Pilot study: Longitudinal analysis of peer feedback in a writing-intensive course
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This pilot study examines the impact of peer feedback on writing across multiple essays in a longitudinal analysis involving first-year students at the University of British Columbia. It explores the use, effectiveness, and quality of peer feedback over time, finding little evidence of significant improvements or changes in comment quality after multiple sessions. The research indicates that while peer feedback is utilized, it does not necessarily result in enhanced writing performance or comment quality in the long run.
Pilot study: Longitudinal analysis of peer feedback in a writing-intensive course
- 1. Longitudinal Analysis of Peer Feedback in a Writing-Intensive Course: A Pilot Study PI: Christina Hendricks Co-PI: Jeremy Biesanz University of British Columbia-Vancouver Funded by the UBC Institute for the Scholarship of Teaching and Learning SoTL Seed Fund Festival of Learning, June 2016 Slides licensed CC-BY 4.0
- 2. Literature on peer feedback Receiving peer feedback improves writing (Paulus, 1999; Cho & Schunn, 2007; Cho & MacArthur, 2010; Crossman & Kite, 2012) Giving peer feedback improves writing (Cho & Cho, 2011; Li, Liu & Steckelberg, 2010)
- 3. GAPS: Most studies look at revisions to a single essay, not changes across different essays Draft 1 Draft 2 Draft 3 Essay 1 Essay 2 Essay 3 Essay 4 Essay …n PFB PF B PF B PFB PF B PFB Few studies look at “dose-response curve”
- 4. Pilot study research questions 1. How do students use peer comments given and received for improving different essays rather than drafts of the same essay? 1. Are students more likely to use peer comments given and received for improving their writing after more than one or two peer feedback sessions? How many sessions are optimal? 2. Does the quality of peer comments improve over time?
- 5. • Interdisciplinary, full year course for first-years • 18 credits (English, History, Philosophy) • Students write 10-12 essays (1500-2000 words) • Peer feedback tutorials every week (4 students) http://artsone.arts.ubc.ca Toni Morrison, Wikimedia Commons, licensed CC BY-SA 2.0 Osamu Tezuka, public domain on Wikimedia Commons Jane Austen, public domain on Wikimedia Commons Friedrich Nietzsche, public domain, Wikimedia Commons
- 6. Data for pilot study 2013-2014 • 10 essays by 12 participants (n=120) • Comments by 3 peers on essays (n=1218) • Comments by instructor (n=3291) • All coded with same rubric
- 7. Coding Rubric Categories (plus subcategories, for 11 options) • Strength of argument • Organization • Insight • Style & Mechanics Numerical value 1: Significant problem 2: Moderate problem 3: Positive comment/praise E.g., STREV 2: could use more textual evidence to support your claims Change for future
- 8. Inter-coder reliability Fleiss’ Kappa Intra-class correlation Student comments (n=141) All categories: 0.61 (moderate) Most used categories: 0.8 (excellent) 0.96 (excellent) Essays (n=120) 0.71 (adequate) 3 coders: • Daniel Munro & Kosta Prodanovic (undergrads, former Arts One) • Jessica Stewart (author, editor) Change for future
- 9. LOOKING AT TRENDS IN COMMENTS OVER TIME
- 10. 0 2 4 6 8 10 12 024681012 Essay Number InstructorNumberofComments Argument Strength Style Insight Organization INSTRUCTOR Comments - .28**Strength Style Organiz. Insight -.04* Number of 2 comments over time
- 11. 0 2 4 6 8 10 12 01234 Essay Number StudentNumberofComments Argument Strength Style Insight Organization STUDENT comments Strength Style Organiz. Insight -.16** Number of 2 comments over time
- 12. 0 2 4 6 8 10 12 012345 Essay Number InstructorNumberofComments Argument Strength Style Insight Organization INSTRUCTOR Comments .31*** Strength Style Organiz. Insight .08** .19** .11** Number of 3 comments
- 13. 0 2 4 6 8 10 12 0.00.51.01.52.02.53.0 Essay Number StudentNumberofComments Argument Strength Style Insight Organization STUDENT Comments Strength Style Organiz. Insight Number of 3 comments over time
- 14. HOW DOES ESSAY QUALITY CHANGE OVER TIME?
- 15. Essay quality improves linearly b = .038 t(107) = 2.1 p = .037 Essays rated on a 7-point scale
- 17. Cross-lagged panel design with auto-regressive structure Essay Quality Time 1 Essay Quality Time 2 Comments Time 1 Comments Time 2 B A C D E … N … N
- 18. Path A: Instructor Comments Essay Quality Time 1 Essay Quality Time 2 Comments Time 1 Comments Time 2 B A C D E … N … N Significant relationships • Ratings of 1 in Strength (-.12*) & Org. (-.23**) • Ratings of 2 in Strength (-.06*) & Style (-.08*) • Ratings of 3 in Str, (.11*), Insight (.35*), Style (.15*) *p < .05, **p< .01, ***p< .001, ****p < .0001 *****p <.00001
- 19. Path A: Student comments Essay Quality Time 1 Essay Quality Time 2 Comments Time 1 Comments Time 2 B A C D E … N … N Significant relationships • Ratings of 2 in Insight (-.53*) • Ratings of 3 in Organization (.13*) *p < .05, **p< .01, ***p< .001, ****p < .0001 *****p <.00001
- 20. Path C: instructor comments Essay Quality Time 1 Essay Quality Time 2 Comments Time 1 Comments Time 2 B A C D E … N … N Significant effects don’t show up if split out by category • Comments ratings of 1 (.29**) • Comments ratings of 2 (.23*) • Comments ratings of 3 (.21, p=.057) *p < .05, **p< .01, ***p< .001, ****p < .0001 *****p <.00001
- 21. Path C: instructor comments Essay Quality Time 1 Essay Quality Time 2 Comments Time 1 Comments Time 2 B A C D E … N … N Significant effects: • Rating of 3 in Strength (.34**) and Style (.30**) *p < .05, **p< .01, ***p< .001, ****p < .0001 *****p <.00001
- 22. Path C: student comments Essay Quality Time 1 Essay Quality Time 2 Comments Time 1 Comments Time 2 B A C D E … N … N Significant relationships • Comments rated 2 in Strength (.22*) & Style (.33**) • Comments rated 3 in Style (.31*) *p < .05, **p< .01, ***p< .001, ****p < .0001 *****p <.00001
- 23. Path D: Student & Instructor comments Essay Quality Time 1 Essay Quality Time 2 Comments Time 1 Comments Time 2 B A C D E … N … N Significant relationship ONLY if combine student & instructor comments, & only for comments rated 1 (all categories combined): (.05, p=.06)
- 24. Research question 1 How do students use peer comments given and received for improving different essays rather than drafts of same essay? o Very little significant evidence of relationships in Path D o No difference between comments given & received
- 25. Research question 2 Are students more likely to use peer comments given and received for improving their writing after more than one or two peer feedback sessions? How many sessions are optimal? o No evidence that there is any change over time in path D o No difference between comments given or received
- 26. Research question 3 Does the quality of peer comments improve over time? o No evidence of change over time in path A Essay Quality Time 1 Essay Quality Time 2 Comments Time 1 Comments Time 2 B A C D E … N … N
- 27. Research Question 3, cont’d Student/instructor agreement on average numerical ratings on each essay • tends to go down over time (-.04**) • student ratings increase at only half the rate (.16*) that instructor’s ratings increase (.33*****) *p < .05, **p< .01, ***p< .001, ****p < .0001 *****p <.00001
- 28. Research Question 3, cont’d Correlations on number of comments, students & instructor • No change in these relationships over time *p < .05, **p< .01, ***p< .001, ****p < .0001 *****p <.00001 Comment value 1 Comment value 2 Comment value 3 Strength 0.23* Organization 0.21* 0.17* Insight 0.17* Style
- 29. Some conclusions Pilot study: feasible for larger sample? Yes, if: o instructors code essay quality rather than coders o “chunk” essays for cross-lagged analyses o have easy collection of comments
- 30. References • Cho, K., & MacArthur, C. (2010). Student revision with peer and expert reviewing, Learning and Instruction. 20, 328-338. • Cho, Y. H., & Cho, K. (2011). Peer reviewers learn from giving comments. Instructional Science, 39, 629-643. • Cho, K. & Schunn, C. D. (2007). Scaffolded writing and rewriting in the discipline: A web-based reciprocal peer review system. Computers & Education, 48, 409–426 • Crossman, J. M., & Kite, S. L. (2012). Facilitating improved writing among students through directed peer review, Active Learning in Higher Education, 13, 219-229. • Li, L., Liu, X., & Steckelberg, A. L. (2010). Assessor or assessee: How student learning improves by giving and receiving peer feedback. British Journal of Educational Technology, 41(3), 525–536. • Paulus, T. M. (1999). The effect of peer and teacher feedback on student writing. Journal of Second Language Writing, 8, 265-289.
- 31. Thank you! Christina Hendricks University of British Columbia-Vancouver Website: http://blogs.ubc.ca/christinahendricks Blog: http://blogs.ubc.ca/chendricks Twitter: @clhendricksbc Slides available: https://is.gd/PeerFeedbackPilot_FOL16 Slides licensed CC-BY 4.0 Capitals needed underscore
Editor's Notes
- #8: Number of “1” comments total: 239 out of over 4000 1’s by students: 35 1’s by instructor: 204
- #9: How much agreement do we observe relative to how much we would expect to see by chance? -- takes into account the frequency of the type of code occurring in the data -- some codes are more frequent, so you’d expect those to have more apparent agreement -1 to +1 0 = amount of agreement we’d expect to see by chance -1 is complete disagreement 0.6 is moderate agreement; 0.8 is substantial -- Kappa includes just the category Many of the mostly used categories have agreement in 0.8 range Reliability on degree: intra class correlation (ICC) of 0.96 -- to what extent is the average across the three raters reliable: average of all the numbers each gave—how does this correlate with the average of everyone who could possibly do this—get no benefit for adding more people -- average is 2.5 -- 1’s are pretty infrequent -- people agree on whether a 2 or a 3 (40% are 2s, 60% are 3s)
- #13: These numbers are linear trend over time, not autoregressive
- #19: What this says, basically, is that the coders’ ratings of essay quality are pretty similar to the instructor’s comments on essay quality, in these categories at least
- #22: But see notes—there are some significant effects in C in instructor comments of 3 in strength and style I think the above numbers are actually for path B, not path C
- #23: This could just be saying that students tend to give the same sorts of comments to the same people, but also that things aren’t changing that much from one essay to another.
- #29: No change in this over time, though