personalize questions to each student. Instructors need time to read and check answers and then take further time to provide feedback before determining what the next question should be. Working with the instructor, AIEd can provide that immediate instruction, guidance, feedback, and following questioning without delay or becoming tired. This appears to be an effective use of AIEd, especially within the HE context.

Managing student learning

Another code that emerged in the grounded coding was focused on the use of AI for managing student learning. AI is accessed to manage student learning by the administrator or instructor to provide information, organization, and data analysis. The axial codes reveal the trends in the use of AI in managing student learning; see Fig.  11 .

Learning analytics was an a priori term often found in studies which describes “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs” (Long & Siemens, 2011 , p. 34). The studies investigated in this systematic review were across grades and subject areas and provided administrators and instructors different types of information to guide their work. One of those studies was conducted by Mavrikis et. al. ( 2019 ) who described learning analytics as teacher assistance tools. In their study, learning analytics were used in an exploratory learning environment with targeted visualizations supporting classroom orchestration. These visualizations, displayed as screenshots in the study, provided information such as the interactions between the students, goals achievements etc. These appear similar to infographics that are brightly colored and draw the eye quickly to pertinent information. AI is also used for other tasks, such as organizing the sequence of curriculum in pacing guides for future groups of students and also designing instruction. Zhang ( 2022 ) described how designing an AI teaching system of talent cultivation and using the digital affordances to establish a quality assurance system for practical teaching, provides new mechanisms for the design of university education systems. In developing such a system, Zhang found that the stability of the instructional design, overcame the drawbacks of traditional manual subjectivity in the instructional design.

Another trend that emerged from the studies was the use of AI to manage student big data to support learning. Ullah and Hafiz ( 2022 ) lament that using traditional methods, including non-AI digital techniques, asking the instructor to pay attention to every student’s learning progress is very difficult and that big data analysis techniques are needed. The ability to look across and within large data sets to inform instruction is a valuable affordance of AIEd in HE. While the use of AIEd to manage student learning emerged from the data, this study uncovered only 19 studies in 7 years (2016–2022) that focused on the use of AIEd to manage student data. This lack of the use was also noted in a recent study in the K-12 space (Crompton et al., 2022 ). In Chu et. al.’s ( 2022 ) study examining the top 50 most cited AIEd articles, they did not report the use of AIEd for managing student data in the top uses of AIEd HE. It would appear that more research should be conducted in this area to fully explore the possibilities of AI.

Gaps and future research

From this systematic review, six gaps emerged in the data providing opportunities for future studies to investigate and provide a fuller understanding of how AIEd can used in HE. (1) The majority of the research was conducted in high income countries revealing a paucity of research in developing countries. More research should be conducted in these developing countries to expand the level of understanding about how AI can enhance learning in under-resourced communities. (2) Almost 50% of the studies were conducted in the areas of language learning, computer science and engineering. Research conducted by members from multiple, different academic departments would help to advance the knowledge of the use of AI in more disciplines. (3) This study revealed that faculty affiliated with schools of education are taking an increasing role in researching the use of AIEd in HE. As this body of knowledge grows, faculty in Schools of Education should share their research regarding the pedagogical affordances of AI so that this knowledge can be applied by faculty across disciplines. (4) The vast majority of the research was conducted at the undergraduate level. More research needs to be done at the graduate student level, as AI provides many opportunities in this environment. (5) Little study was done regarding how AIEd can assist both instructors and managers in their roles in HE. The power of AI to assist both groups further research. (6) Finally, much of the research investigated in this systematic review revealed the use of AIEd in traditional ways that enhance or make more efficient current practices. More research needs to focus on the unexplored affordances of AIEd. As AI becomes more advanced and sophisticated, new opportunities will arise for AIEd. Researchers need to be on the forefront of these possible innovations.

In addition, empirical exploration is needed for new tools, such as ChatGPT that was available for public use at the end of 2022. With the time it takes for a peer review journal article to be published, ChatGPT did not appear in the articles for this study. What is interesting is that it could fit with a variety of the use codes found in this study, with students getting support in writing papers and instructors using Chat GPT to assess students work and with help writing emails or descriptions for students. It would be pertinent for researchers to explore Chat GPT.

Limitations

The findings of this study show a rapid increase in the number of AIEd studies published in HE. However, to ensure a level of credibility, this study only included peer review journal articles. These articles take months to publish. Therefore, conference proceedings and gray literature such as blogs and summaries may reveal further findings not explored in this study. In addition, the articles in this study were all published in English which excluded findings from research published in other languages.

In response to the call by Hinojo-Lucena et. al. ( 2019 ), Chu et. al. ( 2022 ), and Zawacki-Richter et. al. ( 2019 ), this study provides unique findings with an up-to-date examination of the use of AIEd in HE from 2016 to 2022. Past systematic reviews examined the research up to 2020. The findings of this study show that in 2021 and 2022, publications rose nearly two to three times the number of previous years. With this rapid rise in the number of AIEd HE publications, new trends have emerged.

The findings show that of the 138 studies examined, research was conducted in six of the seven continents of the world. In extant systematic reviews showed that the US led by a large margin in the number of studies published. This trend has now shifted to China. Another shift in AIEd HE is that while extant studies lamented the lack of focus on professors of education leading these studies, this systematic review found education to be the most common department affiliation with 28% and computer science coming in second at 20%. Undergraduate students were the most studied students at 72%. Similar to the findings of other studies, language learning was the most common subject domain. This included writing, reading, and vocabulary acquisition. In examination of who the AIEd was intended for, 72% of the studies focused on students, 17% instructors, and 11% managers.

Grounded coding was used to answer the overarching question of how AIEd was used in HE. Five usage codes emerged from the data: (1) Assessment/Evaluation, (2) Predicting, (3) AI Assistant, (4) Intelligent Tutoring System (ITS), and (5) Managing Student Learning. Assessment and evaluation had a wide variety of purposes, including assessing academic progress and student emotions towards learning, individual and group evaluations, and class based online community assessments. Predicting emerged as a code with ten axial codes, as AIEd predicted dropouts and at-risk students, innovative ability, and career decisions. AI Assistants were specific to supporting students in HE. These assistants included those with an anthropomorphic presence, such as virtual agents and persuasive intervention through digital programs. ITS systems were not always noted in extant systematic reviews but were specifically mentioned in 18 of the studies in this review. ITS systems in this study provided customized strategies and approaches to student’s characteristics and needs. The final code in this study highlighted the use of AI in managing student learning, including learning analytics, curriculum sequencing, instructional design, and clustering of students.

The findings of this study provide a springboard for future academics, practitioners, computer scientists, policymakers, and funders in understanding the state of the field in AIEd HE, how AI is used. It also provides actionable items to ameliorate gaps in the current understanding. As the use AIEd will only continue to grow this study can serve as a baseline for further research studies in the use of AIEd in HE.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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Strategic management in higher education: conceptual insights, lessons learned, emerging challenges

• Published: 23 January 2024
• Volume 29 , pages 331–339, ( 2023 )

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• Tatiana Fumasoli 1 &
• Myroslava Hladchenko 2  

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Introduction

This editorial presents the special issue on strategic management in higher education. The introduction sets the stage for nine empirical contributions focused on different levels of analysis: institutional field, organisational and individual levels. As regards the field and organisation levels, the issue demonstrates how strategic management matters for university strategic positioning, emergence and early institutionalisation of competition in higher education, organisational strategising in complex and coherent higher education fields, university internationalisation strategy and university sustainable quality management. At the level of individual actors, the issue explores the perception of university strategies by middle managers and international office professionals, as well as the strategies of PhD supervisors. The introduction provides an overview of various theoretical perspectives informing the studies of the special issue e.g. institutional theory, population ecology perspectives, complexity leadership theory, and explores connections between them discussing the implications for a future research agenda.

Background and relevance

Strategy in higher education has been a growing area of research over the last 20 years. Scholars, as well as policy makers and practitioners, have significantly contributed to the body of knowledge related to higher education management and have investigated different aspects of strategy of and in higher education. This has been analysed at the national (Gazizova, 2012 ; Barbato et al., 2019 ), organisational (Vuori, 2016 ; Fumasoli & Lepori, 2011 ; Van Vught & Huisman, 2013 ; Shah & Nair, 2011 ; Luoma et al., 2016 ; Fumasoli et al., 2020 ) and individual (Degn, 2015 ; Ainscough et al., 2018 ; Torrance et al., 2000 ) levels of analysis.

At the organisational level, different dimensions of strategic management have gained prominence: mission statements of higher education institutions (Arias-Coello et al., 2020 ; Seeber et al., 2019 ; Hladchenko, 2016 ), development and implementation of strategic plans (James & Derrick, 2020 ; Morphew et al., 2018 ), use of strategic management tools like SWOT-analysis and Balanced Scorecard (Hladchenko, 2015 ). University strategy has been explored regarding various activities such as teaching (Newton, 2010 ), internationalisation (James & Derrick, 2020 ; Soliman et al., 2019 ; Kristensen & Karlsen, 2018 ; Middlehurst & Woodfield, 2007 ), the articulation of the research-teaching nexus (Couper & Stoakes, 2010 ), application and competition for research funding (Talib & Steele, 2000 ; Litwin, 2009 ; Boezerooij et al., 2007 ), and the marketing promotion of higher education institutions (Milian, 2016 ). The strategy has also been investigated as a response to changing environmental conditions e.g. funding arrangements (Rolfe, 2003 ), as well as, more recently, to the Covid-19 pandemic (Bebbington, 2021 ). An important strand of research has developed around institutional positioning and profile building (Vuori, 2016 ; Fumasoli & Lepori, 2011 ; Van Vught & Huisman, 2013 ; Fumasoli & Huisman, 2013 ; Wilkins & Huisman, 2019 ; Morphew et al., 2018 ; Fumasoli et al., 2020 ).

At the individual level scholars have explored the strategy development and implementation by different higher education actors e.g. academics (Degn, 2018 ), deans and department heads (De Boer & Goedegebuure, 2009 ; Degn, 2015 ; Hladchenko & Benninghoff, 2020 ; Davis, Jansen van Rensburg, & Venter, 2016 , Stansaker & Fumasoli, 2017 ), doctoral candidates (Odena & Burgess, 2017 , students (Ainscough et al., 2018 ; Torrance et al., 2000 ; Lee et al., 2017 ). Strategy as practice has been highlighted as an important approach to understand the complexity of strategy in higher education (Frolich et al., 2013 ).

Strategy has been investigated in different types of higher education institutions e.g. university colleges (Couper and Stoaker 2010 ), universities of applied sciences ( 2016 ), teaching as well as research-intensive universities (Milian, 2016 ). The literature provides views on the strategy of higher education in multiple countries: Finland (Vuori, 2016 ), Denmark (Degn), Canada (Milian, 2016 ), Ukraine (Hladchenko & Benninghoff, 2020 ), South Africa (Davis, Jansen van Rensburg, & Venter, 2016 ), Portugal (Mourato et al., 2019 ), Australia (Shah & Nair, 2011 ). However, strategy of higher education remains underexplored in many national contexts outside Western countries.

Though the body of knowledge on strategy of higher education has grown and developed in recent years, there is, on the one hand, a need for taking stock of this diverse literature; on the other hand, the challenges higher education has been facing more recently require new investigations on how strategic management is understood, operationalized, and on the extent it is impactful. In other words, this special issue aims to bridge the first stage of strategic management studies in higher education to the ongoing and emerging issues universities are facing when they decide their organizational goals and priorities, how to allocate resources, adapt their governance and select the markets in which to operate.

Drawing from these in-depth cases, we aim to contribute to the understanding of the strategic management of higher education according to the following overarching research questions:

How do higher education institutions strategically position themselves in the institutional field of higher education?

What specific strategies do they develop in terms of different aspects of higher education e.g., internationalisation, competition, sustainable quality management?

What role do university leadership and representatives of different administrative and supportive departments play in the strategic management of the higher education institutions?

Articles in the special issue

The following articles provide an diverse and engaging range of analyses seeking to address the questions raised in the strategic management of higher education.

Julian Zipparo explores strategic positioning, and the processes and factors influencing the development and content of university strategies and plans, with lessons then applied to open questions of institutional diversity and its determinants. Following a sector level analysis of the contents of university positioning documents, an in-depth case study is developed of a large Australian university, where the interaction of intra-institutional ‘meso’ layers is explored to show a confluence of factors contributing to positioning. The case demonstrates that institutional positioning involves the selective crafting of narratives for multiple purposes, including the seeking and portrayal of internal cohesion, identity enhancement, and resource seeking. Importantly, while cross-institutional comparison of positioning narratives portrays an undifferentiated and somewhat homogenous sector, positioning is found within the case institution to obscure what is significant internal diversity and complexity. University positioning found within compacts showed that while seeking to differentiate, Australian universities converged upon a distinct set of common foci in relation to research. The homogeneity seen at the level of institutions, however, represents homogeneity of institutional level decisions on research positioning, not homogeneity in terms of the research enterprise itself within (and by extension across) institutions. The University of Sydney represents a case where significant intra-institutional complexity belies coherent positioning, in particular at an institutional level. Institutional-level positions reflect attempts to encourage and reach a degree of consensus within a contested environment with multiple differentiated actors and competing institutional logics. This case suggests that within universities there is likely significant complexity and internal diversity not reflected in institutional representations, which are selective and crafted narratives occurring within a context of normative frameworks and practical constraints.

Kerttu Kettunen, Kimmo Alajoutsijärvi, John Arngrim Hunnes and Rómulo Pinheiro investigate the emergence and early institutionalization of competition in higher education in Finnish business schools. Building on key contri-butions from economics, management studies, sociology, and higher education research, they develop propositions on competition in higher education and formulate the theoretical framework to explore competition in Finnish business schools. Business schools constitute an interesting field for studying competition in higher education because they are the frontrunners and champions of competition-based views in higher education. The main contribution of the study is a novel explanation of the preconditions, emergence, and early processes of institutionalization that drive higher education institutions to compete and collectively produce the observed competitive transformation. From a broader perspective, the Finnish business school case depicts a narrative of interorganizational relationships between higher education institutions transforming from co-existential and cooperative to competitive. The study shows that competition can be an endogenous feature of the business school field, with market-related elements being present from the outset.

Sandra Hasanefendic and Davide Donina address how higher education organizations strategize in complex and coherent fields. Unlike previous studies which looked at either exogenous (field) or endogenous causes in strategizing, this article integrates them to explain organizational responses. They devise a conceptual framework under the premises of new institutional theory in order to connect macro-transformation in the institutional field to the micro-processes of organizational strategizing. The framework highlights that every combination of the analytical dimensions (field and organization) presents additional possible strategizing practices. Then they test it on the responses to the same change in the field (introduction of research mandate) of three universities of applied sciences located in two countries (Portugal and the Netherlands) by analyzing organizational members’ practices. The cross-country perspective allowed to address the non-comparative gap in strategizing research as well as to provide robustness and to improve overall generalizability of findings. Specifically, in relation to the case studies, in the coherent field the organization mirrors field demands internally, whereas in the complex field the organizations exploit the wider repertories of actions legitimized by field actors to develop different strategizing practices. These findings confirm that strategizing emerges as a result of the interconnections between field and internal organizational dynamics and that organizational member practices must be unveiled as they strongly affect strategizing outcomes. The study results support that both field and organizations warrant investigation in strategizing research since it is not possible to determine the strategizing outcomes just from the combination of theoretical dimensions.

Aleksei Egorov and Daria Platonova contribute to the discussion regarding the correlation between strategic planning and changes in operations as perceived by middle managers and performance of higher education institutions. Considering that the strategy development might have different aims and contribute to positioning, fundraising, teambuilding etc., they focus on strategy as a part of change management. The paper presents the institutional context of strategic thinking in the Russian higher education system, and the analysis of changes in universities’ activities with the influence of the strategy implementation. The latter is based on the survey data and represents the perception of universities’ middle managers (faculty deans and research department heads). The analysis of survey data is complemented by the calculation of changes in organizational-level performance indicators. The results suggest that middle managers’ perception of strategies in general correlates to the changes in actual institutional performance indicators. Findings indicate that most of the department heads do not observe any changes at Russian universities following the development of the strategic plan. This occurs because universities are trying to imitate the use of ‘effective’ management practices in order to attract more public resources and to build external legitimacy. The regulator stimulates universities to introduce strategies as management tools, universities respond to this formally, developing a document that does not entail any changes in their activities.

Lois Yin Ching Cheung explored the isomorphic tendency identified across universities mimicking successful models. Among a wide range of strategic tools, organisational legitimacy theory allows universities to focus on exploiting their resources and capability to position idiosyncratically against competitors. This study applies a legitimacy framework on cognitive, moral and pragmatic perspectives, to investigate how universities adopt an internationalisation strategy to achieve the overall institutional objectives. Drawing on a case study of the Hong Kong Polytechnic University (PolyU), the paper explores how the university internationalises in a differentiated position to acquire legitimacy in specific local, regional and global contexts. PolyU strategically emphasises its pragmatic value to connect with its stakeholders in a globalised dimension. The findings broadly support the notion of comprehensive internationalisation; in other words internationalisation strategy is incorporated into other functional strategies to enhance a ‘global’ experience. This finding, while preliminary, raises the significance of local elements in internationalisation strategies, under the influence of soft power from successful higher education systems and constraints of organisational capabilities.

Betul Bulut-Sahin and Orta Dogu investigate the role of international office professionals in the strategic management of internationalization in higher education institutions. The authors assume that key stakeholders in higher education institutions are increasingly involved in the strategy-making process. It is argued that international office. professionals (IPs) are one of these key stakeholders and need to be part of strategy development. The study aims to explore IPs’ conceptualization of internationalization, their needs, and roles in the universities, as well as their perceptions of strategic planning, management, and institutionalization of internationalization in European and Turkish universities. In this qualitative research, 23 semi-structured interviews showed that they are not sufficiently involved in the strategy-making process and could not contribute to it as expected. This non-involvement observed in both settings has led them to imitate quantitative global strategies similar to those of other universities, like increasing the number of international students. Moreover, the comparative analysis showed that European universities utilize more democratic and participatory decision-making than Turkish universities, which have little or no participation of IPs in decision-making on internationalization. Findings highlight that higher education institutions should initiate more structures and processes for strategy development with a constructive dialogue by including key stakeholders — international office professionals, particularly — and local, national, regional, and international participants for a shared understanding of internationalization. For better institutionalization of internationalization, deliberate strategies should include curriculum, research, and campus services and facilities, along with student, academic, and administrative affairs.

Tolga Ozsen, Baris Uslu and Ahmet Aypay present a systematic literature review of strategy adaptation for sustainable quality management. Despite its roots in environmental discussions, sustainability has become a critical term influencing every aspect of organisations. As human-oriented institutions, universities have also embraced the ‘sustainable development’ concept on the quality of their internal and external services. Two overarching questions are most important for university managers to strategically guide sustainable quality development in their institutions: Which strategies do university managers adapt to construct a “sustainable quality management” structure in their universities? And how are these adapted strategies related to different aspects/components of universities? A Systematic Literature Review (SLR) protocol is employed to analyse the existing studies in the related literature. The systematic review included five steps sequentially: (i) defining the research question(s), (ii) setting inclusion–exclusion criteria, (iii) recording eligible studies, (iv) appraising quality of the selected studies, and (v) discussing prominent results. To integrate the results, five enablers in the European Foundation for Quality Management (EFQM) model and the sub-sections given in the European University Association’s (EUA) institutional evaluation reports were used. The results revealed that the initial steps for university leadership to establish a ‘Sustainable Quality Management’ system are integrating a sustainable quality approach to the main strategy document, and then motivating their staff to participate in and enrich the reform-level cultural changes in their universities. This study also discusses the strategies adapted to sustain quality development in universities’ teaching, research, societal services, and internationalisation practices.

Martine Schophuizen, Aodhán Kelly, Caitlin Utama, Marcus Specht and Marco Kalz explore the factors enabling of educational innovation through complexity leadership. Leadership in higher education can influence the structurally embedding of educational technologies in higher education institutions. However, higher education institutions have to balance dynamic complex interactions while also setting out a clear vision and enacting this vision towards organizational goals. This paper analyses four qualitative case studies with a focus on the choices made by leaders in four Dutch universities that aim to contribute to organisational educational innovation. The data is investigated through the lens of complexity leadership theory in which three types of leadership play an important role: administra-tive leadership (i.e. top-down oriented), adaptive leadership (i.e. bottom-up oriented) and enabling leadership that emerges as a leadership type between administrative and adaptive leadership and contributes to governing innovation in complex environments. This study sheds light on how leaders made strategic choices and followed up on them to enable the innovative potential of the organisation and create synchronization between top-down and bottom-up efforts. The authors argue that if it is required that higher education is constantly adapted to an evolving knowledge-based society, a new leadership paradigm is needed.

Myroslava Hladchenko analyses the strategising of PhD supervision in Ukrainian higher education. She explores the implications of the national, organisational and individual cultural dimensions for the strategies of PhD supervisors. The intended outcome of PhD supervision is considered to be a doctoral graduate with advanced research skills as well as an original contribution to knowledge production. The study findings indicate that, firstly, institutional and cultural complexities, which refer to the lack of favourable conditions for doctoral supervision, hinder PhD supervisors from achieving the intended outcome. Publication requirements for a PhD also refer to the national cultural dimension. In the Ukrainian case, they constrain the supervisors in their choice of means and ends. Though international publications are compulsory for PhD candidates, there are no specific requirements for international journals which can incite PhD candidates to publish in low-quality journals exploiting an open-access model to obtain financial gains. Thus, in the Ukrainian case, publication requirements for a PhD embed means–ends decoupling as they restrict PhD candidates in their choice of journals and do not encourage them to publish in high-quality reputable and impactful peer-reviewed journals. Secondly, the strategic goals and adopted courses of action of PhD supervisors also depend on their values, beliefs, knowledge and skills. If they are unrelated to the intended outcomes of PhD supervision, PhD candidates are hindered from acquiring advanced research skills as well as making an original contribution to knowledge production.

The contributions to this special issue enrich our understanding of the challenges of strategic management in contemporary universities. At the same time they lay the ground for researchers to delve deeper into the problems associated to expanding areas of university strategic management. Equally they shed light on how the roles and responsibilities of the university leaders should be shaped to increase the effectiveness of strategic management.

Towards a renewed research agenda on strategic management in higher education

This special issue contributes to the body of knowledge on strategy in higher education in several ways. Firstly, the in-depth analyses provided in this special issue involve organisational and micro levels of analysis pointing to the dynamic nexus between institutional structures and processes and individual actors. Secondly, the diverse empirical cases of the issue involve different areas of application of strategic management in higher education institutions e.g. internationalisation, competition, sustainable quality management, educational innovations, strategic positioning of universities.

At the organisational level of analysis, the findings of the articles contribute to the body of knowledge on how universities as organisational actors develop their strategic actorhood (Meyer, 2010 ; Krücken & Meier, 2006 ), and respond to the institutional pressure through institutional diversity and homogeneity. The findings of Zipparo support prior studies highlighting that institutional complexity at the field level results in organisational complexity (Hinnings, 2011 ; Hladchenko et al., 2018 ). They also indicate that within universities there is likely significant complexity and internal diversity not reflected in institutional narratives. Institutional positioning is restricted in its capacity to describe – and exert influence upon – activity and behaviour within a university. Hasanefendic and Donina assert that strategizing emerges as a result of the interconnections between field and internal organizational dynamics and that organisational member practices must be unveiled as they strongly affect strategizing outcomes. Kettunen et al. highlight that competition creates organizational boundaries that hamper research collaboration and the spread of good practices, for example.

At the individual level of analysis, articles point to the importance of creating conditions that allow the involvement of individual actors e.g. middle managers, representatives of administrative and supportive departments, academics into the development and implementation of the strategies in university.

The ability of an individual to challenge institutional and organisational pressure as discussed by Hladchenko and Bulut-Sahin & Dogu, relates to either a very high or low social position within the organisation (Lawrence et al., 2011 ). The articles presented in the issue indicate that individuals in academia admit inconsistencies in institutional and organisational environments but lack agency and legitimised instruments to challenge these inconsistencies e.g. formal implementation of the strategies. These findings resonate with earlier studies highlighting how actors are more willing to implement changes included in strategies whose development they contributed to (Pratt & Corley, 2007 ). Hence the findings in the special issue support existing academic literature that stresses the necessity of empowering the deans and department heads to apply professional management approaches and play a crucial role in organisational strategy development (Stage & Kaare, 2019 ; Henkel, 2002 ; Middlehurst, 2004 ; Braun et al., 2015 ).

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Fumasoli, T., Hladchenko, M. Strategic management in higher education: conceptual insights, lessons learned, emerging challenges. Tert Educ Manag 29 , 331–339 (2023). https://doi.org/10.1007/s11233-024-09134-5

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• v.8(12); 2022 Dec

Student support in higher education: campus service utilization, impact, and challenges

Chithira johnson.

a Advisory, Student Experience Department, Qatar University, Doha, Qatar

Rizwan Gitay

b Senior Retention Specialist, Academic Advising Cente, Qatar University, Doha, Qatar

Abdel-Salam G. Abdel-Salam

c Associate Professor of Statistics and Head of Student Data Management-Vice President for Student Experience Department, Student Affairs Sector, VPSA Office, Qatar University, Doha, Qatar

Ahmed BenSaid

d Senior Data Analyst, Student Data Management-Student Experience Department, Student Affairs Sector, Qatar University, Doha, Qatar

Radwa Ismail

e Master Student of Applied Statistics and Graduate Assistant –Student Experience Department, Qatar University, Doha, Qatar

Rusol Adil Naji Al-Tameemi

f Student Experience Department, Qatar University, Doha, Qatar

Michael H. Romanowski

g Professor Educational Research Center College of Education Qatar University, Doha, Qatar

Batoul Mohamad Kazem Al Fakih

h Graduate Assistant, Student Experience Department, Qatar University, Doha, Qatar

Khalifa Al Hazaa

i Director of Student Experience Department, Vice President for Student Affairs Office, Qatar University, Doha, Qatar

Associated Data

The authors do not have permission to share data.

Worldwide, university student support services facilitate student performance, contribute to students' success, and increase students' chances of degree completion. Student support services programs' success depends on students' help-seeking behavior. This study explores the help-seeking behavior of Foundation Program and Undergraduate students at Qatar University (QU) through their use of campus services to better understand students' use of these services. The study examines the association between help-seeking behavior, as indicated through services, on student success and persistence in two consecutive semesters, Spring 2019 and Fall 2019. Findings report a significant association between students' services and student success and persistence. A significant difference was reported between at-risk students’ majors and at-risk students in STEM and non-STEM majors. Also, there was a difference in the help-seeking behavior among males and females, nationals and non-nationals, and student classifications.

Student support; Campus services; At-risk students; STEM.

1. Introduction

Worldwide, campus support services are available to students in educational institutes, national and international, to facilitate student performance ( Perez-Encinas and Ammigan, 2016 ), and contribute to students' success in their academic and career plans ( Lenz-Rashid, 2018 ). Similarly, Okpych et al. (2020) indicated that support services were established to increase the chances of students continuing in college and meeting their academic needs, ultimately leading to completing their studies and enriching the skills necessary for college success.

While institutions are extensively working on students' positive experiences and launching several student support services programs, the success of these programs depends mainly on the student's help-seeking behavior ( Okpych et al., 2020 ). Students need to know and understand what they are learning to avoid trouble, with which material to study, for how long, and when to seek help. Seeking help is associated with higher academic ability and positive teacher-student relationships ( Chu et al., 2018 ). From this perspective, it can be stated that students' help-seeking behavior is a substantial campus support service outcome. Saleh et al. (2017) have reported that about 90% of students experience problems in their academic lives, such as stress, future planning, anxiety, and depression. In contrast, only 15% of students reported seeking help from different sources. A possible reason for this low response can be attributed to a reluctance to seek help ( Dyrbye et al., 2015 ).

Similarly, Eisenberg et al. (2007) commented that lack of resources, cultural differences, social stigma, and hesitations are significant factors that hinder students from seeking help. In this matter, Finney et al. (2018) mentioned that educators need to explain the perceived benefits, such as learning, and costs, such as being labeled as scientifically backward, that come between the relationship between help-seeking behavior and achieving students' desire for success. According to Roussel et al. (2011) , the perceived benefits reflect the understanding that seeking help is a valuable strategy that promotes learning. On the contrary, the estimated costs reflect the threat to students' self-esteem caused by recognizing their need for assistance.

In Qatar, obtaining a higher education is integral to success, employment, and future opportunities ( Khan and Awan, 2017 ). Education is prominent in Qatar's National Vision 2030 and National Development Strategy and is essential to the transition to a knowledge economy. This is just one indicator of the national importance of the catalytic role of education. Since education could be a substantial predictor of innovation and economic productivity at times, higher educational institutions should support their students and provide campus services. According to Chao et al. (2018) , having a learning environment that assists students in identifying their problems and seeking help from on-campus support services enhances their motivation to study and promotes their academic performance.

There is a broad spectrum of services offered to students. For example, the university provides the following student services Academic Advising and Guidance (services to aid in students meeting their academic goals); Career Counseling and Exploration (counseling and professional development services to prepare students to compete for the best career opportunities); Student Counseling (services to students to overcome psychological, behavioral, social and emotional disorders and difficulties that may affect their performance); Writing and Language Support, Academic Support (i.e., peer tutoring, study skills workshops); and Inclusion and Accessibility support (See Qatar University Students Affairs, 2022 for additional information regarding student services at Qatar University). Most research on student services seems to focus on a single campus service and any association between usage, persistence, and retention. It is essential to understand how the use of on-campus services may influence students’ persistence and retention. However, from what we have experienced, this research area has not yet been sufficiently explored.

With that in mind, the purpose of this study is to address if students and students considered at-risk seek help by using any support services available on campus. More specifically, the research aims to explore if any associations exist between the usage of student services and these students’ success and persistence and if there are any differences in the help-seeking behavior as indicated by gender, nationality, major, and student classification.

Therefore, this study investigates the use, impact, and challenges of student support services in higher education. More specifically, the study aims to answer the following questions:

• 1a. To what extent do students seek help using the support services available on campus?
• 1b. To what extent do students identified as at-risk seek help by using the support services available on campus?
• 2a. Is there an association between the usage of campus services by all students and their success?
• 2b. Is there an association between the usage of campus services by students identified as at-risk and their success?
• 3a. Is there an association between the usage of campus services by all students and their persistence?
• 3b. Is there an association between the usage of campus services by students identified as at-risk and their persistence?
• 4a. Is there a difference in the help-seeking behavior of students in general, as indicated through the usage of campus services based on some students' demographic variables, namely, gender, nationality, major, and student classification?
• 4b. Is there a difference in the help-seeking behavior of students identified as at-risk, as indicated through the usage of campus services based on some students' demographic variables?

1.1. Context

The current research has been motivated by the gaps in our knowledge of existing patterns of service usage by students, lack of understanding around the help-seeking behavior of differing student cohorts, knowledge of the demographic factors that could influence help-seeking behavior, desire to ascertain the offering of right services to the right students in a timely and efficient manner and the need to validate the link between service utilization and student success.

1.2. Literature review

This section presents a brief but focused review of literature about high school students’ help-seeking behavior, how students can benefit by using support services on campus, and factors that impact support services' usage.

1.2.1. Students’ help-seeking behavior

According to Ochi et al. (2018) , help-seeking behavior is a person’s behavior toward pursuing and asking for help from others by speaking up about one’s problem. Disabato et al. (2018) defined help-seeking as acquiring help to resolve specific issues inside and outside the campus. Students' help-seeking behaviors refer to students requiring assistance in different matters, such as academic problems and stress. Saleh et al. (2017) found that very few students express their problems for support.

In addition, students show very reluctant help-seeking behavior, as they feel hesitant to ask for help. Disabato et al. (2018) postulated that the most significant barriers to college students’ help-seeking were trust in mental health professionals, embarrassment, poor mental health literacy, and an inclination to self-reliance. For instance, Dyrbye et al. (2015) found that 33.9% of students in several universities in the United States suffering from burnout come to ask for help from student services.

Research has demonstrated that most college students face challenges in seeking help with academic issues ( Chao et al., 2018 ; Karabenick and Knapp, 1988 ). In these cases, Newman (2000) points out that these difficulties can become barriers to obtaining the resources needed to solve the problem, often making modest efforts to resolve academic problems, stopping early, or becoming content with being unsuccessful.

Bornschlegl et al. (2020) report that since all higher educational institutions have different social setups and cultural norms, students’ attitudes toward help-seeking and the facilities available to gain this help vary immensely. Hence, educational institutes should tailor the academic support facilities to the attitudes and needs of their student base.

Seeking help is governed by several factors, both academic and non-academic ( Karabenick and Newman, 2013 ; Lotkowski et al., 2004 ). Students who seek help for their problems undergo improved adjustment experiences and face fewer emotional and behavioral adaptations ( Fallon and Bowles, 2001 ; Watson, 2005 ). This clarifies that the attitude held by an individual towards help-seeking behavior is the driver of the process of change ( McCarthy and Holliday, 2004 ). Therefore, students’ attitudes toward help-seeking are reliable indicators of the likeliness of seeking help available in their institutions if they face academic or non-academic issues.

1.2.2. How students benefit by using support services on campus

Research reports a positive association between students' usage of specific on-campus support services and their persistence within the academic institution. Student retention and sustainability can be affected by the ability to pay for college ( Butler, 2011 ; O'Keeffe, 2013 ). According to Duniway (2012) , a university’s financial aid is critical in ensuring that students continue and complete their degrees. The results indicated that students obtaining higher grants and scholarships were more likely to remain at and graduate from their first college. Ganem and Manasse (2011) report that scholarships are one of the strongest predictors of student persistence, progression, and timely graduation. Robbins et al. (2004) financial support played a statistically significant role in predicting college continuity.

It can be argued that on-campus student support services are the best option for students who feel uncomfortable discussing their issues at home. In addition to supporting the students emotionally, university services assist them with their academic problems, such as tutoring and recommending remedial courses ( Bettinger et al., 2013 ; Laskey and Hetzel, 2011 ). Chao et al. (2018) argue that students can achieve self-regulation and learning outcomes while seeking help to learn independent problem-solving and self-determination. Counselors in higher educational institutions provide many benefits to students, such as helping them prepare for academics and social challenges ( Abiola and Paul, 2019 ). Counselors can also motivate students and facilitate the process of career planning. Moreover, they can encourage students to discuss their problems openly with their parents or guardians ( Jackson, 2017 ).

Kuh et al. (2010) argue that students should have access to learner-centered support services to increase student persistence, such as peer tutoring and dedicated labs for writing and mathematics. Most academic services provide tutoring centers that offer academic support in speaking and writing ( Roberts and Styron, 2009 ). Research has demonstrated that academic services significantly impact student persistence ( Adelman, 1999 ; Pascarella and Terenzini, 2005 ). For example, Stewart et al. (2015) report that “support services such as tutoring, mentoring, counseling services, early intervention systems, and financial aid assistance will improve study participants’ academic deficiencies and increase persistence beyond the first year” (p. 12).

1.2.3. Factors that impact the usage of support services by students

Several factors affect a student’s help-seeking behavior, such as gender ( Magaard et al., 2017 ), ethnicity or nationality ( Disabato et al., 2018 ), academic performance ( Rafal et al., 2018 ), and student classification ( Clark, 2005 ).

1.3. Gender

Previous studies have reported that gender significantly influences individuals' help-seeking behavior and academic self-efficacy ( Baji, 2019 ; Drago et al., 2018 ). A number of studies have found that females possess more positive help-seeking attitudes than males and are more likely to recognize and accept needed services success ( Aoun et al., 2004 ; Bergeron et al., 2005 ; Xie and Xie, 2019 ). Therefore, they are more likely to exhibit help-seeking behavior when facing issues that can hamper their academic success. On the other hand, male students are doubtful to seek help from a professional or even from their social circle in case of any distress ( Sheu and Sedlacek, 2004 ). Xie and Xie (2019) found that gender roles moderated the association between academic help-seeking behavior and self-efficacy. They identified that females were less likely to adopt a maladaptive academic help-seeking behavior once they encountered academic difficulties.

1.4. Nationality

Disabato et al. (2018) discussed that in addition to gender, ethnicity, or nationality of the individual facing an issue or a mental health problem also impacts their help-seeking behaviors. Ethnic minorities in any region show less readiness to ask for help. In a US-based study, Asians and African Americans showed low rates of seeking professional help. They also had a negative attitude toward seeking help compared to European-Americans ( Gee et al., 2020 ; Wong et al., 2014 ). Researchers found that while ethnic groups do not show the likelihood of seeking help from professionals, they do seek help from informal sources, like religious leaders ( Brown et al., 2020 ; Cauce et al., 2002 ). However, this is regulated based on knowing a person who has used these resources. If seeking help is considered acceptable by society, individuals are more willing to seek help ( Disabato et al., 2018 ).

Kilinc and Granello (2003) indicated that US minority students favored seeking help from peers (50%) instead of traditional sources, such as psychologists (14%), counselors (11%), psychiatrists (8%), and academic advisers (2%). It is worth mentioning that “not seeking help from anyone” was also an option among those students, and 12% responded in this manner. In contrast, in Japan, Nguyen et al. (2019) found no statistically significant difference between minority and non-minority students in formal help-seeking behaviors.

1.5. Academic performance

Many studies have listed academic performance and success as an outcome of help-seeking behavior ( Rafal et al., 2018 ). However, in the context of this research, the authors propose that academic performance can also be a decisive factor in seeking help. If the student has previously witnessed success in their academic life but is experiencing problems and failures due to some inherent issues, they would need to seek help from a professional to understand how to resolve these issues and return to their prior academic success. However, students who have continued to experience academic problems will feel discouraged from visiting the help providers because they fear social rejection ( Karabenick, 2003 ). In addition, Wimer and Levant (2011) reported that college students with the highest and lowest scores tend not to seek help. In contrast, students with moderate scores (that is, the 'C+' range) reported the most help-seeking behavior, indicating that some students most in need of help were the least likely to seek help.

1.6. Student’s class

The attitude and behavior of the students towards seeking academic help and advising facilities vary with the years they have spent in the institution. According to Clark (2005) , the first and the last year are among the most critical years for advising. Junior and sophomore years highly impact overall student retention and degree completion. The transition that students undergo between high school and college can be a challenging experience for most first-year students as they may face some academic, social, and cultural challenges and may develop stress, depression, and maladaptive behaviors. These issues can lead to academic and non-academic failures. However, among other authors, Pace et al. (2018) identified that awareness about help facilities available, the stigma associated with help-seeking behavior, and peer support impact first-year students’ behavior and attitude towards help-seeking. In the second and third years, the support services focus on encouraging students to enroll in further courses to achieve degree completion ( Kot, 2014 ; Schwebel et al., 2012 ). In the final year, the academic advisors encourage completing courses and advising about the students' career opportunities. The issues of stress and depression may reoccur at this stage due to the feelings of anxiety associated with the unknown expectations that the business and career world will hold for them. At this stage of their collegiate careers, students use student advising and career counseling facilities ( Leao et al., 2011 ).

1.7. Major classification

Many students who complete high school lack preparedness for the expectations that college courses demand ( Moore et al., 2010 ). The number of students that join colleges underprepared has shown to be more among the science, engineering, mathematics, and technology (STEM) streams than arts or social sciences (non-STEM) ( Rodgers et al., 2014 ).

2. Research methods

Two consecutive semesters – Spring 2019 and Fall 2019, were used as the base semesters for this research. For this research, success is defined as the increase in a student's GPA at the end of the Spring 2019 and Fall 2019 semesters upon using campus services. Persistence is defined as students returning the following semester, Fall 2019 and Spring 2020. Finally, at-risk students are defined as students with a GPA of less than 2.00, especially those who were placed on probation and academic warning upon receiving a GPA below 2.00.

This research uses a data set provided by Qatar University’s institutional research department. Still, all information and forms required by Qatar University’s Institutional Review Board (QU-IRB) were submitted for the board’s review. Since the research involved collecting or studying existing data and the researchers’ inability to identify participants, QU-IRB provided an exemption (QU-IRB 1453-E/21).

2.1. Extraction of base data

First, the researchers extracted both semesters' active/registered students list from a standard student information system database. Only the relevant parameters of student ID, student name, gender, nationality, college, admitted term, nationality, major, GPA, and student classification were considered, thereby eliminating any other parameters irrelevant to the analysis or results of this study. As a final step in this process, the student IDs were matched against their at-risk status for the given semester, meaning students identified as at-risk per any of the pre-defined categories of academic underperformance by institutional policies.

2.2. Collection of data from service providers

To further collect data for analytical purposes, ten on-campus service providers were approached via email to provide the research team with the required data in line with University’s Institutional Review Board guidelines. These providers are highlighted in Table 1 . The ten on-campus support providers are categorized into two types: Institutional Support Services and College Support Services. The Institutional support services cater to all undergraduate students enrolled at Qatar University. While the College support services provide support to specific courses offered by the individual colleges and for the students enrolled in these courses. Representatives from these ten service providers were provided with the same base data from Spring (2019) and Fall 2019. The service providers were requested to provide information on which students from the base data used their services and the frequency of usage in a given semester.

Table 1

Service Providers and their objectives.

The frequency of visits was further consolidated into three actions: none, once, and twice or more. In addition, students were further classified as STEM and non-STEM based on students' major and concentration with the aid of Turner and Brass's (2014) report (Appendix A). Furthermore, the Success Oases, in particular, were requested to provide the list of courses for which they offered tutoring services or supplemental instruction in each of the two semesters. Only students registered in these courses were considered the sample for the success oases services.

2.3. Sample

The total number of active/registered students as an overall sample from Spring (2019) and Fall 2019 were 17,137 and 18,393, respectively. However, given the analytical requirements of this study, only students who had registered for courses belonging to the tutoring offered by the Success Oasis of a specific college were considered to generate the results of the success oasis particular to that college. However, for the other three centers being institutional services, i.e., the AAC, the CDC, and the SLSC, the data sets were analyzed in light of the frequency of utilizing the services throughout the semester as per the following parameters only: gender, at-risk status, and nationality, for the entire student population registered in the institution in a given semester.

2.4. Statistical analysis

Statistical analyses were performed using IBM SPSS Statistics. Since our objective is to define the characteristics of students who use the support services at Qatar University, simple yet effective statistical methods have been used to compare groups of students with different traits. We analyzed the categorical variables in the data set using a two-sample z-test to determine whether the two proportions of visits in each semester (Spring, 2019 and Fall, 2019) are equal. Two-sample Z-test is a generalization for the two-sample t-test when the sample is large, as is the case in this paper. Verma et al. (2019) mentioned that the two-sample t-test is an excellent method to measure the difference in proportions between two subsamples. Pearson Chi-square test for independence is used to assess the association between the independent variable (i.e., help-seeking behavior) and the dependent variable (i.e., success and persistence). According to Franke et al. (2012) and Mchugh (2013) , Pearson’s chi-square tests are one of the most used tests that measure the association and difference between two or more categories.

The Chi-square test is a non-parametric test. It does not assume that the data follow a specific distribution, which is one of its strengths. However, the chi-square test requires that the sample size be more than 30, which is the case in this paper. The Chi-square test of association ( χ 2 ) is used because the help-seeking behavior, success, and persistence are categorical (nominal and binary) variables. Agresti (2018) stated that the larger the value of χ 2 with a level of significance ( p < . 05 ) , more evidence exists toward association (i.e., against the null hypothesis H ° : i n d e p e n d e n c e ). Then, a Chi-Square test for homogeneity is used on every single demographic variable that can be split into two or more different groups. For example, gender can be divided into females and males. In this study, each student's demographic variable entered the homogeneity test to determine whether help-seeking behavior differed significantly among each group. A significance value of .05 indicates significance in the homogeneity analysis. Assumptions of the homogeneity test, (a) the demographic variable groups are sampled randomly and (b) the demographic variable is categorical, are checked before running the test.

3. Results from research

3.1. sample and service utilization description.

The service utilization study was motivated by the institution’s desire to understand students’ help-seeking behavior as indicated through their use of support services. The study also served as a measure to close the loop for at-risk interventions carried out by the academic advising services on campus-to gauge how many of the students who were referred to the various campus and university support services pro-actively availed of the services. The sample for the present investigation included a total of N = 15,650 and N = 14,615 undergraduate students for Spring 2019 and Fall 2019, respectively. It is worth mentioning that 1,487 students and 3,778 students were omitted from the dataset because they were newly admitted in either semester and did not possess a GPA score.

The support services are categorized into two types: Institutional Support Services and College Support Services, as evidenced by Table 1 above. The service utilization for the Success Oases in various colleges includes the active registered student population eligible to use services or course support in each individual college. In Spring (2019), 10,174 visits were recorded to AAC (65.0%), which also has the most frequent visits compared to other support providers. In the context of colleges’ Success Oasis, it is noteworthy that no data was provided for the investigation of CED Success Oasis because service utilization was not tracked during Spring 2019. About 22.0% of all eligible students to avail of the services provided by the CAS Success Oasis, based on the courses offered, utilized the services in Spring (2019), 15.7% of students used the Foundation support services, and 27.3% visited the CENG success oasis. However, only 3.6% of the eligible students visited the LAWC Success Oasis to avail help. In the Fall of 2019, a large majority (66.4%) visited AAC, while 18.9% visited SLSC. Percentages in Table 2 represent the utilization of other services in Fall (2019).

Table 2

Campus service providers with corresponding student visits.

The two-proportion Z-test was used to investigate whether the proportion of visits in the two semesters is comparable at a 5% significance level. The analysis confirmed a difference in the service utilization proportions in the two semesters for all the support service centers. In other words, there is a significant difference in students' behavior toward using support centers in Spring (2019) and Fall 2019.

Figures  1 and ​ and2 2 below compare the students' help-seeking behavior across the Institutional Support Service centers and the Success Oases within colleges for the overall sample and sub-sample of at-risk students. In Spring (2019), the use of AAC among the general sample (65.0%) and at-risk students (88.5%) was significantly higher than in other support service centers. Figure 2 reports similar findings during the Fall of 2019. However, student utilization of AAC services was slightly lower in Spring (2019) (65.0%) than in Fall (2019) (66.4%). In Spring (2019), findings indicated that the proportion of at-risk students who used CDC services once (9.9%) was considerably higher than those who used these services twice or more (0.4%). Most frequently, in Spring (2019), at-risk students used the services of SLSC twice or more (7.5%). Besides, a slightly higher proportion of at-risk students used SLSC services once (9.5%) in the Fall of 2019 compared to those who used SLSC services twice or more (7.7%).

Student characteristics (Spring 2019) – in percentages.

Student characteristics (Fall 2019) – in percentages.

Among the colleges’ Success Oasis, data was unavailable for the CEDU Success Oasis in Spring (2019), and the sample population in CSIS indicated the lowest compared with other colleges. For instance, only 105 students are included in the study sample for Spring 2019, where 25 are recognized as at-risk students. CENG recorded the highest student utilization in Spring (2019) (27.3%), while in Fall (2019), CBE had the highest record (28.1%). Similar findings are observed for at-risk students' utilization of CENG (21.1%) and CBE (29.6%). About 10.6% of the overall students used CAS Success Oasis services once in the Spring of 2019, and 11.4% used the services twice or more. A decline was observed in the usage of services in CAS, wherein in the Fall of 2019, only 4.9% used CAS support services once, and 3.6% used these services twice or more. The lowest service utilization among the at-risk students was observed in the services of LAWC Success Oasis in Spring (2019) (2.1%) and CAS Success Oasis during Fall 2019 (4.4%).

Overall, 35.0% of the sampled students reported not using the AAC in the Spring of 2019. While among the at-risk students, only 11.6% did not use the support services of AAC. However, in the Fall of 2019, the numbers were very close, where 33.6% of the sampled students did not use AAC compared to 11.3% of the at-risk students. On average, 72.6% of the overall sampled students in Spring (2019) have not utilized any support services offered by the six colleges' Success Oasis and Foundation Program. This average increased in the Fall of 2019 to reach 86.0%. Statistics for at-risk students indicated comparable results to the overall sampled students in both semesters.

In all, 11,666 is the total number of students who visited at least one support service center in Spring (2019). Similarly, 10,960 students were reported in the Fall of 2019. Most students who utilized the support services for the two semesters are females. Most students who gained support from the campus resources are nationals (67.9% in Spring, 2019 and 69.2% in Fall, 2019), and only 32.7% of non-national students reached these support centers. Students in Non-STEM disciplines outnumbered their STEM counterparts in the usage of the support services within the two semesters. Only 17.9% (18.1 %) of the students who got help at any of the support service centers in Spring (2019) (Fall, 2019) were at risk.

Since this study focuses on the service utilization by QU students, Figures  3 and ​ and4 4 provide parallel descriptive statistics between a sub-sample of students who used campus support services and another subsample of those who did not, for Spring 2019 and Fall 2019, respectively. This allows examination of the differences between the characteristics of help-seeking students and their counterparts. In most instances, students who seek help from the campus service centers are at-risk. As illustrated in Figure 3 , the proportion of at-risk students is higher among those using services than in the overall sample. As to student classification, the number of students in the foundation who used services and those who did not are similar to the general sample. The number of first year (28.2%) and sophomore (30.2%) students are found to be over-represented among those who used services compared to those who did not overall. Correspondingly, juniors and seniors tend to be under-represented among those using services. Following the research aim, the number of students in Spring (2019) who used the campus support services represented a higher percentage of success (57.3% increase in GPA) and persistence (82.5% registered for next semester) in comparison with the overall sample and those who did not use any service.

Usage of support services (Spring 2019) – in percentages.

Usage of support services (Fall 2019) – in percentages.

Likewise, the proportion of female students in Fall (2019) who used services is lower than that in the other two categories, while the proportion of male students who used the services is more than in the other categories, as shown in Figure 4 . This means that the proportion of females in the sample who used the support services is less than the proportion of males included in the sample who used the services. About 50% of the students who used the support services improved their GPA at the end of Fall (2019), and 91% registered for the next semester. This indicates a higher percentage of success and persistence among those using services than their counterparts.

3.2. Association measurements

As part of the analysis, it is interesting to determine the independent relationship between the students' help-seeking behavior and their success. This study will examine the relationships between the use of at-risk student services and student persistence and retention, based on factors such as gender, nationality, major, and student classification. This will enable universities to more effectively target their student support services to meet students' specific needs. The hypothesis to be tested:

• H 0 : There is no association between the students’ help — seeking behavior and their success.
• H a : There is an association between the students’ help — seeking behavior and their success.

A chi-squared test is undertaken for the data in Spring (2019) (see Table 3 ), and the results ( χ 2 = 70.4 , d f = 2 , p < . 05 ) show that the null hypothesis is to be rejected, which means that there is an association between the two variables, in other words, students who used the services in Spring (2019) were more successful. A similar test was made for the data in Fall (2019) ( χ 2 = 69.3 , d f = 2 , p < . 05 ) . The results indicate that the null hypothesis is rejected, which means there is a relation between the usage of the services and students’ success.

Table 3

Association measure between service utilization and success and persistence in Spring (2019) and Fall 2019.

Regarding the association between the utilization of campus support services and students' persistence among the overall sample in Spring (2019), Table 4 presents the cross-tabulation for the data linking the use of campus support services and the registration for the next semester during Spring 2019. Pearson Chi-square statistic ( χ 2 = 54.2 , d f = 2 , p < . 05 ) indicated a statistical association between the usage of support services and students’ persistence. One can also infer that given that students used the support services provided by the university, 82.5% of them will persist by registering for the next semester, as in Table 4 .

Table 4

Usage of Services∗Registered for next semester cross-tabulation (all students in Spring, 2019).

On the other hand, Pearson Chi-square statistic ( χ 2 = 40.2 , d f = 2 , p < . 05 ) indicated a correlation between the usage of support services and the persistence of the at-risk students in Spring (2019). From Table 5 , 77.2% of the at-risk students who used the support services in Spring (2019) will register for the next semester. Similar results were obtained in the Fall of 2019. However, the values of Chi-square are nearly double, providing more substantial evidence that a high association exists.

Table 5

Usage of Services∗Registered for next semester cross-tabulation (at-risk students in Spring, 2019).

3.3. The difference in help-seeking behavior

This research also investigated whether the help-seeking behavior differs among the categories of students' characteristic variables. The Chi-square test for homogeneity is conducted to determine the difference between the proportions of the two categories of gender, nationality, major classification, and academic standing on help-seeking behavior. The null and alternative hypotheses are stated as.

• H0: The Proportions of the two groups are equal.
• Ha: The Proportions of the two groups are different.

Some assumptions on the variable’s nature are required to run the correct Chi-square homogeneity test. Hence, help-seeking behavior is one dependent variable that identifies whether the student has visited any support service center at least once. It is measured at a dichotomous level, including two categories: “used services” and “did not use services”, however, since our interest is the in the behavior of students who used the services, the proportions used are for the students who acquired a specific characteristic and used the support service centers. Each of the former students' characteristics is an independent variable consisting of only two categories, whereas students’ classification includes five categories.

The Null Hypotheses to be tested are:

• H 0 : The proportions of males and females are the same
• H 0 : The proportions of nationals and non — nationals are the same,
• H 0 : The proportions of STEM and non — STEM are the same
• H 0 : The proportions of foundation, first year, sophomore, junior, and senior are the same

In Spring (2019), a statistically significant difference in proportions of 0.051 in the help-seeking behavior between males and females was found. Help-seeking behavior for males (78.6%) is statistically higher than for females (73.5%). Likewise, the null hypothesis is rejected for nationality because the help-seeking behavior of non-nationals (76.1%) is higher than nationals (73.8%), with a significance value of p = .003. For students’ majors, we failed to reject the null hypothesis for the primary classification, and the binomial proportions are not statistically different, with a significance value of p = .764. Students in STEM majors tend to have similar help-seeking behavior (74.7%) as non-STEM students (74.5%). In addition, students classified as foundation (85.9%) and first-year (82.7%) have higher help-seeking behavior than their counterparts. Hence, the Chi-square test for homogeneity indicated sufficient evidence of a significant difference between three of the five student classification categories.

A parallel analysis was conducted only for the students whose academic standing is identified as at-risk. Unlike the overall sample, the help-seeking behavior is not statistically different for the gender of students at risk, with a significance value of p = .07. Furthermore, the proportion of help-seeking behavior is comparable among the categories of at-risk students’ nationality ( p = .795) and primary classification ( p = .058) (see Table 6 ).

Proportion of services usage among students’ demographics (overall sample).

For both demographic variables. However, the Chi-square test for the help-seeking behavior among the five categories of at-risk student classification indicates a similar conclusion as the overall sample, with a significance value of p < .0001. Table 7 illustrates the proportions of at-risk students who used the support service centers concerning the different categories of students' demographic variables. For example, it can be said that 91.6% of the at-risk female students used support services in the Spring of 2019.

Proportion of services usage among students’ demographics (at-risk students).

The Chi-square test in Fall (2019) indicates comparable results to the previous semester (Spring, 2019) among the help-seeking behavior for all of the listed demographic variables. However, the test of two proportions reveals a significant difference in proportions of 0.029 for help-seeking behavior between STEM and non-STEM students whose academic standing is classified as at-risk, p = .033.

4. Discussion

This study examined how campus support services substantially influence students' help-seeking behavior. The results indicate that students are encouraged to use support services offered by success oases and institutional support centers (questions 1a & 1b). According to Julal (2013) , students are likely to stay in an educational institution with various support services available. Still, how individuals handle stress can avert some students from seeking help. Academics can use research that recognizes students who probably seek and use student support services so professors can help during their studies. Research can also be used to identify ways to improve access to and increase the use of support services. In this regard, these results indicate that in Spring (2019), AAC had the most frequent visits, and LAWC had the lowest. While in the Fall of 2019, AAC had the most visits, CSIS had the least. Zolezzi et al. (2017) explain that stigma is considered a common dilemma in mental health that creates hurdles for students in Qatar based on their gender and college type. More specifically, they found that stigmatizing attitudes held by most students included the belief that “people with mental illness cannot have regular jobs” (p. 1221). Therefore, it could be considered that moving toward institutional support services such as AAC is an outcome of a student's constructive behavior in seeking help.

Additionally, this study has found a significant association between service utilization and student success and persistence (questions 2a, b, and 3a, b). Students in general and at-risk students who utilized the support services were more likely to succeed and persist in their academic journey by returning to register for their next semester. In this regard, several prior research studies have confirmed that when students seek help from institutional services, it encourages them to be satisfied and exhibit higher performance ( Brown et al., 2020 ; Khoury, 2017 ; Seeto, 2016 ). Furthermore, Khoury (2017) has confirmed that colleges with student support services enable students to avail themselves of the opportunity to perform better academically. Similarly, Seeto (2016) also stated that universities' effective student support services predict persistence in students' academic performance. When students face challenges and adopt help-seeking behavior from an institutional source, they tend to demonstrate higher performance in the long run due to consistent mentoring by university programs ( Beisler and Medaille, 2016 ). The possible risks include lower awareness of academic courses, university projects, personal issues, and experiencing lower mental health to learn modules ( Brown et al., 2020 ). Such problems can be tackled by an effective student support services program in a university. Therefore, it can be considered that using services in help-seeking behavior while experiencing risk predicts students' success and persistence.

In both semesters, there is a difference in the help-seeking behavior among the overall students, males and females, nationals and non-nationals, and student classifications (questions 4a & 4b). In contrast, students in STEM and non-STEM majors show similar help-seeking behavior. These findings are identical to several prior research studies ( Al-Darmaki, 2011 ; Arthur, 2017 ; Rafal et al., 2018 ). Rafal et al. (2018) claimed that males expressed a higher need to demonstrate help-seeking compared to females. Arthur (2017) stated that international students are encouraged to seek help from institutional sources because of engagement, culture, and learning differences. Gansemer-Topf et al. (2017) claimed that students with STEM majors demonstrate higher help-seeking behavior than non-STEM students. This may imply that students require an appropriate level of awareness, then such demographic variables have a lower tendency to influence their help-seeking behavior ( Sontag-Padilla et al., 2018 ). From this perspective, it can be considered that students with help-seeking behavior, based on these demographic variables, have higher student support services awareness than others.

Furthermore, results have indicated a significant difference between the at-risk student classification categories in Spring (2019). A difference in the help-seeking behavior between the at-risk student classification categories and the at-risk students in STEM and non-STEM majors in the Fall of 2019 was also found. In comparison, there is no difference in the help-seeking behavior among the demographic variables of the at-risk students other than the ones mentioned above. Gansemer-Topf et al. (2017) also claimed significant differences in students' persistence based on their affiliation with STEM and non-STEM. It is possible because students with STEM majors experience constructive issues that require complete support services ( Sellami et al., 2017 ; Sithole et al., 2017 ).

Similarly, this study did not find any differences in gender and nationality toward help-seeking behavior in the two semesters. Students with sufficient awareness of support services can demonstrate help-seeking behavior regardless of the time ( Sontag-Padilla et al., 2018 ). From this perspective, it can be considered that students demonstrated help-seeking behavior based on their awareness of the student’s support services.

5. Conclusion

Our key findings from this study indicated that students were encouraged to use support services. In both semesters, the Academic Advising Center had the most frequent visits. In the spring, the College of Law had the lowest number of visits, while in the fall, the College of Sharia and Islamic Studies was the lowest number of visits. Additionally, there was a significant association between service utilization and student success and persistence, students in general and at-risk students who utilized the support services were more likely to succeed and persist in their academic journey by returning to register for their next semester. Furthermore, Differences appeared between students, males and females, nationals and non-nationals, and student classifications in self-seeking behavior. At the same time, STEM and non-STEM majors show similar help-seeking behavior. There is no difference in the help-seeking behavior among the demographic variables of the at-risk students other than the ones mentioned above. Finally, there were no differences in gender and nationality toward help-seeking in the two semesters.

5.1. Limitations and further research

The goal of on-campus service delivery is to ensure students have the proper support for the right problem at the right time, so they can successfully progress in their academic journey. Thus, the findings in the current study have the potential to have implications for policymakers, service planners, and strategic planning of institutional resources and budgets.

Future research should focus on expanding efforts to explore service utilization at different types of universities in Qatar, as the services offered to vary significantly by the institution and needs of the student population it hosts. There is a deficit in research pertaining to student services and affairs in the MENA region, and similar studies published would help understand the type of services that are more utilized and efficient among students in the Arab world. This could guide institutions to benchmark their efforts and ‘tailor-make’ their services to cater to their student population's unique needs and demographics.

In addition, students should investigate the issues surrounding why they do not seek services and ensure that preventable barriers, such as stigma about seeking help, lack of necessary services, and laissez-faire policies, are not the cause.

Finally, additional studies could examine and research the service utilization among pocket populations in university campuses among non-national students, international students, students with special needs, working students, non-traditional mature students, etc. Several studies have considered these aspects in a broad sense ( Kerr et al., 2013 ; Miranda et al., 2015 ). Few studies examined the relationship between the specific issues and services utilized. For example, Miranda et al. (2015) reported that racial minorities reported having more hurdles and challenges accessing on-campus counseling services for mental health issues than white students. Combining this knowledge with current research results, one of the future directions is to look at demographic characteristics as an intermediary in the relationship between students' risky academic status and on-campus service use. Such information may provide strong evidence for more comprehensive coordination of on-campus services and awareness.

In this study, data collection was challenging, as it required continuous tracking of the service utilization by students manually from multiple support providers throughout the semester. The research process could inform policymakers of the need to automate monitoring of student service utilization and inform them of services most in need of such tracking to plan their projects. Due to privacy concerns, essential student support services were not considered in the study (e.g., student counseling and unique need support services). Future efforts need to include these student populations without violating student confidentiality. The current research focuses mainly on undergraduate students. Future work may consider service utilization for graduate students. The data collected that was available with support providers were basic; hence, for this study, minimal statistical analysis techniques were deployed. A future study could expand on this by obtaining more information about the students to deploy expanded analytical techniques. Despite gaps in knowledge about using services on campus, current results can help with planning at similar universities. Our results suggest that certain services have higher student usage than others, and it is worth exploring the factors that mitigate this trend.

Declarations

Author contribution statement.

Chithira Johnson; Abdel-Salam G. Abdel-Salam; Radwa Ismail: Conceived and designed the experiments; Analyzed and interpreted the data; Wrote the paper.

Rizwan Gitay; Rusol Adil Naji Al-Tameemi: Performed the experiments; Analyzed and interpreted the data.

Ahmed BenSaid: Analyzed and interpreted the data.

Michael H. Romanowski; Batoul Mohamad Kazem Al Fakih: Analyzed and interpreted the data; Wrote the paper.

Khalifa A. Haza: Conceived and designed the experiments; Wrote the paper.

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability statement

Declaration of interest’s statement.

The authors declare no competing interests.

Additional information

No additional information is available for this paper.

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Student visa: Views of students and higher education institutions

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Published 14 May 2024

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1. Introduction

1.1 background.

Since leaving the EU, the UK government has maintained a highly competitive offer for international students who want to study in the UK via the Sponsored Study visa route. At present, under the Future Borders and Immigration System ( FBIS ), there continues to be no limit on the number of international students who can undertake sponsored study in the UK.

In 2023, there were 457,673 sponsored study visas granted to main applicants, 5% fewer than in 2022 but 70% higher than 2019. The Sponsored Study visa route plays a crucial part in the UK government’s plan for growth, and ministers are keen to build an evidence base on route delivery to inform future policy and underpin assessments of economic impact.

1.2 Student visas

The Sponsored Study visa route is open to international students who are aged 16 and over, have been offered a place on a course by a licensed Student sponsor, have enough money to support themselves and pay for their course, can speak, read, write, and understand English and, if 16 or 17, have consent from their parents.

The length of time successful applicants can stay depends on the length of their course and what study they have already completed in the UK. If they are aged 18 and over and the course is at degree level, they can usually stay up to 5 years. If it is below degree level, they can usually stay up to 2 years.

To sponsor international students, higher education institutions ( HEIs ) must hold an active and unsanctioned licence. There are routine duties which must be fulfilled by the sponsoring institution to maintain a valid sponsorship licence – these and other immigration compliance requirements are set out in the UK Visas and Immigration (UKVI) Student sponsor guidance.

1.3 Research aims

The aim of this research was to understand international student and sponsor decision-making when using the Sponsored Study visa route. The outputs of the research will be used to aid understanding of trends appearing in management information ( MI ) data, and to help inform the focus and design of future evidence gathering and evaluation plans.

Specifically, the research aims were:

• to understand why international students chose to study in the UK, awareness of policy restrictions, the relative attractiveness of policy features and how these compare to international offerings, and the relative importance of other drivers outside the sphere to policy influence
• to gather details on post-study work intentions and reflections on the Sponsored Study visa route interacting with other visa routes (for example, Skilled Worker, Graduate) as means of retaining international talent and pathway for high-skilled migrants to work and settle in the UK
• to learn from user experiences and identify areas for improvement in operational delivery, including experiences of the fully digital application process
• to provide insight on HEIs ’ understanding of sponsorship requirements, how sponsors comply, any external support needed to overcome barriers and burdens, and the impact of sponsorship policy on international student recruitment efforts; the research aimed to address what influences actions taken by sponsors when recruiting domestically and internationally and whether this varied by different faculties

The key research questions were:

• what factors motivate international student decisions to undertake higher education study in the UK (compared to other countries); to what extent are they influenced by policy features (for example, ability to bring dependants); how did they learn about the route
• has the launch of the Graduate route influenced study intentions; what are their intentions for after their course ends
• what labour market activities are the dependants of visa holders undertaking in the UK
• how have students and sponsors found the application/sponsorship process; how have students found their experience of studying in the UK
• how have changes to the Sponsored Study visa route impacted wider HEI strategy around international recruitment
• what are HEI sponsors doing to achieve their international recruitment objectives; how is this working in practice

1.4 Methodology

The research was split into 2 strands, one focusing on the views and experiences of the Student visa holders, the other focusing on the views and experiences of higher education institutions. This involved an online survey with over 2,000 Student visa holders and 25 follow-up qualitative interviews, and a telephone survey of 115 institutions and follow-up qualitative interviews with 20 institutions.

On the Student visa holders strand, 2,415 current Student visa holders completed the survey out of the 40,000 invited. The sample of students invited was selected to match the overall population profile of Student visa holders by nationality, age, and gender. The number of completed surveys by each of those categories is presented in table 1 below. The completed surveys were then weighted on an age by nationality basis back to the main population profile.

Table 1: Profile of students who completed the visa holders survey

For the qualitative strand, 25 interviews were completed, aiming for a spread of profiles and experiences, by nationality (at least 3 to 6 interviews with students from India, Nigeria, and China), dependants (14 had dependants), level of qualification (5 undergraduate students, 15 master’s students, 5 doctoral), working practices (18 worked while studying), experience of applying (17 positive, 8 negative), and future plans (18 plan to stay).

For the HEI strand, a census approach was adopted. computer assisted telephone interviews were completed with 115 HEIs , out of a total sample of 172 institutions. Each institution had up to 4 named contacts, and all were considered in scope for the survey. No weighting was applied.

Table 2: Profile of institutions who completed the HEI survey

For the qualitative strand, 20 follow-up interviews were conducted with a range of institutions from across the UK (9 from London and the South, 11 from the rest of UK). The cohort included responses from a range of institutions with varying percentages of international students (6 each of high, medium and low, and 2 unknown), and respondents included some HEIs who wanted to increase their international students intake (3 HEIs ), and some who used third-party services (6 HEIs ).

More information on the methodology for both strands of the research can be found in Appendix 1: Methodology .

2. Prior awareness of visa routes

This chapter explores the ways students reported first hearing about the Student visa as well as examining their awareness of other visa routes, namely the Graduate route.

2.1 How did students first hear about the Student visa?

When asked about where they first heard about the Student visa, students indicated that they were most likely to have heard about it from friends or family members (23%). This was closely followed by education agents (22%) and places of study in their home country (19%)(figure 1).

Figure 1: How visa holders first heard about the UK Student visa

• Base: Visa holders survey, All visa holders (2,415).
• Percentages <1% are not included in this chart.

Differences by nationality

There were some differences by nationality in how the students first heard about the Student visa. Nigerian students were the most likely out of all nationalities to have heard about the visa from friends and family (42%), whilst Chinese students were the least likely (12%) to have done so. Chinese students were the most likely out of all nationalities to have found out about the visa from a place of study in their home country (33%). Pakistani students were more likely than average to have reported hearing about the visa from social media or an employer or work colleague (15% and 5% compared to 8% and 1% respectively).

Differences by subject and level of study

There were further differences depending on the subject studied and the level of study. Those who were studying a science, technology, engineering and mathematics ( STEM ) subject were more likely to have heard about the visa from friends or family than those studying a non- STEM subject (25% compared to 22%). In contrast, those who were studying a non- STEM subject were more likely to have heard about the visa from an education agent (23% compared to 20% among those studying a STEM subject) or from a place of study in the UK (10% compared to 7%). Undergraduates were most likely to have first heard about the visa from a place of study in their home country (28%). Master’s students were more likely to have heard from friends or a family member (25%) and doctoral students were more likely to have heard from a place of study in the UK (25%).

Differences by age and dependants on Student visa

The age of the student also seemed to determine how they first heard about the Student visa. For example, older students, aged 25 and over (27%) were more likely to have heard about the visa through friends or family compared to younger students aged 16 to 24 (19%). In contrast, younger students were more likely than average to have heard about the visa through an education agent or a place of study in their home country (both 24%).

Those with dependants were more likely than those with no dependants to have heard about the visa from a friend or family members (32% compared to 22%), from the UK government website (19% compared to 14%), from social media (14% compared to 7%), as well as from colleagues or peers (4% compared to 2%). In comparison, those with no dependants were more likely than those who had dependants on their visa to have heard about the visa from an education agent (24% compared to 13%), a place of study in their home country (17% compared to 11%) and a place of study in the UK (9% compared to 4%).

Several students who participated in the qualitative interviews found out about the Student visa through official websites, such as the GOV.UK website, the Home Office website and the UK Visas and Immigration (UKVI) website. This was driven mainly by students studying non- STEM subjects, those on master’s courses and those with dependants on their Student visa. This predisposition towards official sources among the qualitative interviews could be explained by the slight “self-selection” of the kind of audience who would be confident enough to take part in qualitative interviews.

“I was just searching on Google and then I found out that the UK actually has a UK government website with all the information.” – Student visa holder, India, master’s, no dependants.

“[I] just checked the information that’s available on the Home Office website, like the conditions, and of course the information that they provide when they grant a visa.” – Student visa holder, France, doctorate, has dependants.

Interviewees also reported that they found out through friends and family as well as from universities in the UK, mostly on their website. It was often the case that the friends and family were themselves students in the UK and had Student visas themselves, which indicates that they would be in a good position to offer advice or share knowledge about the Student visa. Some of the students who had first heard about the Student visa through universities in the UK had come across this information whilst proactively searching courses and university requirements. For others, they had been informed about the Student visa through acceptance letters that they had received from the universities.

“Once your application to the university is approved, they start to send you emails about how to apply for the visa.” – Student visa holder, USA, doctorate, has dependants.

2.2 Awareness of other routes

Most students (70%) were aware of the Graduate route before the survey had taken place. Just over two-in-five (22%) students were not aware of the Graduate route and only 8% said that they did not know if they were aware of it.

Figure 2: Awareness of Graduate route

Certain nationalities were more aware of the Graduate route. Pakistani (80%), Nigerian (78%) and Indian (78%) students were more likely to have been aware of the Graduate route than Chinese students (63%). Furthermore, students who had ‘other’ nationalities, not including Pakistani, Nigerian, Indian and Chinese students, were more likely to be unaware of the Graduate route (31% compared to 22% overall).

Those studying on a postgraduate course, both master’s and doctorates (76% and 70%), were more likely to be aware of the Graduate route compared to undergraduates (54%). This finding may have been influenced in part by the higher proportion of postgraduate students being from Pakistan, India, and Nigeria who, as mentioned before, had more awareness of the Graduate route. Furthermore, those who were studying at Russell Group universities were more likely to be unaware of the Graduate route compared to those who were studying at non-Russell Group universities (27% compared to 20%). This may have been driven by the high proportion of Chinese students studying at Russell Group universities.

Students who may have been more likely to benefit from the Graduate route were more aware of its existence. For example, those who had the intention to remain in the UK post-study were more likely to be aware of the Graduate route than those who wanted to leave the UK post-study or did not know what they wanted to do after their study (76% compared to 56% and 62% respectively). Those who had worked whilst studying were more likely to be aware of the Graduate route compared to those who didn’t (82% compared to 67%). Additionally, those who had dependants on their Student visa were more likely to have been aware of the Graduate route than those with no dependants on their Student visa (80% compared to 74%).

Younger students were less likely to be aware of the Graduate route. Over three-quarters (78%) of students aged 25 and over were aware of the Graduate route compared to 62% of students aged between 16 to 24. This may be influenced in part by the high proportion of Chinese students aged between 16 to 24 (70%) who were less likely to have been aware of the Graduate route.

3. Decision-making

This chapter explores the reasons and decision-making process of Student visa holders when choosing to come study in the UK, including the influence of other countries, visa routes, and other influences. The chapter then considers how HEIs prioritise how many Student visas to sponsor and why, discusses the recruitment practices and goals of sponsor HEIs , and investigates the impact of the recent policy changes on their practices.

3.1 Reasons for studying in the UK

The majority of Student visa holders said their reason for coming to study in the UK under the Student visa was because they wanted to pursue a particular course at a particular university (60%). A further third said that studying at their chosen university and wanting to live in the UK were both equally important (33%). Only 4% of international students said their main motivation was primarily wanting to live in the UK.

Table 3: Main drivers for decision to come study in the UK, overall and by nationality

• Base: Visa holders survey, All respondents; Total (2,415), India (519), China (507), Nigeria (431), Pakistan (155), Other (803).

Students from China were more likely to say they wanted to pursue a particular course at a specific university (74%). Students were also more likely to say a particular course or university was what drove their decision if they were studying for a PhD (80%), planned to leave the UK after their studies (75%), studying at a Russell Group university (69%), or had no dependants (62%).

On the other hand, students from Nigeria and Pakistan were more likely than average to say that both living and studying in the UK were equally important for them (42% and 41% respectively). A similar pattern was found among students who worked while studying (45%), students with dependants (38%), and those with 3 or more dependants (43%).

Reasons for choosing the Student visa over other UK visa routes

Students who wanted to live in the UK and those who thought living in the UK was equally as important as pursuing a course at a particular university were asked their reasons for choosing a Student visa over other UK visas. Access to the Graduate route, the ease of the application and the ability to bring dependants were influences on students’ decision to get a Student visa rather than a different UK visa. Among this group, the main reason for choosing the Student visa was the fact that they primarily wanted to study in the UK, rather than work (57%). In addition, more than a third (37%) said they chose the Student visa because it led to the Graduate route, about one-in-six (16%) chose it because it was an easier application process compared to other UK visas, and one-in-ten (10%) chose it because it allowed them to bring dependants. A full list of the reasons for choosing the Student visa over other UK visas is in figure 3 below.

During the qualitative interviews, most students indicated that their decisions were mostly driven by the fact they wanted to do a bachelor’s degree, master’s or doctorate (as applicable), and it was just a matter of deciding where to do it.

“Wanting to study a master’s was my priority one and then came studying in the UK and then finally the university.” – Student visa holder, India, master’s, no dependants.

Figure 3: Reasons for choosing the Student visa over other UK visa options

• Base: Visa holders survey, All respondents who wanted to live in the UK and those who thought it was equally as important as pursuing a course at a particular university (1,004).
• Percentages under 5% are not shown above.

Among those who said they wanted to primarily pursue a certain course at a particular university, the majority chose their current option because it fitted their academic interests (74%) and because the course would enable them to develop the right professional or technical skills (73%). In addition, almost half (47%) said it was the reputation of the UK higher education institution that attracted them.

The reputation of the UK institutions seemed to be an attraction particularly among students from China (56%), who indicated in the qualitative interviews that they sought the good reputation of UK universities and relative accessibility of acceptance compared to the high competition for good universities in China.

“So I come from China, and it is so competitive if I want to go to a very high reputation university but in the UK it is not that hard to get an offer from a university, and the second reason that I came here is that I am really interested in the culture and the history, so I choose to come here.” – Student visa holder, China, undergraduate, no dependants.

The UK’s reputation for higher education also extended beyond China, with students from India and the USA also noting the UK’s academic reputation.

“I really like the intellectual community at the University of [redacted]…The reputation of the university itself.” – Student visa holder, USA, doctorate, has dependants.

“My choice of destination was always the UK because I know the top Universities are always in the UK.” – Student visa holder, India, master’s, no dependants.

Additionally, some students from Nigeria and India mentioned that they preferred the UK’s practical and applied learning system, compared to the very theory and book-based approach in their countries.

“In India a lot of the studying comes from the book but not practical. When it came to [studying] other countries it had practical as well as theoretical so I chose something that gave me hands on practice.” – Student visa holder, India, master’s, has dependants.

3.2 Impact of alternative options on students

Half of the Student visa holders (50%) also considered other countries before applying to come to the UK, as shown in figure 4. While two-fifths (41%) considered other countries as study destinations, 12% considered other countries for non-study related reasons. Students from India and Pakistan were the least likely to consider going to other countries (31% and 36% respectively).

Figure 4: Proportion of Student visa holders that considered other destinations, overall and by nationality

The countries most mentioned were firstly other English-speaking countries like the USA (by 51% of those who said they were considering other countries alongside the UK), Canada (42%), Australia (34%), followed by Germany (19%), France (13%) and Japan (10%).

The USA and Canada were more likely to be considered by Nigerian students, 60% of whom considered the USA, and 79% considered Canada. Canada was the main alternative destination considered by those with dependants (70%).

Students from Pakistan were more likely than average to consider Australia (50%) and Germany (32%). Students from China were also more likely than average to consider Australia (40%) and were the most likely to consider France (19%) and Japan (19%).

In line with the survey, most of the students in the qualitative interviews mentioned they had considered either Canada or USA, or both, due to the international recognition of their degrees and accreditations, and opportunities after graduation (the same reasons as for the UK).

“I considered Canada and the US but after weighing up the pros and cons I decided on apply to a UK university because the visa process was simpler, and the documentation required. I had just got married too so I liked that I could bring my wife with me while studying.” – Student visa holder, Nigeria, master’s, has dependants.

“I was also looking at other countries that have master’s programmes, like Canada, because they are internationally recognised and allow board placement.” – Student visa holder, India, undergraduate, no dependants.

Reasons for choosing the UK in the end

The reasons for choosing the UK over the other countries in the end, as represented in figure 5, included the UK course or institution being better (67%), because they wanted to experience living in the UK (42%), or because they wanted to move to an English-speaking country (28%). Almost a quarter (23%) mentioned that the UK Student visa was a better fit for them, rising to 41% of students from Pakistan, to 46% among those aged between 35 and 44 and to 36% among those with dependants.

Figure 5: Reasons for choosing the UK over other countries

• Base: Visa holders survey, Respondents who considered moving to a country other than the UK (1,192).

For some students, the deciding factor in choosing the UK seemed to be the ease of application and the speed of the processing of the UK Student visa compared to those of USA and Canada. Many people said they were put off by the USA visa needing an in-person interview which was difficult to set up due to high demand, and by the cost of it. In contrast, the process for applying for a Canadian Student visa was all online and straightforward, but the processing times were very long.

“Looking at both the Canadian and the UK visa thing for students, I found the UK process to be a little more laid back and convenient for me, especially since I was married by then.” – Student visa holder, India, master’s, has dependants.

“I applied to 5 universities in the UK through UCAS, and Canada as well. I was supposed to go to Canada, applied for the visa and all, but Canadian visa got very delayed due to COVID-19, so I decided to accept the [UK university] option just in case.” – Student visa holder, India, undergraduate, no dependants.

In one instance, a student who was accepted by a Canadian and a UK university was forced to accept the offer from the UK university, despite the Canadian university being their first choice. This was because COVID-19 caused delays to the processing of their Canadian visa, meaning they would arrive in Canada after the course had already started. The UK student visa provided them the option to pay to expedite this process, allowing them to start their course on time.

Influence of dependants on decision-making

Ability to bring dependants was important. Not many of those with dependants mentioned it was a driving factor in their decision, but most mentioned how important it was that they were able to bring them too.

“What attracted me the most was the ability to bring my wife with me and the ability to work after my studies… And to get sponsored so I could continue my career.” – Student visa holder, Nigeria, master’s, has dependants.

“If I’d not been able to bring my kids, I would not have considered coming at all, I would not have given it a second thought.” – Student visa holder, USA, doctorate, has dependants.

“It’s important because my course is 3 years. Having my husband with me in the UK is making the whole thing a little bit easier, it’s making the whole journey easier… We are able to support each other. But it was not a criteria for me coming to the UK. What I prioritised was getting the admission to [University] I still would’ve struggled on with it.” – Student visa holder, Nigeria, doctorate, has dependants.

For those who had children as their dependants, they tended to consider the quality of the UK education system for their children and that played an important role in their decision as well.

“I didn’t want my children to have a Korean education because Korean education is very tough and high cost…and I really like them to have physical education too.” – Student visa holder, South Korea, Post-graduate, has dependants.

Influence of the Graduate route

The Graduate route was also a consideration for Student visa holders. As previously mentioned, most students were aware of the Graduate route (70%), and over six-in-ten (62%) had been aware of the route from before applying to the UK Student visa. Of those aware of the Graduate route when applying, as depicted in figure 6, 85% of them said that its availability influenced them to apply for a UK Student visa at least to some extent, and just over a third (35%) said it influenced them to a great extent. Students from Nigeria and Pakistan were more likely to have been influenced by the Graduate route to a great extent (46% each).

Figure 6: Influence of the Graduate route on decision to apply for UK Student visa

• Base: Visa holders survey, All those who were aware of the Graduate visa route when applying (1,059).

However, only a third (34%) of those who said they were influenced by the Graduate route would have changed their destination if it had not been available, while almost half (46%) said they would have still made the same choice, and 20% were unsure what they would have done otherwise. Students from Nigeria were more likely to choose a different country if the Graduate route had not been an option (44%).

Having the Graduate route available provided some peace of mind for international students, that if they wanted to, they could try to find a job in the UK after their studies and they would have the time to look for it.

“It felt hopeful when I was back in my home country that ‘Ok, we still have some time to, you know, find a job and get the experience that I was looking for’ because studying here is an experience that I can get and working is again, another experience that I can have on my resume.” – Student visa holder, India, master’s, has dependants.

“I decided on the MBA because I can get the one-year visa plus 2 years extended visa for working… It was a huge impact on my decision.” – Student visa holder, South Korea, master’s, has dependants.

The length of the course and the UK culture were also common themes in the qualitative research.

“There was very much an experience component of if I’m going to be spending this much money on a master’s degree, how could I make it part of my life experience?” –Student visa holder, Australia, master’s, has dependants.

The fact that UK master’s programmes are 1-year and bachelor’s are 3 years, when in most other countries they are 2 and 4 years long respectively, was seen as a plus, particularly among students returning to education after working full-time. A few students also mentioned wanting to “get away from” the political situation and corruption in their country of origin, and one student mentioned they were attracted by the rule of law in the UK.

Case study 1 - Decision-making

One master’s student interviewed was a 34 year old man from Nigeria, studying sociology, a non- STEM subject in the UK. He had a teaching qualification from Nigeria and had previously worked in Nigeria and the UAE, but he wanted to further his education. He felt that the Nigerian higher education system relied too heavily on textbooks, while he wanted to get a more practical experience out of his master’s. He felt this practical experience would improve his future employment prospects in the education sector.

He was made aware of the opportunity to study in the UK via the Student visa by a friend while he was working in the UAE. He was also considering Canada and the USA. After some internet research on different criteria and application processes for universities as well as visas, he decided on the UK.

This was influenced by the simplicity of the visa process and the documentation required, as well as the fact that he could bring his wife with him as a dependant, as he had just got married. For other visas and university applications he noted the need to use a consultant to be able to navigate the process, which he saw as being prone to fraud and unnecessarily expensive.

“What attracted me the most was the ability to bring my wife with me and the ability to work after my studies…And to get sponsored so I could continue my career”.

He also highlighted the rule of law, and lack of corruption as being very important considerations in his decision-making process for a study destination, as corruption was something he had experienced both in his home country and while working in the UAE.

He was quite happy that his lived experience of the course matched his expectations, and he enjoyed the ability to put into practice what he was learning about. He was working while studying, during weekends, in a hotel in a neighbouring city. After finishing his studies, he was hoping to build a career here in the UK by undertaking a teaching qualification and furthering his teaching practice, though he was originally planning on going back to Nigeria.

“It’s easier to get a job here in the UK than it is in Nigeria.”

Student visa holder, Nigeria, master’s, non- STEM , has dependants.

3.3 Impact of the ability to change to different visa routes on students

In the qualitative interviews no one mentioned the Student visa as one of the main attractions for coming to the UK. A lot of students said they did not consider the visa until after they chose their destinations for study. But, as previously mentioned, some did cite the ease of the visa application process (compared to Student visas in other countries) to be a plus, and sometimes a deciding factor in which country to go to.

Figure 7: Level of agreement with statement: ‘As a Student visa holder, it is important that I am able to switch to another visa (for example, Skilled Worker) before completing my studies

• Base: Visa holders survey, All those who are not PhD students (2,338).

Although no longer allowed, but a possibility at the time of application for the students interviewed, students studying at below doctoral level were asked whether it was important for them to be able to switch to another visa (for example, Skilled Worker) before completing their studies. Just under a third (31%) agreed with that statement, while 29% disagreed, 26% neither agreed nor disagreed, and a further 15% were unsure of their answer.

Figure 8: Whether people would still have applied for a UK Student visa if early switching was not an option

• Base: Visa holders survey, All those who agreed the early-switching option was important (741).

However, if the early-switching option was not available at the time of their application, three-quarters (74%) of the people who agreed that having that option was important to them would have still applied for a UK Student visa. Students from Nigeria were more likely to say they would have still applied for the Student visa without the early-switching option (84%).

From the HEIs ’ perspective, two-thirds (67%) said that it was rare for students to change visas before the end of their studies, 13% said not notably rare nor common. Only 13% of HEIs said it was common. The final 7% did not know.

3.4 Reasons for HEIs recruiting via the Student visa route

Most (93%) HEIs reported that they actively recruit international students. All Russell Group universities surveyed reported that they did this, as did 92% of non-Russell Group Universities.

Figure 9: Factors leading HEIs to sponsor international students on the Student visa route

• Base: HEI survey, All HEI respondents (115).

The most common reason for becoming a sponsor for international students was to increase cultural diversity. This factor was reported by 64% of HEIs . Universities in the North (78%) and Scotland (77%) were more likely to be recruiting to increase their cultural diversity than the rest of the UK.

“We’ve got the corporate reasonings, which is established in to diversify recruitment significantly. There’s obviously finite reasonings as well, but a lot of it is around diversifying our recruitment portfolio.” – HEI, East of England, non-Russell Group.

Almost half (47%) of HEIs stated that they were motivated to sponsor international students for financial reasons. In the qualitative interviews some reported that this worked alongside increasing cultural diversity.

“If we didn’t [sponsor], we wouldn’t be able to recruit students and that’ll have a massive impact on both the diversity of the student population but also, the university is a business.” - HEI, South East, non-Russell Group.

There was also a sense in the qualitative interviews that sponsoring international students was something that the HEI had always done, and the strategy continued to be an integral part of the institution. This was reported by 12% of HEIs in the survey.

One-in-ten (10%) of HEIs reported that they wanted to build global long-term connections with other countries and 10% also stated that they recruited as part of international partnerships with institutions. These 2 motivations were also referred to in the qualitative interviews, particularly those with specific research interests.

“We’ve always had very sound international relationships with universities overseas, so this is just a continuation of that.” – HEI, outside of England, Russell Group.

3.5 Level of recruitment of international students

Nearly three-quarters (73%) of HEIs said they planned to increase their level of international recruitment, as figure 10 indicates. Russell Group universities were less likely to plan an increase, but this was from a small base. There were no statistically significant differences by region.

Figure 10: HEIs recruitment goals for numbers of international students over the next 1 to 2 years

• Base: HEI survey, All HEIs who actively recruit international students (107).

In the qualitative interviews, those who planned to expand tended to say this was driven by financial reasons.

“[The] only way we can actually grow income is by recruiting more international students.” – HEI, South East, non-Russell Group.

Most of those planning an increase in recruitment were only planning a small increase (53% overall). While around a third were looking to increase the number of students (31%), this was frequently either because they felt that a small increase was what was within their capacity, or felt it was more realistic to have some growth for stability given some uncertainty around policy changes.

“There’s a plan to increase slightly, but it will only be slight because we are a small school…We’ve asked to increase our CAS capacity by about 15 but it’s still under 100 we’ll be requesting.” – HEI, London, non-Russell Group.

“So we’re now looking to broadly stabilize our numbers and a lot of that’s reflecting on governmental policy recently around the dependant changes and within the wireless sector has been reported, you know in a number of areas and there is the significant decrease in stream recruitment.” – HEI, East of England, non-Russell Group.

Just under a third of HEIs (30%) reported that they wanted to increase their markets or diversify them. For some, this was an active part of their institution’s strategy.

“The school’s strategy for overseas growth is about the diversity of the student body, and it was about what overseas students bring to the curriculum, in terms of the student cohort.” – HEI, Yorkshire and the Humber, non-Russell Group.

Others felt that there was a need to offset reducing student numbers coming from the UK and also from the EU following the UK’s withdrawal from the EU.

“Home students have been a steady decline due to pre-COVID-19 and Brexit, a downturn in the 18-year old demographic … so [we’re] exploring more into other markets.” – HEI, South East, non-Russell Group.

A full list of what HEIs were hoping to achieve in relation to their international student recruitments can be found in figure 11.

Figure 11: HEI goals in relation to international student recruitment

One institution reported that they recruited specifically so that they qualified for grants from the Scottish government.

“No, we couldn’t [recruit any less] because we’ve got to hit the Scottish numbers…If we don’t do that, we don’t get the bigger block grants from the Scottish Government.” –HEI, Scotland, non-Russell Group.

As seen in figure 12, 90% of HEIs considered international recruitment to be important to their overall strategy (80% very important). This was often because it was a crucial financial aspect but also that internationalisation was a core part of the philosophy of the institution and how they provide and contribute to education.

“[HEI] has always been an international or a global university, and we have always had a large proportion of international students and staff and I think that that is part of the make-up of a global university, (so we are one of the top 100 in the world). Typically leading universities are very international in terms of not only composition, but how they engage with the world.” – HEI, West Midlands, Russell Group.

Figure 12: Importance of international student recruitment to HEIs ’ overall strategy

Figure 13: activities undertaken to attract international students and meet recruitment objectives.

The most common form of activity to attract international students was overseas outreach and advertising (64%), followed by the use of student recruitment agents (56%). Respondents in the qualitative interviews gave some examples of overseas outreach, which can include recruitment trips, British Consular events in the UK, but also revising what they offer and the language criteria for international students.

In addition to the reasons identified in the quantitative survey as seen in figure 13, respondents in the interviews commented that they were reviewing courses and language policies in order to further appeal to certain target markets.

“The team is also looking at revising our qualifications and English language policy to potentially suit more those markets [Nigeria and Ghana].” – HEI, London, non-Russell Group.

Other strategies identified to increase numbers included having feedback on their website from alumni and running campaigns with Study International. Some identified alumni as the biggest recruitment asset through word-of-mouth and being ambassadors for the institution.

Note: Study International is an independent resource aimed at giving students, parents, educators and institutions a globally-inclined information hub with the latest news and trends in international education.

3.6 Targeted recruitment of international students

Over seven-in-ten (71%) HEIs planned to expand the countries or regions of the world they recruit international students from over the next 1 to 2 years. Sponsors who were previously subscribed to the premium service were more likely to intend to expand than non-Premium sponsors (74% compared with 58%), and non-Russell Group universities were more likely than Russell Group universities (72% compared with 64%, but from a low base so not statistically significant).

As shown in figure 14 the most common country for HEIs to target was the USA (28%), followed by China (24%) and South America in general (20%). The qualitative interviews suggested that countries tended to be targeted for financial reasons.

“Countries being targeted next year include Nigeria and Ghana because the intelligence was telling our international recruitment team that those countries have a very young population, from kind of wealthy backgrounds, and there is a desire from that area for young people to come and study in the UK, so that’s some of the indicators which prompted the team to explore that area.” – HEI, London, non-Russell Group.

In some cases, the motivation was to tap into previously unexplored markets.

“I think we want to look at more of South East Asia in terms of Singapore, China and Vietnam where we traditionally don’t get any students from.” – HEI, South East, non-Russell Group.

Figure 14: Locations where HEIs plan to increase recruitment from

• Base: HEI survey, All HEIs who plan to expand the countries or regions they recruit international students from (76).

3.7 Impact of policy changes

HEIs were mostly positive about their ability to adapt to policy changes affecting students, 66% thought they could do so easily, although only 17% said very easily, as seen in figure 15. The qualitative interviews suggested that the difficulty stemmed from timings and being able to process and disseminate these changes to students efficiently.

Figure 15: Extent to which HEIs are able to easily adapt to visa policy changes affecting students

For changes that affect institutions directly, HEIs were slightly less optimistic about their ability to manage the changes – 60% thought it would be done easily, and 9% very easily, as shown in figure 16. Changes that meant having to adopt new processes could take time, particularly around introducing digital technology such as the shift to eVisas or uploading scans of qualification certificates, because this creates certain questions around how they verified the voracity of digital documents, and particularly the algorithm to filter immigration applications had affected the length of time for processing.

One institution also thought that changes could be difficult to adapt to because they were changes that do not suit institutions and were being made when they can make things harder for HEIs .

“I think the Home Office need to think carefully about how they manage that relationship with the sector, both in our operational level and on that more the wider engagement piece, because I think there’s a certain amount of tone deafness there.” – HEI, South East, non-Russell Group.

Figure 16: Extent to which HEIs are able to easily adapt to visa policy changes affecting organisations

When asked whether specific aspects of policy changes would affect recruitment of international students, many qualitative respondents felt that it was difficult to predict the amount of impact there would be.

“It’s tricky to see how large an impact it’s going to have until it’s kind of been in operation for a while.” – HEI, South East, Non-Russell Group.

As shown in figure 17, those who did feel they could predict what the effects would be thought that most changes would not have a major impact. Just over half (59%) of HEIs thought greater scrutiny over student finances would have an impact (6% to a great extent), 35% thought greater scrutiny over international student agents would have an impact (3% to a great extent) and 27% thought students being unable to switch out of the Student visa route would have an impact (3% to a great extent).

Figure 17: Extent to which HEIs think policy changes to the Student visa will affect their recruitment of overseas students in the UK the following year

HEIs thought that losing the ability to bring dependants was the most likely change to have an effect. Three-quarters (75%) thought this would have an impact to at least some extent, 30% to a large extent.

Some respondents in the qualitative interviews felt that they had already started to see an impact in this regard.

“We have like all other institutions [noticed] a marked decline in the number of applications for this January and we’re as a sector, I suppose we assume we’re putting that down to that removal the of dependants.” – HEI, North West, non-Russell Group.

Across the subgroups, there was a feeling that this change would be likely impact older students in particular, and especially female students.

“It’s a big pull to move to another country and if you’ve got kids or a spouse, you’d want them to come with you naturally.” – HEI, North West, non-Russell Group.

“Our biggest disappointment in regard to that (visa changes), was that we knew that it would particularly impact on women in some cultures where they are not permitted to travel unless their partners come with them.” – HEI, West Midlands, Russell Group.

One institution gave anecdotal evidence that they thought this would have a big impact on Iranian students or certain cultures, but in general respondents found this a difficult topic to talk about with any certainty because it’s not an area that they hold detailed or robust data on.

One specific recent policy change was the ability of students to be able to switch visa routes. For most HEIs it was rare for student holders to switch visas before the end of their studies. Two-thirds (67%) thought it was rare and a third (33%) very rare, as seen in figure 18.

Figure 18: At your institution, how common was it for Student visa holders to switch visas before the end of their studies?

4. dependants.

This chapter covers the characteristics of the Student visa holders who also had dependants on their visa, as well as dependants themselves, exploring their relationship to the visa holders, age, and main activities in the UK before briefly discussing their influence on the visa holder’s decision to come study in the UK.

4.1 Profile of students with dependants

Almost a quarter (24%) of Student visa holders had dependants on their visa. A further 3% expected their partner and/or child(ren) to join them as dependants on their Student visa later, and another 3% on another visa in the future. Lastly, 70% of students had no dependants associated with their visa nor any plans to bring some in the future.

By nationality, students from Nigeria were more likely than those from any other countries to have dependants on their visa, with 59% of them currently having dependants. By contrast, only 2% of students from China had dependants, making them the least likely to have dependants.

By level of study, master’s students (25%) were more likely than those pursuing a doctorate (10%) to have dependants on their Student visa. Additionally, more students who planned to stay in the UK after their studies had dependants (27%), compared to those who wanted to leave the UK (14%).

Also more likely to have dependants were students who worked while studying (35% compared to 18% among those who didn’t work), women (34% compared to 14% among men), and students at non-Russell Group universities (32% compared to 5% among those at Russell Group HEIs ). The likelihood of someone having dependants increased with their age, from 6% among those aged 24 and under to 32% among those aged between 25 and 34 years, and 62% of those aged 35 and over.

4.2 Profile of dependants

Among the students who had dependants on their visa, almost all (94%) had their partner as a dependant, and 35% had their children as dependants. The majority of those with children as dependants had between 1 and 2 children, with a mean average of 1.7 children.

Students from Nigeria were more likely to have children as dependants (53%), and also more likely to have 3 children as dependants (19% compared to 12% overall among those with dependent children).

Additionally, students aged 35 and over with dependents were more likely to have children on their visa (72%), as were those who wanted to stay in the UK (39% compared to 22% among those who wanted to leave).”

Figure 19: Activities of dependant partners

• Base: Visa holders survey, All those who have a partner as a dependant (516).

In terms of the activities of the dependent partners, as shown in figure 19, they were most likely to be a full-time employee in the UK (61%). This was followed by the partners being unemployed (13%) or working part-time (10%). Partners of students from India were more likely than average to be full-time employed (74%).

4.3 Influence of dependants in decision-making

When asked whether they would have still come to study in the UK if they were not able to bring their dependants with them (figure 20), roughly two-in-five (38%) said they would have looked for other options instead. Around half (49%) of students with dependants said they still would have chosen to study in the UK, but 10% would have chosen shorter courses or qualifications. In addition, 13% were not sure what they would have done if bringing dependants was not an option.

Figure 20: Whether people would have still chosen to study in the UK if they could not bring dependants

• Base: Visa holders survey, All those who have dependants (549).

Students with dependants from India were more likely than those from other countries to say they would have still chosen to come study in the UK without their dependants (66% compared to 43% for Nigeria, 41% for Pakistan and 35% for all other countries). The base size for students with dependants from China was too low (5 students) to provide any indications.

In general, the more dependants they had, the less likely Student visa holders were to have applied without their dependants. Just over a third (34%) of those with one dependant would have looked for other options, whereas almost half (46%) of those with 2 dependants and just over half (51%) of those with 3 or more dependants would have looked for other options. Perhaps related to the number of dependants, the likelihood of choosing other options also increased with age, from 34% among those aged 34 and under, to 52% of those aged 35 and over.

“Having them [my children] on my visa was crucial. As I mentioned, the reason why I didn’t go to Canada first is because my daughter was really young at that time and I wasn’t sure if I could study and then have her because she was so young, and also coming to the UK with my children was really something that I considered because I checked all the conditions and I saw that it was possible to bring my family members.” – Student visa holder, France, doctorate, has dependants.

It should be noted that many HEIs interviewed did not record data on dependants in any significant way and did not comment on the influence of dependants in the decision-making process for students. Anecdotally, universities expected to see an impact of students not being able to bring dependants in coming years.

Case study 2 - Dependants

One student came from South Korea to the UK to study a non- STEM subject at a postgraduate (non-doctorate) level. She had previously studied in Australia and came to do a one-year course as a mature student. Her husband had studied in the UK and recommended it because of its culture and lifestyle.

Dissatisfied with life in South Korea, she wanted to come to the UK and while the intention was to study, she would have applied for a work visa if she was unable to come as a student. Being able to bring dependents with her was a critical factor in coming to the UK because she wanted her children to experience a UK education and live close to mainland Europe to be able to experience a wide range of history and culture.

“Compared to other countries, like the US, it’s more like focussing on the polite attitudes and really like a high education for the children from the young ages to higher education as well.”

“I didn’t want my children to have a Korean education because Korean education is very tough [with a] high cost.”

She learned about the visa through her husband, sought further information from the university website and received guidance from an agent. She wanted to do an MBA (masters in business administration) because being able to get the 2-year working visa extension was very appealing, although she noted her university did not advertise this.

“I decided on the MBA because I can get the one-year visa plus 2 years extended visa for working…it was a huge impact on my decision.”

Through the support she received, she found the whole process very straightforward and quick.

“It was a lot faster than I expected compared to Korean speed.”

Student visa holder, South Korea, master’s, non- STEM , has dependants.

More detail about the influence of dependants on the decision to come study in the UK was covered in the chapter on motivations and the decision-making process for coming to study in the UK.

5. Application and sponsorship experience

This chapter explores the visa application process for students as well as the sponsorship process for HEIs . The transition from Tier 4 sponsorship to Student sponsorship is also examined.

5.1 The application process for students

Satisfaction with the application process

Overall, satisfaction with the Student visa application process was high. Over four-in-five (82%) students reported that they were satisfied with the application process as a whole. Over a third (37%) said that they were very satisfied. Only 5% said that they were dissatisfied and just over one-in-ten (12%) said that they were neither satisfied nor dissatisfied. A full break down of satisfaction is shown in figure 21 below.

Figure 21: Visa holder’s satisfaction with the application process

• Base: Visa holders survey, All respondents (2,415).
• Data labels below 3% not shown. ‘Don’t know’ not shown (1%).

Satisfaction was highest amongst students from Pakistan, Nigeria and India (94%, 92% and 90% respectively). Students from China and other countries were less likely to be satisfied. Around three-quarters (78%) of students from China and 73% from other countries reported being satisfied, both lower than average.

Students studying at Russell Group universities were less likely to be satisfied with the application process compared to those studying at non-Russell Group universities. Overall, 86% of students at non-Russell Group universities said that they were satisfied whereas this was 75% for those at Russell Group universities.

Students in the 35 to 44 age group were the most likely to be satisfied with the application process, with 92% having reported being satisfied. The 25 to 34 age group were also more likely than average to be satisfied with the application process with 86% reporting satisfaction. The 16 to 24 age group were the least likely to be satisfied with application process. Less than four-fifths (78%) of this group said that they were satisfied.

By qualification level, those studying a non-doctoral postgraduate degree, such as a master’s degree were the most likely to be satisfied (87%). Those studying a doctorate level degree were the least likely to be satisfied (70%), followed by undergraduate degree level students (71%). Both doctorate and undergraduate students were below the overall average in terms of their satisfaction.

The qualitative interviewing also brought up challenges which affected students during the application process. For example, several people described having to pay more money compared to other countries for elements of the visa application process and that these fees had reportedly gone up in recent years. Others said that they were not made aware of costs for services, such as the NHS, at the start of the application.

“These costs [for the Student visa] were orders of magnitude above the amounts I paid for study visas to France. I paid about 100 euros for France and about £3,000 for the UK for one year.” – Student visa holder, Australia, master’s, has dependants.

“When I started the [visa application] process I did not realise we had to buy in the services of the NHS for the entire life of our visa. The payment wasn’t a problem for me, but it wasn’t necessarily communicated at the outset of the application process.” –Student visa holder, USA, doctorate, has dependants.

Completing the application

When applying for their visa, over three-quarters (76%) of all students said that they had received some help to complete their application. Students most commonly used an education agent to help them with their application (50% of all Student visa holders). Other support came from friends and family (26%), and places of study (12%). A full list is detailed in figure 22 below. Students from India were the most likely to have received support, with 85% of Indian students reporting that they had used at least one person or organisation for help. Nigerian students were the least likely to have used support, though a majority of them still did (65%).

Figure 22: People or organisations from where visa holders received help for their visa application

Students from India were more likely than others to use an education agent, with 61% reporting that they used one to help with their application. This was also higher than the overall average. Students from Nigeria and other countries were less likely than average to use an education agent (42% and 37% respectively). Chinese students were the most likely to have received support from a place of study, with 18% of these students saying that they had received support in this way. Qualitative interviewing suggested that education agents performed a variety of roles, from helping organise paperwork, to translation of official documentation.

“So I actually had like an agent. I thought maybe it was safe to have someone as a person who can guide me.” – Student visa holder, India, master’s, no dependants.

Students attending Russell Group universities were less likely overall to have received support with their application than those attending non-Russell Group universities (73% compared to 77% respectively). However, those attending Russell Group universities were more likely to have received support from a place of study compared to those attending non-Russell Group universities (16% compared to 10% respectively).

Students were asked whether particular elements of the visa application process were easy or difficult. They were asked about:

• locating the necessary documents and information required for their application
• navigating and completing online forms
• receiving updates and communicating with the UK Home Office about the status of their application

Just under half of all students (46%) said that it was easy to locate the necessary documentation for their application. Around a fifth (19%) said that it was difficult and a third (33%) said that it was neither easy nor difficult. Figure 23 below shows the breakdown in further detail.

Figure 23: How easy or difficult visa holders found locating the necessary information or documents for their application

• Base: Visa holders survey, All respondents (2,415). ‘Don’t know’ not shown (3%).

Undergraduate students were the most likely to suggest that they struggled with locating the right documents for their application. A quarter (25%) of this group said that they found it difficult. By comparison, this was only 16% for students studying a master’s degree.

“The financial statements that you need to include are a bit confusing, because not everyone has just one source of income. I had to move some money around to get the one figure acceptable for the application.” – Student visa holder, India, undergraduate, no dependants.

Just over half (52%) of all students found navigating and completing the online application forms easy. Conversely, 15% said that they found it difficult and 31% said that they neither found it easy nor difficult. A full breakdown is shown in figure 24 below.

“It was quite easy for me because everything was self-explanatory … You could easily navigate the site and answer the questions [the Home Office] asked.” – Student visa holder, Nigeria, doctorate, has dependants.

Figure 24: How easy or difficult visa holders found navigating and completing online application forms

• Base: Visa holders survey, All respondents (2,415). ‘Don’t know’ not shown (2%).

Students from Nigeria were the most likely to report finding the online application forms easy to navigate and complete (72%). On the other hand, students from China were the least likely to say that. Just under two-fifths (38%) of these students said that it was somewhat easy or very easy.

Those who had dependants on their visa said that they found navigating and completing the online forms easier than those who did not have dependants (62% compared to 54% respectively).

Those who attended non-Russell Group universities were more likely to say that they found navigating and completing online application forms easy compared to those who attended Russell Group universities (55% compared to 47% respectively).

Overall, just under half (47%) of all students said that they found getting updates about the status of their application easy. Conversely, 22% said that they found this aspect difficult and under a third (28%) said that they found it neither difficult nor easy. A further breakdown of this is shown in figure 25 below. This element of the application process had the highest proportion of students suggesting that it was very difficult (7%), higher than the other 2 aspects investigated. Qualitative interviewing revealed that many had been told that they would receive an outcome to their visa application by a certain date but that this was not met. Some had to re-arrange their travel at their own cost and some missed the start of their course due to Home Office processing delays.

“We were told it would take 3 weeks [for the application to be processed] and it took 11 weeks. We got no updates in that time except for an automated response when we submitted our application … Our passports arrived one working day before we flew out … it was so stressful.” – Student visa holder, Australia, master’s, has dependants.

Figure 25: How easy or difficult visa holders found getting updates about the status of their application and communicating with the UK Home Office

Similar to previous aspects of the application process, there was a difference between students attending Russell Group and non-Russell Group universities. Students attending non-Russell Group universities suggested that they found finding out the status of their visa application and being able to contact the Home Office much easier than those attending Russell Group universities (52% compared to 35%).

Case study 3 - Application experience

This student applied to study in the UK after completing GCSEs and the International Baccalaureate at her international school in India. She applied to 5 universities in the UK as well as Canada. Her first choice was to study in Canada, however her Canadian visa was heavily delayed and the UK visa came back first. She therefore opted for the UK as it was closer to India geographically, and the universities she applied to had a higher global reputation.

In order to complete her application, she reached out to an education agent for support. The agent helped her with her Letter of Recommendation (LOR) and Statement of Purpose (SOP). They also supported her with providing bank statements and financial documents for the application. She had struggled to understand the financial side of the application which was confusing due to the number of bank accounts she held her money in. The education agent was able to guide her through the process and ensure she had her money in the right place.

Once her application was submitted, she received a quick resolution, and she was accepted onto an undergraduate psychology course at the university of her choice.

“The application process is short and straightforward but financial statements less so.” – Student visa holder, India, undergraduate, STEM, no dependants.

5.2 Sponsor experience with the application process

Renewing a sponsorship licence

For an education provider to be able to sponsor visas they must obtain a Student sponsor licence. This licence must be renewed every 4 years in order for HEIs to be able to continue sponsoring visas for overseas students. Through qualitative interviewing, HEIs suggested that sponsorship renewal process was not difficult or cumbersome. One HEI suggested that an online portal for renewal would have been useful as it would have allowed everything to be submitted in one location. However, overall, there seemed to be little issue with the renewal process.

“I think from a business efficiency perspective for the Home Office and for us it would’ve been easier if there was a one stop shop for submitting documents” – HEI, South East, non-Russell Group.

Another HEI mentioned that at the beginning of the Sponsorship Licence, the Home Office said that HEIs would receive a notification that their licence renewal window was opening however this had not materialised.

On the whole, however, most HEIs suggested that the sponsorship licence application process was positive.

“It seemed to be quite sensible, far less complicated than I’d thought. I thought they might ask questions where I’d have to go hunting down the answer, and I didn’t.” – HEI, Wales, Russell Group.

Experience of being a sponsor

HEIs gave mixed responses when describing their experience of being a sponsor. Some HEIs suggested that the experience was positive and that their relationship with the Home Office was constructive. These HEIs also reported that they had good networks between institutions which could help share information.

On the other hand, some HEIs suggested that there were issues with the system and that the Home Office was not always able to help in the way that they would have liked. Several HEIs reported issues during the COVID-19 pandemic when students were stranded either in their home countries or in the UK with expiring visas. One HEI however said that whilst it was stressful at the time, in the longer term, COVID-19 had helped.

“We were forced to do things differently during COVID-19, but in the long term that’s helped us. It’s helped us with new automatic ways of doing things which makes it more robust I think.” – HEI, Wales, Russell Group.

Other HEIs expressed their frustrations at certain aspects of the visa application process for students. Delays in processing for students from low-risk countries had created problems and there were instances where, due to miscommunication, students had been allocated in-country visa application interviews after the HEI ’s final registration date. One HEI suggested that having a live ‘Confirmation of Acceptance’ ( CAS ) update would be useful for ensuring that things like that did not happen. Another HEI said that the communication around CAS allocation was poor.

“We are not told why we didn’t get the CAS we asked for, we should be.” – HEI, West Midlands, Russell Group.

Several HEIs mentioned that the process for assigning CAS and the software was easy to make mistakes on, and the implications of these mistakes could be large. One HEI mentioned that the Home Office did not provide training on the CAS software and training had to be sought through the private sector at a significant cost.

“If we make a very human mistake, it’s very difficult to go back and have that altered, so that’s quite a challenge.” – HEI, Scotland, non-Russell Group.

Additionally, HEIs mentioned that the frequency of policy changes was hard to follow and remember what the current guidelines were. This led to what one HEI described as second-guessing particular rules.

Several HEIs reported that the loss of the Premium customer service support team was a real issue as it meant that they were unable to source the information they required to ensure that they were complying with the guidance. When the HEI survey took place (prior to the closing of the Premium customer service team) 70% of HEIs said that they were a Premium sponsor. One HEI said that because the Premium customer service team no longer existed, when they went to discuss issues with the Home Office, they often had more knowledge than those who they were contacting.

“Those quick announcements and changes in policy direction can be a bit of a challenge.” – HEI, Scotland, non-Russell Group.

“Having the Premium customer service team was an excellent way of getting clarification and confirmation about policy and getting support to ensure that we were abiding and not deviating from the UKVI rules, … but now they are closed.” – HEI, London, non-Russell Group.

When asked what improvements would benefit the experience of being a sponsor, several suggested that the sponsorship management software needed to be updated. Additionally, bringing back the Premium customer service support team was mentioned by a couple of HEIs . Some HEIs also raised the need for consistency with regulations and guidelines which would help ensure that HEI staff would not have to second-guess themselves.

HEI engagement with students regarding sponsorship

Most HEIs said that they were very engaged with students throughout their visa application process. Those who reported that their involvement was not that much said that if applicants were struggling, they would still assist where they could. Engagement throughout the application process took multiple forms including producing written guidance sent to applicants and direct contact with individual applicants if necessary. HEIs said that they often took steps such as directing students to other sources of information first, such as the UK Council for International Student Affairs, before engaging with the student directly.

Whilst students’ studies were ongoing, HEIs reported that they tended only to have direct contact with students if they were failing to comply with the requirements. However, a small minority of HEIs mentioned that they held monthly seminars on compliance information for their students.

“The word we use is compassionate compliance: when a student looks like they might have slightly fallen off the rails, one of our colleagues brings them in, we have a compliance briefing, we reiterate the importance of not missing a tutorial or a lecture to get them back on track … We want to work really closely across our services, so we’re not just saying ‘you’re not being compliant with your visa’, but we’re saying ‘what’s the reason for that, how can we signpost you to services that will help you, and if you’re not able to be compliant, let’s find a way for you to pause your studies so you can go away and deal with that.” – HEI, Scotland, non-Russell Group.

Some HEIs said that they were considering increasing the dedicated support for international students in the future. One HEI mentioned that they were considering creating roles within the university to support.

“We’re thinking about bringing in dedicated visa application advisors…Applying for a visa is more complicated than applying for a mortgage.” – HEI, South East, non-Russell Group.

Most HEIs said that they ran surveys of their international students to receive feedback on their processes. HEIs reported that these surveys often have a poor uptake and that the results were negatively skewed as only those who have had issues tend to fill them in. HEIs felt that a level of frustration was to be expected with visa applications and compliance checks.

Subject specialisms and post-COVID-19 trends

Through qualitative interviewing, HEIs were asked whether there were any subjects that were more popular amongst international students. A majority of HEIs reported that courses related to business and management were most popular amongst international students with some saying that courses in health and nursing were also popular.

Very few HEIs said that course popularity had changed since the COVID-19 pandemic. A minority of HEIs mentioned that there was a greater interest in technology and computer-related courses than there was before the pandemic.

Transitioning from Tier 4 sponsor to Student sponsor

Overall, transitioning from being a Tier 4 sponsor to a Student sponsor seemed to have been a positive experience. Of those who were involved in the transition process from their institution being a Tier 4 sponsor to a Student sponsor, 60% said that the process was fairly easy or very easy. Just over one-in-ten (12%) said that it was difficult and 29% said that it was neither difficult nor easy. A full breakdown is shown in figure 26 below.

Figure 26: How easy or difficult HEIs found the transition from Tier 4 sponsorship to Student sponsorship

• Base: HEI Survey, All those who were involved in the transition process (84).

Of those who did find it difficult, the most common response was that there were difficulties communicating rule changes and dealing with student enquiries. The second most common response was the information was provided too late or was difficult to obtain.

“[It’s] always an area with lots of changes, not necessarily in line with HE cycle, last minute changes which affect students’ admission.” – HEI, Scotland, Non-Russell Group.

Another reason for difficulty discussed in an interview was that there were difficulties surrounding the set-up such as not having a registration number and being unable to get approvals in place.

“The system was so complicated; it took us 2 years to build it.” – HEI, Scotland, Non-Russell Group.

The timing of the change was also a challenge, coming when institutions were dealing with the pandemic and complexities around bringing students to the UK.

“My understanding is everyone will be moving to a digital immigration status check at some point in the next 18 months which is good, but it’s been complex when the whole worlds been kind of turned upside down.” – HEI, South East, Non-Russell Group.

For those who didn’t find the transition to be difficult, there was a sense that these changes were part of a gradual evolution rather than a sudden big change.

“To be honest, it hasn’t made much difference to me… Sponsorship is exactly the same really just with slight changes in the points you get for CAS. But in effect nothing has changed from that kind of experience really.” – HEI, North West, Non-Russell Group.

Throughout the transition process some HEIs had sought support. Those who had been involved in the transition process were asked what support they had used. The most common support used was an account manager (11%), UKVI (10%) and legal advisors (4%). The majority (65%) said that they had not sought assistance during the transition process.

6. Support received

This chapter covers the various forms of support used by HEIs and that was offered to students. This included third-party support for HEIs , Premium sponsorship, support that students received from the HEIs , and finally the work and financial support students received.

6.1 Third-party support received by HEIs

When HEIs were asked about their use of third-party support, such as consultancy firms or immigration advisors, the majority did not use any to manage their sponsorship licences (68%). Of the nearly a third who did use support (31%) the most common organisation types used were immigration law firms (64%).

Over half of the time, third-party support was used to help with audit preparation and mock audits (58%). It was also used for policy review or interpretation (19%) and general advice (11%). The full breakdown of this can be seen in figure 27.

Figure 27: How HEIs use third-party support to manage their sponsorship licence

• Base: HEI survey, All those who have received third-party help (36).

These findings were echoed in the qualitative research, where many respondents had no or minimal interaction with third-party support systems. As with the quantitative research, audits were one of the primary ways that HEIs used third-party support and were mostly used on an ad-hoc basis as and when needed.

International agents were again referenced as the most common source of third-party support, where they either worked in a recruitment role for the HEI or as a way to support students in their application process. Most experiences of using third parties were positive, but some highlighted difficulties using international agents and worried that agents do too much to support students during their application process.

“It’s clear that the agent network does help them [in their application], they probably do too much.” – HEI, South East, non-Russell Group.

6.2 Premium sponsorship

The majority of HEIs surveyed had been Premium sponsors (70%, compared to 28% who were not), and institutions with larger cohorts of international students were more likely to be Premium sponsors (84%). Almost all of the former Premium sponsors used their named account manager and regional account manager (99%), and nine-in-ten used the student immigration history details (93%). The full breakdown of the services used can be seen in figure 28.

Figure 28: Services HEIs have used from the student premium customer service

• Base: HEI survey, All those who are a Premium sponsor (80).

HEIs that had an international student population of over 2,500 students were more likely to use student immigration history details (98%).

On the whole people felt positively about the services offered with the Premium sponsorship, and at least eight-in-ten respondents felt satisfied with the 4 most common services offered. The full breakdown of satisfaction can be found in figure 29.

Figure 29: Satisfaction with services offered by the student premium customer service

• Base: HEI survey, All those who were a Premium sponsor (80).

As can be seen in the quantitative research, the named account manager worked well and HEIs were satisfied with it as a feature. This was supported by the qualitative research where the main element of the Premium sponsor system mentioned was the named account manager. Respondents discussed the benefits of the named account manager which included having detailed knowledge of their institution, ongoing direct support, and a more streamlined process which avoided repetition.

“Having the Premium customer service team was an excellent way of getting clarification and confirmation about policy and getting support to ensure that we were abiding and not deviating from the UKVI rules … but it is now closed.” – HEI, London, non-Russell Group.

“You could go to the premium account manager and get an answer pretty much within a couple of days.” – HEI, North West, non-Russell Group.

The loss of Premium sponsorship was raised by multiple respondents as a negative change, and many reported that they felt disappointed at this decision.

“I think the loss of the premium account manager, I think that’s going to be catastrophic, because you’re not going to have any dedicated support for the errors that happen.” – HEI, Scotland, non-Russell Group.

6.3 Support from HEIs towards students

The majority of HEIs signposted applicants to other sources of help and support whilst they were completing their Student visa application (97%). Other forms of common support offered by HEIs were helping applicants to understand the eligibility criteria (89%) and gathering evidence to support applications (68%). This can be seen in more detail in figure 30.

Figure 30: Help offered by HEIs for applicants whilst they complete their Student visa

• Base: HEI survey, All respondents (115).

HEIs that were looking to increase their recruitment goals were more likely to signpost applicants to other sources of help (100%), and HEIs that were Premium sponsors were more likely to support students in gathering evidence to support their application (75%). HEIs with a medium percentage of international students (between 10% and 20% of all students) were more likely to help students to fill out forms (59%).

In the qualitative research, HEIs discussed a range of support that they offer to students, which included but was not limited to:

• information on the website
• signposting to alternative supports
• online videos and webinars
• regular checks ins and opportunities to discuss their application

HEIs highlighted their role as a place to provide transparency and information, as well as steering applicants in the right direction to find additional support.

“From the visa perspective it is probably more around [providing] transparency because we are often at the coal face in terms of speaking to students and helping them through the process of joining us to study in the UK. The main issue they run up against is the lack of transparency, so – ‘What do I need to put in place to make a successful visa application?’ and it is keeping students updated on that process.” – HEI, West Midlands, Russell Group.

“We try to provide as much information on our website and documentation to kind of steer people in the right direction as well.” – HEI, South East, non-Russell Group.

There was some variation in the amount of support offered to applicants, with some institutions only offering support when something had gone wrong, whereas others took a more hands-on approach in supporting applicants. It should be noted that the HEI that discussed a hands-on approach reported they had only small numbers of international students so potentially had more resource available.

“Because we’ve got a small amount of CAS’s we don’t want any mistakes with the applications so we’re kind of a bit pedantic with it and in touch with them a lot.” – HEI, London, non-Russell Group.

“Even though technically we don’t usually help applicants … if they are really, really in a mess, we will help them.” – HEI, Wales, Russell Group.

When asked about the level of support offered to students, HEIs mostly felt satisfied with their current offer. There was some interest in more resource to provide more support, but others also worried about overwhelming students with too much contact.

HEIs also highlighted that their institution offered different levels of support based on the level of risk associated with their applicants. When it came to HEIs who recruited mostly low-risk applicants there were institutions who offered high levels of support and others who offered lower levels of support. An institution that offered high levels of support did so as they felt there was less risk of losing out due to a rejected application – by offering support across other aspects of the application process they were able to ensure return on the investment.

“So we focus on low risk countries to make the process more streamline and also one the key things is that historically they have less issues with visa applications … Because our students go through such a thorough selection process with all the documentation, by the time they get to the selection process, they have gone through so many hoops that they are unlikely to get rejected.” – HEI, London, non-Russell Group.

However, another institution which recruited from low-risk countries reported less engagement and support offered to these applicants. This was because they were lower risk so needed less support on producing documentation and other requirements.

“Students who are under the differentiation arrangement or low risk, we do less checks which is common practice across the sector.” – HEI, South East, non-Russell Group.

Thinking about the feedback received from international students, HEIs reported that there was usually a level of mixed feedback, but that was to be expected with a stressful process like Student visa applications and often feedback is only received when it was a negative.

“We only tend to hear [feedback] from the ones where they’re having a problem. On the whole, there’s nothing particularly surprising.” – HEI, South East, non-Russell Group.

However, on the whole, universities felt that students had as positive an experience as they could offer.

6.4 Financial support and student’s work

A minority of students’ main reason for choosing to study their course was because they had a grant or scholarship (6%), and students doing a doctorate or from India were more likely to have reported a grant or scholarship as a motivator (24% and 9% respectively).

In the qualitative research, some respondents received financial support such as grants or scholarships. Generally, these grants or scholarships only partially covered the costs associated with their degree. There were mixed views on whether receiving a grant or scholarship influenced their decision to attend university in the UK. Some had already made up their minds to study in the UK regardless of the outcome of their scholarship, whilst others said it was an incentive to study in the UK over another country.

“It was an incentive for me, knowing that I would have part of my cost of living covered by the tuition fees.” – Student, France, doctorate, has dependants.

The majority of students had not undertaken any paid work alongside their studies (68%), though of these 46% were considering taking up some form of paid work in the future, whilst around a quarter of students were working (23%). Students who worked alongside their studies were more likely to be from Nigeria and India (47% and 33% respectively), as were those studying for their doctorate (33%).

The majority of work was non-study related work (73%), with a third working on a study-related work placement (32%). Doctoral students were more likely to have a study-related work placement (57%), as were those who attended a Russell Group institution (45%).

In terms of sectors, the most common sectors students were working in were hospitality and wholesale / retail work (36% and 23%). The full breakdown of sectors can be found in figure 31.

Figure 31: Sectors that students worked in

• Base: Visa holders survey, All those who have undertaken paid work (618).

Students who were studying at undergraduate level were more likely to work in hospitality (45%), whilst those studying for a doctorate were more likely to work within education (51%). Students who had dependants were more likely to work within the health and social work sector (40%), as were students from Nigeria (53%).

Students said they worked alongside their studies because primarily to gain work experience and to meet new people (68% and 57% respectively). Other reasons students worked were to support themselves or family in the UK (47%), to practice their English (36%) or to support themselves and / or family outside the UK (22%).

Students from Nigeria were more likely to report the main reason why they worked was to gain work experience (85%), whilst students from Pakistan and India were more likely to say that it was to practice their English language skills (64% and 50%).

Similar findings were found in the qualitative interviews, with respondents highlighting the importance of gaining work experience.

“[I worked] because I need extra money, and also I need experience; teaching at [my university] is a great experience which I want to have on my CV.” – Student visa holder, France, doctorate, has dependants.

Students also discussed the impact of the increased cost of living as a reason for engaging with paid work, as well as unfavourable exchange rates.

Students were working an average of 16.9 hours a week. The majority of students were working 16 to 20 hours (73%), and a small minority were working more than 20 hours (2%) within one week. The 2% working more than 20 hours during term time are not working within the rules. This is a small minority and may also be at least in part an error in approximation on the part of the student. The average time spent working increased to 22.3 hours a week when students were asked about their time spent working outside of term time. Outside of term time around half of students were working more than 20 hours a week (43%) and a third worked 16 to 20 hours a week (33%). More detail can be seen in figure 32.

Figure 32: Hours worked by students in and outside of term time

• The data labels not shown are 2%.

As shown in figure 32, the number of students working over 16 hours a week did not vary much from term to non-term time, but the way in which they were working changed.

Outside of time term over half of the 73% of students who worked 16 to 20 hours a week moved to working more than 20 hours a week (43%). The students who worked more casual hours (less than 15 hours a week) were less likely to work outside of term time, with the number of students who did not work at all raising from 2% to 16%.

Students from Pakistan, India and Nigeria were more likely to work 16 to 20 hours during term time (88%, 81% and 79% respectively). Outside of term time, students from Nigeria were more likely to work over 20 hours a week (54%) and to work on average of 25.1 hours a week. Master’s students were more likely to work 16 to 20 hours a week during term time (80%).

From qualitative research, respondents felt that it could be hard to secure work and felt that the 20-hour limit was sometimes a barrier. Though they did report that it was easy to keep under the 20-hour cap during term time once they had secured work. Some noted that their employers were well versed in the regulations which made it simpler for them.

“I told my employer I was a student, and he explained the conditions to me.” – Student visa holder, Nigeria, Master’s, has dependants.

In terms of pay, students most commonly earned between £10.43 and £14.99 per hour. Nine-in-ten students earned up to £14.99 an hour (90%), and over a third earned up to £10.42 an hour (35%). This can be seen in figure 33.

Figure 33: Visa holders earning per hour

Students from Nigeria were more likely to earn between £10.43 and £14.99 per hour (71%), whilst students from India were more likely to earn between £7.49 and £10.42 per hour (44%).

Case study 4 - Work and study

This student came from Nigeria to study a STEM master’s degree, with the aim of applying for a further doctorate programme. He wanted to stay in his home country but became dissatisfied with the quality of the teaching and lack of research opportunities. He applied to study in the UK and received a £2,000 scholarship for his particular course. This was an influencing factor when he chose to study in the UK at the specific university. He viewed this scholarship as a ‘discount’ for paying the university fees.

When he first started at university, he did not work but once term time finished, he began to look for work. The student wanted to work to meet new people and because a UK salary converts to more money in their home country. Initially, he found it difficult finding suitable work, as he wanted to work in a school setting or a professional setting related to their course, but the timing was wrong for the school roles, and he could not meet the working hours criteria employers were looking for.

“I applied to schools for a teaching assistant role, but they were on summer break, and when I applied for professional jobs, I was unable to get one; they all wanted full-time, full-time, full-time.”

Whilst he looked for work in a school, he got work in a warehouse. The student felt that this work helped him build confidence and allow for a settling-in period. Eventually he joined an agency and worked once a week as an agency supply teaching assistant.

Student visa holder, Nigeria, master’s, STEM , has dependants.

7. Future intentions

This chapter explores the future plans of students and whether they intended to remain in the UK after finishing their studies, as well as what they planned to do in the UK once their studies had finished, and the different visa routes they were considering. Additionally, this chapter also looks at HEIs ’ plans around their status as a Student sponsor in the future and explores any further reflections they may have.

7.1 Future plans for students

More than half (58%) of Student visa holders said that they would apply for a further visa to stay in the UK once their current visa expires. Nearly a third (31%) of students were not sure yet if they would apply for a further visa.

Nearly one-fifth (18%) of Chinese students said that they would not apply for a further visa, making them the least likely out of all nationalities planning to stay in the UK after their studies. A further two-fifths (41%) of Chinese students did not know if they would apply for a further visa, which was higher than reported in all other nationalities (Table 4).

Table 4: Intention to apply for a further visa once current visa expires

• Base: Visa holders survey, All visa holders (2,415); India (519), China (507), Nigeria (431), Pakistan (155), Other (803).

Master’s students were most likely to be planning to apply for a further visa, when compared to doctoral students and undergraduates (60% compared to 45% and 52% respectively). However, undergraduate students and doctorate students were also more likely to report that they did not know if they would apply for a further visa (37% and 44%) when compared to master’s students (28%).

Students who had dependants on their Student visa were more likely than those with no dependants to report that they intended to apply for a further visa (67% compared to 57%). They were also less likely to not know if they intended to apply for a further visa (27%).

Older students had a better understanding of their future intentions than younger students. Over three-fifths (62%) of students aged 25 and over had the intention of applying for a further visa. In contrast, over a third (34%) of students aged between 16 and 24 reported that they did not know if they would apply for a further visa, which was higher than those aged 25 and over(28%).

Students who had worked whilst studying were more likely to be planning to apply for a further visa. Nearly three-quarters (71%) of those who had worked whilst studying intended to apply for a further visa compared to over half (55%) of those who did not work whilst studying. Additionally, those who did not work whilst studying were more likely than those who worked whilst studying to say they did not intend to apply for a further visa (14% compared to 6%) or that they did not know if they intended to do so (31% compared to 23%).

Most students who intended to stay in the UK planned to work (76%), followed by planning to enrol in further study (38%). Just under one-in-ten (8%) of those who intended to stay in the UK were not sure of their future plans.

There were notable differences in sub-groups in terms of which students were considering working in the UK. Nigerian students who were planning to stay in the UK were more likely to be planning to work in the UK (83%). Furthermore, master’s students were more likely to be planning to work in the UK (80%). For those with no dependants, over four-fifths (81%) reported that they planned to work in the UK. Those who were aged between 25 to 34 and 35 to 44 were also more likely to plan to work in the UK (80% and 85% respectively). Unsurprisingly, those who had worked whilst studying were more likely to plan to work in the UK after their studies compared to those who had not worked whilst studying (84% compared to 75%).

In terms of enrolling in further study, Chinese students were more likely than any other nationality to be planning to take this route (58%) at the end of their visa. Similarly, undergraduates were more likely to be planning to enrol in further study (60%), as were younger students aged between 16 to 24 (43%). Additionally, those who were studying at Russell Group universities were more likely to be planning to enrol in further study compared to those in non-Russell Group universities (48% compared to 35%).

The most important factor for students when considering remaining in the UK were opportunities for work in the UK (91%). The next most important factors were familiarity with the English language (37%) and having personal networks in the UK (34%) (figure 34).

Figure 34: Importance of factors when considering remaining in the UK

• Base: Visa holders survey, All visa holders intending to stay in the UK (1,439).

The importance of certain factors varied depending on the nationality of students. Nigerian and Chinese students were more likely to think that personal networks (49% and 43%) were important than Indian and Pakistani students (24% and 23%). They were also more likely to think that familiarity with British culture was important (50% and 44%) compared to Indian and Pakistani students (25% and 27%). Chinese students were the most likely out of all nationalities to think that familiarity with the English language was an important factor (57%).

In terms of work being a motivating factor to remain in the UK, those studying at Russell Group universities were more likely than those studying at non-Russell Group universities to think opportunities for work in the UK was an important factor (94% compared to 90%). Students with dependants on their visa were more than twice as likely to think opportunities for dependants to work was an important factor (33% compared to 16% overall). This suggests that when it comes to decision-making, those with dependants’ place emphasis on the benefits that were available to not only them, but also to their dependants.

There were also further subgroup differences when personal networks in the UK was a motivating factor. Doctoral students, (64%), those at Russell Group universities (42%) and students aged between 35 and 44 (42%) were all more likely to think that this was an important factor.

Most of the students in the qualitative interviews were also planning to stay in the UK. Many were planning to work in the UK or were at least considering it as part of their plans.

“I want to gain professional experience in Business analytics because that was my main purpose for coming here” – Student visa holder, India, master’s, no dependants.

In line with the survey, a few students also mentioned staying in the UK to enrol in further study, such as master’s or a PhD.

Some students we interviewed were motivated to remain in the UK due to better opportunities in the UK. This included jobs being more readily available as well as having access to high quality education. It was also noted that it was relatively easy to stay in the UK as they were familiar with the culture, had developed local networks and had visa options available to them. A few students interviewed also reported that the Graduate route and the time it gave them to think about their future plans was an encouraging factor to consider staying in the UK.

“Also it’s in Leeds, so it allows me to stay local, because all my friends I knew after I get to UK, my church, Christian Union, it’s all in Bradford… so Leeds gave me that option [to stay local].” – Student visa holder, China, undergraduate, no dependants.

“The Graduate route is something that I’ve considered. So, I think that’s one thing that’s attracting me to stay because it gives you more time to find work and stuff like that.” – Student visa holder, USA, doctorate, no dependants.

Of the few students from the qualitative interviews who were unsure of what they planned to do in the future, this was mostly because they considered they had time on their side to decide as they were on an undergraduate course. The students did have some idea of what they may do in the future but nothing firmly decided.

The Graduate route was the most likely route that students who wished to stay in the UK would apply through (62%), followed by Skilled Worker visa (34%) and Global Talent visa (10%) (figure 35).

Figure 35: Visa routes being considered for application after studies are finished

• Percentages <3% are not included in this chart.

There was a considerable difference in the routes students were thinking of taking depending on their nationality, with Chinese students overall most likely to apply for a range of visas, as shown in table 5 below. Nigerian students were most likely to apply for the Skilled Worker visa (49%), the Health and Care Worker visa (25%) and indefinite leave to remain (settlement) (13%). Pakistani students were the most likely to not know which routes they might apply for (21%).

Table 5: Potential routes students might apply for after finishing studies

• Base: Visa holders survey, All visa holders intending to stay in the UK, Total (1,439); India (346), China (211), Nigeria (308), Pakistan (106), Other (468).

As the Graduate route was the most popular potential visa route, it was selected by a range of students. Doctorate students were more likely to consider the Graduate route (83%) as well as students studying non- STEM subjects (65%) and at Russell Group universities (71%). Furthermore, those with no dependants were more likely to consider the Graduate route (66%).

Visas that related to working also attracted certain students. The Skilled Worker and Health and Care worker visa was more likely to be considered by students on STEM subjects (38% and 10% respectively), those at non-Russell Group universities (36% and 10%) and those who had worked whilst studying (45% and 12%).

Over half (56%) of those who did not plan to stay in the UK after their course reported that they would leave immediately after the end of the course. Just under one-fifth (18%) reported that they would stay longer and just over a quarter (26%) did not yet know.

Subgroup analysis for this particular question was limited due to small base sizes. However, it should be noted that men were more likely to leave the UK immediately compared to women (64% compared to 48%). Women were also more likely to not know how long they planned to stay in the UK (31% compared to 20% of men).

Case study 5 - Future intentions

This Student visa holder was a master’s student from India who studied international business. She had her husband and her child as dependants on her visa. Whilst studying in the UK, she had undertaken work, which included working at a fast-food restaurant and at a retail store as a sales associate. After her Student visa expired, the student planned to either apply for the Graduate visa so that she could work or secure a Skilled Worker visa. This was part of her original 5-year plan as the student thought working in the UK in her field would be a different experience to studying in the UK.

“I, along with the student experience in the UK, want the job experience too, so if I’m not getting the Skilled Worker one, I’ll apply for the Graduate route visa.”

“So far I’ve worked in the retail sector, but that’s not where I want to work in the long run, so I want to get the perfect [multinational corporation] (MNC) experience to add to my previous work experience.”

Another factor that motivated the student to stay in the UK was that she was on a 2-year long master’s course, with the intention being that students would secure an internship during this time. However, she found the process of securing an internship very difficult and was ultimately unsuccessful. By moving onto the Graduate route or securing a Skilled Worker visa, she hoped to be able to gain the job experience she would have gained from the internship.

Student visa holder, India, master’s, non- STEM , has dependants.

7.2 Remaining a HEI sponsor

Nearly all (98%) HEIs said that they were likely to continue to be a Student route sponsor. The majority (95%) of HEIs reported that it was very likely they would continue to do so.

Nearly three-in-ten (29%) HEIs reported that they had no further reflections on being a Student route sponsor. Of those who did have reflections to share, the most common ones related to the communication from the Home Office needing to be improved (23%) and issues with the premium account service (23%). This was followed by issues with policy changes or timings of policy changes (21%) (figure 36).

“The uncertainty and the changes of the last year or so do make our lives quite difficult.” – HEI, Wales, Russell Group.

“The Home Office need to think carefully about how they manage that relationship with the sector, both in our operational level and on that wider engagement piece, because I think there’s a certain amount of tone deafness there. Most of the sector wasn’t in favour of the withdrawal of the premium customer service, they wanted it to be enhanced, improved so offered better value for money. But that seems to have been interpreted by the Home Office as nobody wants to pay so let’s make it a free service and offer less…” – HEI, South East, non-Russell Group.

Figure 36: Further reflections from HEIs on what can be improved

• Base: HEI Survey, All HEIs (115).

Those who sponsored over 2,500 international students were more likely than average to report policy changes (33% compared to 21% overall). They were also more likely to want more support or consultation from the Home Office (23%) and would like to see improved information sharing between the Home Office and student route sponsors (9%).

8. Conclusions

8.1 decision making and prior awareness of visa routes.

Students indicated that they were most likely to have heard about the Student visa from friends or family members (23%), from education agents (22%) and places of study in their home country (19%). It was often the case that these friends and family were students in the UK and had Student visas themselves, which indicates that they would be in a good position to offer advice or share knowledge about the Student visa.

The majority of Student visa holders said their reason for coming to study in the UK under the Student visa was because they wanted to pursue a particular course at a particular university (60%). Only 4% of international students said their main motivation was primarily wanting to live in the UK.

Among the students for whom living in the UK was at least partly important, access to the Graduate route, the ease of the application and the ability to bring dependants were influences on student’s decision to get a Student visa rather than a different UK visa, though the most common reason was because they mainly wanted to study in the UK. Most students (70%) were aware of the Graduate route visa before the survey had taken place, particularly those studying at a postgraduate level.

Half of the Student visa holders (50%) also considered other countries before applying to come to the UK, most commonly the USA and Canada. The UK Student visa was a factor in deciding to come to the UK over other countries in almost a quarter of cases.

The ability to change to a different visa before finishing their studies was perceived as important by almost a third of non-doctoral international students, but three-quarters of those students would not have been deterred from applying for a UK student visa if this option wasn’t available at the time.

Most (93%) HEIs reported that they actively recruit international students, mostly to increase cultural diversity, but also motivated by financial reasons. Most HEIs planned to further increase their level of international recruitment as well as to expand the countries or global regions that they recruit from.

International recruitment was seen as a core element of most HEIs ’ overall strategy from an internationalisation and financial point of view as well. HEIs did this mainly by overseas outreach and advertising and via the use of student recruitment agents. Most commonly targeted countries for HEIs were the USA and China and South America in general.

Finally, HEIs were mostly positive about their ability to adapt to policy changes affecting both students and the institution itself. However, some HEIs mentioned that the frequency of policy changes was hard to follow and remember what the current guidelines were. This led to what one HEI described as second-guessing particular rules. Several HEIs reported that they were disappointed with the loss of the premium customer service support. As well wanting to see this reinstated, HEIs felt that the sponsorship management software needed to be updated.

8.2 Dependants

Almost a quarter (24%) of Student visa holders had dependants on their visa. Almost all of these had their partner as a dependant, and just over a third had children as dependants. Most dependent partners were employed full-time (61%), with a further 10% being employed part-time.

About half of all students with dependants said that they would have still chosen to come study in the UK if they couldn’t bring their dependants on their visa, while just over one-in-three would have looked for other options and 13% were unsure of what they would have done.

8.3 Visa application and sponsorship experience

Overall students were satisfied with the application process, Over four-in-five (82%) students reported that they were satisfied with the application process as a whole. Over a third (37%) said that they were very satisfied. Students studying at Russell Group universities were less likely to be satisfied with the application process compared to those studying at non-Russell Group universities.

When applying for their visa, over three-quarters (76%) of all students said that they had received some help to complete their application. Students most commonly used an education agent to help them with their application.

Students were asked whether particular elements of the visa application process were easy or difficult. They were asked about: locating the necessary documents and information required for their application, navigating and completing online forms, and receiving updates and communicating with the UK Home Office about the status of their application. Just under half of all students (46%) said that it was easy to locate the necessary documentation for their application.

Through qualitative interviewing, HEIs were asked whether there were any subjects that were more popular for applications amongst international students. A majority of HEIs reported that courses related to business and management were most popular amongst international students with some saying that courses in health and nursing were also popular.

Most HEIs said that they were very engaged with students throughout their visa application process. Those who reported that their involvement was not that much said that if applicants were struggling, they would still assist where they could.

Through qualitative interviewing, HEIs suggested that sponsorship renewal process was not difficult or cumbersome.

On the other hand, some HEIs suggested that there were issues with the system and that the Home Office was not always able to help in the way that they would have liked.

Transitioning from the Tier 4 to the Student visa route was not seen a difficult by HEIs . Only difficulties flagged were in getting quick specific information about and communicating rule changes to students, compounded by the timing of the change with the COVID-19 pandemic, which had added further complexity.

Overall, transitioning from being a Tier 4 sponsor to a Student sponsor seemed to have been a positive experience. Of those who were involved in the transition process from their institution being a Tier 4 sponsor to a Student sponsor, 60% said that the process was fairly easy or very easy.

8.4 Support received and student’s work

When HEIs were asked about their use of third-party support, such as consultancy firms or immigration advisors, the majority did not use any to manage their sponsorship licences (68%). Audits were one of the primary ways that HEIs used third-party support and were mostly used on an ad-hoc basis as and when needed.

On the whole HEIs felt positively about the services offered with the Premium sponsorship, at least eight-in-ten respondents felt satisfied with the 4 most common services offered.

The majority of HEIs signposted applicants to other sources of help and support whilst they were completing their Student visa application (97%). Other forms of common support offered by HEIs were helping applicants to understand the eligibility criteria (89%) and gathering evidence to support applications (68%).

Only a minority of students’ main reason for choosing to study their course was because they had a grant or scholarship (6%), and students doing a doctorate or from India were more likely to have reported a grant or scholarship as a motivator (24% and 9% respectively). Similarly, the majority of students had not undertaken any paid work alongside their studies (68%), though of these 46% were considering taking up some form of paid work in the future, whilst around a quarter of students were working (23%).

8.5 Future intentions

Master’s students were most likely to be planning to apply for a further visa, when compared to doctoral students and undergraduates (60% compared to 45% and 52% respectively).

Students who had worked whilst studying were more likely to be planning to apply for a further visa. Nearly three-quarters (71%) of those who had worked whilst studying intended to apply for a further visa compared to over half (55%) of those who did not work whilst studying.

Some students we interviewed were motivated to remain in the UK due to better opportunities in the UK. This included jobs being more readily available as well as having access to high quality education.

The Graduate route visa was the most likely route that students who wished to stay in the UK would apply through (62%), followed by Skilled Worker visa (34%) and Global Talent visa (10%).

Appendix 1: Methodology

Student visa holder method.

The study with Student visa holders comprised of an online survey of over 2,000 international students, and follow-up qualitative interviews with 25 students.

The contact details for the student survey were provided by the Home Office. A file containing the details of international students who had had their Student visa approved since 2019 was sent securely and saved on the IFF Research internal secure access servers. The reason for only including Student visa holders from the last 4 years was in order to increase the number of visa holders who were still students and had not completed their studies yet. The data from the Home Office was cleaned to remove any accidental duplicates and to exclude students whose email address was that of an agency or law firm that helped them with the application process, in order to try to maximise the response rate from the drawn sample.

The survey consisted of a one-week pilot between 20 and 26 September 2023 and a mainstage fieldwork period of 5 weeks between 18 October and 20 November 2023.

A sample of 2,000 records was randomly selected from the cleaned file for the pilot, and 40,000 contacts were drawn for the mainstage survey, representative of the total population of Student visa holders by a cross-section of nationality and age and gender. The Home Office were particularly interested in the nationalities that had the highest number of Student visa holders, therefore the top 11 countries were monitored separately, while all other countries were grouped together.

The survey and all communications were translated and made available in Mandarin for all students from China. Weekly reminder emails were sent to those who had not yet completed the survey, including those had only partially completed it, up to a maximum of 4 reminders.

The survey was completed by 46 students during the pilot and by 2,369 students during the mainstage fieldwork period, a total of 2,415 completes. In order to keep the profile of the survey completes as close to the population profile as possible, the data was weighted to nationality by age-band (the gender split was already close to that of the overall population). The full weighting grid can be found in table 6.

Table 6: Weighting grid profile for the Student visa holder survey, country of origin by age

The number of international students surveyed was split across the different demographic categories as represented in table 7 through to table 12.

Table 7: Achieved student interviews by country and age

Table 8: achieved student interviews by country and gender, table 9: achieved student interviews by country and level of study, table 10: achieved student interviews by country and university type, table 11: achieved student interviews by country and subject of study, table 12: achieved student interviews by country and whether they have dependants.

For the qualitative interviews with students, we aimed to cover a wide range of experiences and profiles, with a focus on a few characteristics, as represented in table 13 below. We also covered a good spread of subjects studied (15 non- STEM , 10 STEM ), despite it not being an original quota.

Table 13: Qualitative interviews achieved with students, by category

The qualitative interviews covered in more detail student’s decision making process for coming to study in the UK, their experience with the UK Student visa application process, their experience of working while studying, and their plans for after they finish their current studies.

Ten interviews were conducted by telephone and 15 via Microsoft Teams. The interviews lasted around 45 minutes on average and took place between 8 November and 11 December 2023.

Higher education institutions ( HEIs ) method

The study with HEIs comprised a telephone survey of 115 institutions, and follow-up qualitative interviews with 20 institutions.

The sample for HEIs comprised 172 institutions, with up to 4 named contacts for each, and all were considered in scope for the survey. A census approach was adopted, and no weighting applied. Contact details were provided from the Home Office for up to 4 members of staff at each institution that had a role that made them suitable to talk about the impact of sponsorship policy on their institutions decisions to attract international students and the requirements of being a sponsor. These roles included: Associate Directors of Admissions, Deputy Academic Registrars, Head of Compliance and Immigration Compliance, Head of Admissions, and Director of Human Resources. Screener questions were used in the questionnaire to ensure the respondent was in a position to answer questions fully.

Minimum call protocols were put in place for each piece of sample so each institution was treated equally as it would be for random probability sampling (RPS).

The telephone survey consisted of a one-week pilot between 18 and 22 September 2023 and a mainstage period of 5 weeks between 16 October and 7 December 2023.

Table 14: Achieved HEI interviews by geographical region

Table 15: achieved hei interviews by russell group/non-russell group status, table 16: achieved hei interviews by prior premium sponsor/non-premium sponsor status.

For the qualitative interviews with HEIs , soft quotas were used to ensure coverage across some areas as outlined in table 17.

Table 17: Qualitative interviews achieved with HEIs by category

The qualitative interviews covered in more detail HEIs ’ level of engagement with sponsoring students (for example, intermittent vs. extensive), length of time as a sponsor, experience of being a sponsor and renewing licences, use of third-party support, and subject specialisms.

Five of these interviews were conducted by telephone and 15 via Microsoft Teams. The interviews lasted around 45 minutes on average and took place between 14 November and 14 December 2023.

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• Carnegie Classification
• American Council on Education
• Higher Education Today
• Race and Ethnicity in Higher Education

2025 Social and Economic Mobility Classification

In 2022, ACE and the Carnegie Foundation for the Advancement of Teaching partnered to design a Social and Economic Mobility Classification that would complement the existing classification structure. From the outset, the Social and Economic Mobility Classification has been intended to center students and drive institutional improvement that can increase access to higher education and improve outcomes.

By design, the Social and Economic Mobility Classification will identify institutions throughout the U.S. higher education landscape that provide strong socio-economic mobility for students, and it will equip users to understand how an institution’s data compares to similar campuses. This classification-based approach will facilitate richer research and study, help to identify successful strategies, and allow institutions to collaborate with each other to find solutions.

The classification will be released in spring 2025 alongside the revised Basic Classification . Ahead of the release, ACE and the Carnegie Foundation are providing updates on the classification design and methodology in order to gather feedback from the field. At this time, no institution has been classified, and because the model is not finalized, it is not possible to know how specific institutions will fare.

Draft Framework for 2025 Social and Economic Mobility Classification

Over the past 18 months, the Carnegie Classifications staff has worked with several experts and advisory groups, including a Technical Review Panel and Institutional Roundtable , to develop a framework for classifying institutions based on the types of students they serve and the outcomes that students experience. For more context on these conversations, please read the blog post from the chair of the Technical Review Panel .

The Carnegie Social and Economic Mobility Classification has the following objectives:

• Create groupings of meaningfully similar institutions, likely connected to the Basic Classification.
• Within those groupings, assess the extent to which institutions offer broad access to learners and evaluate the outcomes of past students.
• Present results in a visual way that emphasizes the complex and multidimensional nature of social and economic mobility.
• Have clear transparency in the data and methodology.

Like the Basic Classification, the Social and Economic Mobility Classification will be a universal classification, and every degree-granting college and university will receive a classification. As such, the classification will rely on publicly available data sources that contain data on all institutions in the United States. These data provide key information about a campus, but we recognize they are sometimes incomplete. While other data providers may have richer datasets for a limited number of institutions, the value of the Carnegie Classifications is in classifying every institution. We also believe the public, universal data that is available can be used to make meaningful analyses that can complement those other sources.

To measure access, the classification will evaluate whether institutions are enrolling a student population that is representative of the locations they serve. To do this, we currently plan to use data describing the enrollment of undergraduate students by race and ethnicity as well as Pell grant status, as reported in IPEDS. Those data would be adjusted based on the location that students are from.

To measure outcomes, the classification will focus on students’ economic success. We currently plan to use undergraduate post-attendance earnings as reported by the College Scorecard and compare those earnings to a reference group, such as those with a high school diploma or associate degree-holders. This earnings data would be adjusted and analyzed based on the geographical and racial/ethnic composition of the student body, recognizing that students’ experiences in the labor market may be affected by their location, race/ethnicity, sex, and/or age. For those adjustments and analyses, we plan to use data from the U.S. Census.

This framework for social and economic mobility would separately analyze the concepts of access and outcomes. To display the results, the classification could look something like the following, with institutions being compared in the context of peer groups.

Provide Feedback on the Social and Economic Mobility Classification

We would welcome feedback on the specific measures we should use as well as the overall approach. As mentioned above, the Carnegie Classifications are a universal classification system. Accordingly, the data the classifications will use must be from publicly available, universal data sources, meaning they are available for all institutions across the country.

Feedback would be particularly helpful on the following concepts:

• Specific measures of access that should be included in addition to or instead of data on the percent of students who are Pell recipients and the racial/ethnic composition of the student body (e.g., other student characteristics, inclusion of other groups of students, etc.)
• Specific measures of outcomes that should be included in addition to or instead of the earnings of former students (e.g., completion rates, retention rates, etc.)
• In measuring earnings, whether we should consider all students or only program completers
• How to identify the geographic areas served by colleges and universities (e.g., use migration data to determine original state of residence for the student body, use the state the institution is located in, etc.)
• We currently plan to provide a visual categorization as opposed to a ranking. Would the framework as pictured above be a helpful illustration, or would another representation of the data be more useful?
• Other data we should include for reference in the presentation of results, even if not included in the student access and outcome determinations (e.g., completion rates, median undergraduate debt levels, loan default rates, etc.)

The feedback form below will be open until July 31, 2024. We welcome any ideas and thoughts.

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