rubric for essay writing in science

An official website of the United States government

Official websites use .gov A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

• Publications
• Account settings
• Advanced Search
• Journal List

Development and Validation of a Universal Science Writing Rubric That is Applicable to Diverse Genres of Science Writing

Alycia pisano, amanda crawford, heather huffman, barbara graham, nicole kelp.

• Author information
• Article notes
• Copyright and License information

Citation Pisano A, Crawford A, Huffman H, Graham B, Kelp N. 2021. Development and validation of a universal science writing rubric that is applicable to diverse genres of science writing. J Microbiol Biol Educ 22:e00189-21. https://doi.org/10.1128/jmbe.00189-21 .

Corresponding author.

Received 2021 Jun 22; Accepted 2021 Aug 24; Collection date 2021 Dec.

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license .

It is critical for science, technology, engineering, and mathematics (STEM) students to develop competencies in science communication, including science writing. However, it can be difficult for instructors and departments to assess the quality of their students’ science writing. Many published science writing rubrics are specific to certain genres like lab reports. We thus developed a Universal Science Writing Rubric (USWR) that is usable regardless of the genre or audience of science writing. This tool enables students, instructors, and departments to assess science writing written to lay or scientific audiences, focusing on important rhetorical concerns like science content and interpretation rather than simply surface features like grammar. We demonstrate the use of our USWR on various life science lab reports, scientific review articles, grant proposals, and news articles, showing that the USWR is sensitive enough to highlight statistically significant differences between groups of student writing samples and valid enough to produce results that echo published and anecdotal observations of STEM student science writing skills. Thus, the USWR is a useful tool for assessment of STEM student science writing that is widely applicable in the classroom and laboratory.

KEYWORDS: rubric, writing, science communication, assessment tool

INTRODUCTION

Science, technology, engineering, and mathematics (STEM) students must develop communication skills, including science writing, to become effective future scientists. Thus, STEM curricula often involve writing, including lab reports, for students to develop these skills. Many instructors follow the best practice of providing a rubric when grading student writing ( 1 ). However, these rubrics are created with various goals for each assignment, so a “90%” on a paper graded with one rubric is not comparable to a “90%” on a paper graded with a different rubric, precluding programmatic assessment. Additionally, instructors and teaching assistants often grade more on surface features like grammar instead of discourse and content ( 2 , 3 ).

Some published science writing rubrics, including the “Conclusion Assessment Rubric” ( 4 ) and “Rubric for Science Writing” ( 5 ), can provide more consistency, but these are focused on laboratory/data reports and are not translatable for other genres. In addition to traditional “science writing” like lab reports or research papers, assessing students’ skills in communicating science to nonscientific audiences is important. A published instrument for assessing science writing geared toward public audiences focuses on analogy, narrative, and dialogue ( 6 ), making it appropriate for lay writing but less applicable to science journal articles.

We thus created a Universal Science Writing Rubric (USWR) that can apply to all genres of science writing from the classroom and laboratory, regardless of intended audience. Our rubric was informed by a multidisciplinary perspective ( 7 , 8 ), bringing theory and methods from science education ( 9 , 10 ), science communication ( 11 , 12 ), and applied linguistics ( 13 , 14 ). As shown in Table 1 , the USWR is a tool to assess various rhetorical concerns in students’ writing, including clarity of scientific content, interpretation of scientific content, targeting the audience, organization, and writing quality. In this article we present the USWR, implementation ideas, and sample data that it can produce to demonstrate its validity and practicality for diverse science writing genres.

Universal science writing rubric

The USWR is a useful tool for student self-assessment, peer grading ( 15 ), instructor or teaching assistant grading ( 3 ), and departmental programmatic assessment of any science writing from the classroom or laboratory. The USWR is also useful for science education researchers to complete pre- and post-assessment of curricular interventions regarding science writing. Because the USWR does not simply check for the inclusion of assignment-specific components but instead focuses on competencies that cross genres, the USWR enables students, teachers, and researchers to holistically assess the progression of students’ skills over time.

The USWR could be modified in many ways to support diverse needs as follows.

In our preliminary testing, we assigned the 4 levels scores of 0 to 3. These numbers could be increased to recognize student effort.

The rubric could be used honestly across students in a department, but first year students only need to score 5/15 to earn 100% while higher-level students need a 12/15 to earn 100%. This prevents students from encountering less precise rubrics giving them high scores freshman year only to be blindsided by lower grades as rubrics become more discriminating. Students would see needed areas for improvement as younger students, without this penalizing their actual grade.

Each rubric category could be weighted differently to support the hierarchy of rhetorical concerns ( 16 ), with content, targeting, and interpretation being weighted higher than organization and writing quality.

Preliminary testing

Student writing samples ( Table 2 ) were collected in life science departments at two universities (Washington State University institutional review board [IRB] no. [18121-001] and Colorado State University IRB no. 20-10236H). Two coders scored each writing sample and then discussed until interrater reliability was achieved, as indicated by an intraclass correlation coefficient of >0.8 ( 17 – 19 ). We provide examples of what constituted each rubric score (see Appendix S1 in the supplemental material) and frequently asked questions (FAQs) about use of the USWR (see Appendix S2 in the supplemental material). The nonparametric Wilcoxon rank test or signed-rank test for paired samples ( 20 , 21 ) was used to compare sets of student writing samples. The Kruskal-Wallis test ( 22 ) was used for testing three levels of writing, followed by Dunn’s test ( 23 ); a P value of <0.05, adjusted for multiple comparisons, indicated significance. All statistics were calculated using R (packages in Appendix S3 in the supplemental material).

Student writing samples collected and analyzed to establish usability and validity of USWR

The USWR revealed the following statistically significant trends in student science writing.

Draft versus final versions of diverse genres of writing. Overall scoring was higher on final versions than draft versions. However, some individual students did not improve from draft to final or even received lower final scores, confirming that students likely need further training in responding to instructor or peer feedback ( 24 ).

Papers of the same genre at different levels. In our samples, students’ scientific interpretation and targeting skills increased from 200- to 400-level but did not change from 400- to 600-level ( Fig. 1A ). The higher-level samples showcased outliers; this supports observations that as students gain independence in graduate school, they still have room for improvement in science writing ( 25 ).

Papers at the same level but written to scientific versus lay audiences. We found that students struggled to interpret science for lay audiences but overall struggled to properly target a scientific audience ( Fig. 1B ). Of note, the rubrics for the original paper did not include targeting, suggesting that students write to the rubric rather than considering all aspects of quality science writing.

Lab reports submitted by students at the beginning, middle, and end of a semester. There was no significant change in scores over time. This demonstrates that a consistent rubric could facilitate the development of writing skills. The teaching assistant grading these lab reports indicated that grading rubrics were based on inclusion of particular items in each individual lab report and were not consistent from report to report, validating the data produced by the USWR.

Example data produced by USWR analysis of student science writing, highlighting statistically significant differences in interpretation and targeting. (A) Analysis of writing to a scientific audience at different levels. Students improved from the 200 level to the 400 level, but there was no difference between the 400 and 600 level. Gray bar indicates median. (B) Analysis of writing to a scientific versus a lay audience at the same level. Lines connect paired scores (from the same student). Students were better at interpreting for a scientific audience but better at targeting for a lay audience. For both panels A and B, there were no statistically significant differences between sets of samples in other rubric categories.

We also compared the USWR to grading rubrics used for several of the writing assignments collected in this study. The USWR was more discriminating (producing lower average scores and higher standard deviations) than the grading rubrics, pinpointing students who were struggling with particular skills but may have received a passing grade with a traditional rubric.

The USWR is an important tool for assessing student writing skills. While our example data is limited by small n values, we show that the USWR is usable for diverse science writing genres, sensitive enough to reveal statistically significant differences between writing samples, and valid enough to produce findings supported by the literature and instructor observations. Overall, benefits of using our USWR include better discrimination than some grading rubrics but discrimination based on important rhetorical concerns like scientific interpretation and targeting rather than surface-level grammatical features.

ACKNOWLEDGMENTS

This work was funded by startup funds provided to Nicole Kelp by Colorado State University.

We thank the instructors at two universities who facilitated collection of writing samples from students in their courses.

We declare no conflicts of interest.

Supplemental material is available online only.

• 1. Clabough EBD, Clabough SW. 2016. Using rubrics as a scientific writing instructional method in early stage undergraduate neuroscience study. J Undergrad Neurosci Educ 15:A85–A93. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 2. Szymanski EA. 2014. Instructor feedback in upper-division biology courses: moving from spelling and syntax to scientific discourse. Across the Disciplines 11:1–14. doi: 10.37514/ATD-J.2014.11.2.06. [ DOI ] [ Google Scholar ]
• 3. Hill CFC, Gouvea JS, Hammer D. 2018. Teaching assistant attention and responsiveness to student reasoning in written work. CBE Life Sci Educ 17:ar25. doi: 10.1187/cbe.17-04-0070. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 4. Cary T, Harris M, Hong S, Yin Y. 2019. Conclusion assessment rubric (CAR). Society for the Advancement of Biology Education Research, Minneapolis, MN. [ Google Scholar ]
• 5. Timmerman BEC, Strickland DC, Johnson RL, Payne JR. 2011. Development of a ‘universal’ rubric for assessing undergraduates’ scientific reasoning skills using scientific writing. Assess Eval Higher Ed 36:509–547. doi: 10.1080/02602930903540991. [ DOI ] [ Google Scholar ]
• 6. Baram-Tsabari A, Lewenstein BV. 2013. An instrument for assessing scientists’ written skills in public communication of science. Sci Commun 35:56–85. doi: 10.1177/1075547012440634. [ DOI ] [ Google Scholar ]
• 7. Stoller F, Robinson M. 2014. Drawing upon applied linguistics to attain goals in an interdisciplinary chemistry-applied linguistics project, p 11–25. In Curry MJ, Hanauer DI (ed), Language, literacy, and learning in STEM education: research methods and perspectives from applied linguistics. John Benjamins Publishing Company, Amsterdam, Netherlands. [ Google Scholar ]
• 8. Murdock RC. 2017. An instrument for assessing the public communication of scientists. PhD dissertation. Iowa State University, Digital Repository, Ames, IA. [ Google Scholar ]
• 9. Reynolds JA, Thaiss C, Katkin W, Thompson RJ. 2012. Writing-to-learn in undergraduate science education: a community-based, conceptually driven approach. CBE Life Sci Educ 11:17–25. doi: 10.1187/cbe.11-08-0064. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 10. Hand B, Wallace CW, Yang E-M. 2004. Using a science writing heuristic to enhance learning outcomes from laboratory activities in seventh‐grade science: quantitative and qualitative aspects. Int J Sci Educ 26:131–149. doi: 10.1080/0950069032000070252. [ DOI ] [ Google Scholar ]
• 11. Nisbet MC, Scheufele DA. 2009. What’s next for science communication? Promising directions and lingering distractions. Am J Bot 96:1767–1778. doi: 10.3732/ajb.0900041. [ DOI ] [ PubMed ] [ Google Scholar ]
• 12. Fischhoff B, Davis AL. 2014. Communicating scientific uncertainty. Proc Natl Acad Sci U S A 111(Suppl):13664–13671. doi: 10.1073/pnas.1317504111. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 13. Hanauer D, Curry MJ. 2014. Integrating applied linguistics and literacies within STEM education: Studies, aims theories, methods, and forms, p 1–8. In Language, literacy, and learning in STEM education: research methods and perspectives from applied linguistics. John Benjamins Publishing Company, Amsterdam, Netherlands. [ Google Scholar ]
• 14. McCarthy M. 2001. Applying linguistics: disciplines, theories, models, descriptions. In Issues in applied linguistics. Cambridge University Press, Cambridge, United Kingdom. [ Google Scholar ]
• 15. Deng Y, Kelly G, Deng S. 2019. The influences of integrating reading, peer evaluation, and discussion on undergraduate students’ scientific writing. Int J Sci Educ 41:1408–1433. doi: 10.1080/09500693.2019.1610811. [ DOI ] [ Google Scholar ]
• 16. Colorado State University Writing Center. Hierarchy of rhetorical concerns. Colorado State University, Fort Collins, CO. [ Google Scholar ]
• 17. Bartko JJ. 1966. The intraclass correlation coefficient as a measure of reliability. Psychol Rep 19:3–11. doi: 10.2466/pr0.1966.19.1.3. [ DOI ] [ PubMed ] [ Google Scholar ]
• 18. McGraw KO, Wong SP. 1996. Forming inferences about some intraclass correlation coefficients. Psych Methods 1:30–46. doi: 10.1037/1082-989X.1.1.30. [ DOI ] [ Google Scholar ]
• 19. Shrout PE, Fleiss JL. 1979. Intraclass correlations: uses in assessing rater reliability. Psych Bull 86:420–428. doi: 10.1037/0033-2909.86.2.420. [ DOI ] [ PubMed ] [ Google Scholar ]
• 20. Whitley E, Ball J. 2002. Statistics review 6: nonparametric methods. Crit Care 6:509–513. doi: 10.1186/cc1820. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 21. Wilcoxon F. 1945. Individual comparisons by ranking methods. Biometrics Bull 1:80–83. doi: 10.2307/3001968. [ DOI ] [ Google Scholar ]
• 22. Kruskal WH, Wallis WA. 1952. Use of ranks in one-criterion variance analysis. J Am Stat Assoc 47:583–621. doi: 10.1080/01621459.1952.10483441. [ DOI ] [ Google Scholar ]
• 23. Dunn OJ. 1964. Multiple comparisons using rank sums. Technometrics 6:241–252. doi: 10.1080/00401706.1964.10490181. [ DOI ] [ Google Scholar ]
• 24. Ornella Treglia M. 2008. Feedback on feedback: exploring student responses to teachers’ written commentary. J Basic Writing 27:105–137. doi: 10.37514/JBW-J.2008.27.1.06. [ DOI ] [ Google Scholar ]
• 25. Wagenmakers E-J. 2009. Teaching graduate students how to write clearly. APS Observer 22. [ Google Scholar ]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental material. Download JMBE00189-21_Supp_1_seq5.pdf, PDF file, 0.12 MB (125.4KB, pdf)

Supplemental material. Download JMBE00189-21_Supp_2_seq6.pdf, PDF file, 0.02 MB (25.9KB, pdf)

Supplemental material. Download JMBE00189-21_Supp_3_seq7.pdf, PDF file, 0.04 MB (41.8KB, pdf)

• View on publisher site
• PDF (533.8 KB)
• Collections

Similar articles

Cited by other articles, links to ncbi databases.

• Download .nbib .nbib
• Format: AMA APA MLA NLM

Add to Collections

• Communicating in STEM Disciplines
• Features of Academic STEM Writing
• STEM Writing Tips
• Academic Integrity in STEM
• Strategies for Writing
• Science Writing Videos – YouTube Channel
• Educator Resources
• Lesson Plans, Activities and Assignments
• Strategies for Teaching Writing
• Grading Techniques

Creating and Using Good Rubrics

Creating and using good rubrics can simplify the grading process for instructors and help provide general feedback on class performance on an assignment. Rubrics can also clearly outline to students what is expected for each assignment and satisfy them that their grades are being assigned objectively.

Rubrics essentially detail how marks/scores should be distributed based on the quality of each student’s completed assignment. They can be broken down into sub-sections for each assignment, but to be useful they must be detailed yet easy to understand and follow, so that different individuals using a rubric will award the same marks/scores when they grade the same student assignment.

Holistic rubrics require graders to assess the learning process as a whole without judging individual components on their own, whereas analytic rubrics operate in the opposite way; they require graders to score individual components of a student’s work on their own (e.g. different questions on an assignment) and then sum the total scores to provide one final grade 1 .

Holistic rubrics may be suitable for some writing assignments if you are happy for students to make errors in individual components providing their final product is still of high quality (e.g. perhaps a few grammatical errors are tolerable when the main learning objective is to research the literature and present a content-heavy essay that is supported by the literature).

Generally, analytic rubrics are preferred when a relatively focused response is required (e.g. when you want to assess student writing ability based on grammar, punctuation and mechanics, structure, content, logic, and use of sources, or if there are many individual tasks that students need to complete in one assignment). Whether you use a holistic or analytic rubric should depend on the assignment and associated learning goals 2 .

Creating a Rubric

Each rubric will differ based on the assignment you ask your students to complete, but you should focus on the specific learning objectives you wish students to develop 3 . Think about the observable attributes you want to see from them, as well as those that you don’t.

If you are creating a rubric for an existing assignment that has been used in past offerings of the course, it may be useful to re-read some of those assignments to gain a perspective of the typical spectrum of answers that students provided; it is helpful to predict the kind of answers you expect to see when designing a rubric to cover as many of these as possible, as well as keeping in mind what students must typically show in their assignments to achieve low, middle and high grades.

When creating rubrics (particularly if they are holistic), it is helpful to divide each criterion into levels, such that you create categories that relate to different responses that reflect the progression from novice to expert-like writing (e.g. a score of 1 might represent emerging ability, whereas a score of 5 might represent the quality of an expert.

Defining these categories can be useful for students who wish to monitor their learning progress, especially because the scores/marks will not represent linear progression (e.g. a student who scores 4 out of 5 for logical development does not mean that student has twice as much ability as one who scores 2 out of 5).

If you are creating a rubric for a new assignment, you should keep the following tips in mind:

1. First divide the total marks for the assignment into different sections (e.g. five marks for the depth of content, five for the quality of sources used, five for integration of these sources, five for quality of argument, and five for paragraph structure and transitions). Note that most rubrics focus on six to seven criteria 4 , but the absolute number should depend on what the assignment 5 asks of students; in most cases, limiting the number of criteria is more practical, but sufficient scope should exist within these criteria to distinguish the full range of likely student abilities.

2. Provide a detailed explanation of what an answer would need to show to be awarded any mark/score within the range available for each section (e.g. if you have allocated up to five marks for the depth of content, you should clearly state what a student must cover to gain one, two, three, four and five marks).

3. Do not use potentially ambiguous explanations. For example, do not propose a scale of 0 – 3 marks where weak, fair, good and very good are the descriptors used to differentiate between scores of 0, 1, 2, and 3 because different graders will likely differ on their interpretation of what is weak, fair, good or very good. Instead, try to provide objective definitions (e.g. less than one primary source = 0, one or two primary sources = 1…). If your rubric is holistic rather than analytic, you should provide detailed summaries (with examples) to clearly distinguish between marks/scores.

4. Add a qualitative description to each of these marks/scores if you plan to share the rubrics with students at any stage, so that they can assess their own learning development based on the grade they receive for the assignment.

5. Share the rubric with colleagues and TAs and ask for feedback. Expect to make changes based on this feedback.

6. If you plan to share the rubrics with students, ask these same students whether it is clear to them before the assignment begins. If they misinterpret any part of it, this may be a sign that you should make changes.

By following the above steps, you should design rubrics that are straightforward and objective to use. However, when more than one person will grade the assignments, it is important for all graders (e.g. instructors and TAs) to meet to troubleshoot any issues at an early stage. Ensuring your graders can use your rubric objectively is a crucial part of the design process, which is why the following steps are very important before you grade the assignments from an entire class:

7. Try to select a range of assignments from students of varying abilities and then take turns to grade each one using the rubric.

8. Compare the grades you each assigned the same assignments and calculate your inter-rater reliability (see below).

9. If you have a low reliability (e.g. you have awarded different grades to the same assignments), this indicates issues with the rubric or the way it is being interpreted.

10. In such a scenario, work through each section and pinpoint where – and why – graders have awarded different scores based on the rubric, and then rephrase the rubric to make it more objective.

11. Grade a new set of assignments in the same way before comparing grades until you are satisfied that your inter-rater reliability is sufficiently high, and you are confident that you are all using the rubric in the same way.

Inter-Rater Reliability

Calculating inter-rater reliability (IRR) provides an estimate of the degree of agreement between different graders using the same rubric. A well designed, objective rubric should result in a high IRR (approaching 1), whereas a poorly designed, ambiguous one will result in a low IRR (approaching 0 or –1, depending on your method).

All graders who will be grading assignments using your rubric should take part in IRR assessments; if they do not, the IRR estimate you obtain will not encompass data from everyone whose interpretations will provide the final grades. As a result, the rubric may not be effectively assessed before it is used to grade the assignments of a whole class.

There are various techniques for providing IRR estimates, and the best one to use depends on the situation 6 . When you obtain data from three or more coders, it is generally best to use an extension of Scott’s Pi statistic 7 , or compute the arithmetic mean of kappa 8 (a statistic used in IRR analysis 9 ). There are no cast-iron guidelines for an acceptable level of agreement, but popular benchmarks for high agreement using kappa are 0.75 10 and 0.8 11 . Hallgren 6 provides a detailed overview of these procedures.

Using a Rubric to Provide Feedback

You can save time when providing assignment feedback to large classes by referring to the rubric when highlighting example student answers, and then explaining how/why they were scored/marked as they were. By showing a spectrum of answers, you can also indicate to students how they must approach similar questions in future to attain high scores/marks.

Depending on the situation, you may also wish to provide a marked rubric with each student’s assignment, so that they can see how they have been assessed on each question 12 . This can be very useful for students, and can again save you time in providing feedback in large classes as it can reduce the need to write explanations to justify scores/marks throughout.

Sample Rubrics and Useful Links

In addition, we encourage interested instructors to contact us to obtain access to some example rubrics created by the ScWRL team.  Please fill out the Access Request and Feedback Form and then, once you have been granted access, input your password at the suggested solutions password protected page .

Resource Download

Useful References

1: Nitko AJ. Educational assessment of students. 3 rd ed. Upper Saddle River, NJ: Merrill. 2001.

2: De Leeuw J. Rubrics and Exemplars in Writing Assessment. In: Scott S, Scott DE, Webber CF, editors. Leadership of Assessment, Inclusion, and Learning. Switzerland: Springer International Publishing; 2016. p.89-110.

3: Mertler CA. Designing Scoring Rubrics for Your Classroom. Pract Assess, Res & Eval. 2001; 7(25).

4: Andrade HG, Wang X, Du Y and Akawi RL. Rubric-referenced self-assessment and self-efficacy for writing. J Educ Res. 2009; 102:287-301.

5: Covill, AE. College Students’ Use of a Writing Rubric: Effect on Quality of Writing, Self-Efficacy, and Writing Practices. J Writ Assess. 2012; 5(1).

6: Hallgren KA. Computing Inter-Rater Reliability for Observational Data: An Overview and Tutorial. Tutor Quant Methods Psychol. 2012; 8(1):23-34.

7: Scott WA. Reliability of content analysis: The case of nominal scale coding. Public Opinion Quarterly. 1955; 19(3):321-325.

8: Davies M, Fleiss JL. Measuring agreement for multinomial data. Biometrics. 1982; 38(4):1047-1051.

9: Cohen J. A coefficient of agreement for nominal scales. Educ and Psych Measurement. 1960; 20(1): 37-46.

10: Fleiss JL. Statistical methods for rates and proportions. 2 nd ed. New York: John Wiley. 1981.

11: Altman D. Practical statistics for medical research. Boca Raton, FL: CRC Press. 1991.

12: Huba ME, Freed JE. Learner-Centred Assessment on College Campuses. Boston: Allyn & Bacon. 2000.