Redesigning educational peer review interactions using computer tools: An introduction

Journal of Writing Research

Volumn 4, Issue 2, 2012, Pages 111-119

  Goldin, Ilya M ^a,b   Ashley, Kevin D ^a,b   Schunn, Christian D ^a,b  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b UNIVERSITY OF PITTSBURGH   (United States)

Author keywords

Peer review; Technology enhanced learning

Indexed keywords

EID: 84875262244     PISSN: 20301006     EISSN: 22943307     Source Type: Journal    
DOI: 10.17239/jowr-2012.04.02.1     Document Type: Article

References (37)

1. Armstrong, S. L., & Paulson, E. J. (2008). Whither "Peer Review"? Terminology Matters for the Writing Classroom. Teaching English in the Two-Year College, 35(4), 398-407.
2. Bruffee, K. (1984). Peer tutoring and the "convesation of mankind." Writing centers: Theory and administration, 3-15.
3. Cho, K. (2008). Machine classification of peer comments in physics. In R. S. J. de Baker, T. Barnes, & J. E. Beck (Eds.), Proceedings of the 1st International Conference on Educational Data Mining (pp. 192-196). Presented at the Educational Data Mining, Montreal, Canada.
4. Cho, K., & Schunn, C. D. (2007). Scaffolded writing and rewriting in the discipline: A web-based reciprocal peer review system. Computers and Education, 48(3), 409-426. doi:10.1016/j.compedu.2005.02.004
5. Cho, K., Schunn, C. D., & Kwon, K. (2007). Learning writing by reviewing in science. 8th International conference on computer-supported collaborative learning (pp. 141-143). New
6. Brunswick, NJ, USA: International Society of the Learning Sciences. Retrieved from http://portal.acm.org/citation.cfm?id=1599600.1599626
7. Cho, K., Schunn, C. D., & Wilson, R. W. (2006). Validity and reliability of scaffolded peer assessment of writing from instructor and student perspectives. Journal of Educational Psychology, 98(4), 891-901. doi:10.1037/0022-0663.98.4.891
8. Crespo García, R. M., Pardo, A., & Delgado Kloos, C. (2006). Adaptive Peer Review Based on Student Profiles. In M. Ikeda, K. Ashley, & T.-W. Chan (Eds.), Intelligent Tutoring Systems, Lecture Notes in Computer Science (Vol. 4053, pp. 781-783). Springer Berlin / Heidelberg. doi:10.1007/11774303_99
9. Crinon, J. (2012). The dynamics of writing and peer review at primary school. Journal of Writing Research, 4(2).121-154.
10. Elbow, P. (2000). Everyone can write: Essays toward a hopeful theory of writing and teaching writing. Oxford University Press, USA.
11. Gehringer, E. F. (2000). Strategies and mechanisms for electronic peer review. 30th Annual Frontiers in Education Conference (Vol. 1, pp. F1B/2-F1B/7 vol.1). Presented at the 30th Annual Frontiers in Education Conference. doi:10.1109/FIE.2000.897675
12. Gehringer, E. F., Gummadi, A., Kadanjoth, R., & Andrés, Y. M. (2010). Motivating effective peer review with extra credit and leaderboards. Proceedings of the 2010 American Society for Engineering Education Annual Conference & Exposition.
13. Gielen, S., Dochy, F., & Onghena, P. (2010). An inventory of peer assessment diversity. Assessment & Evaluation in Higher Education, 36(2), 137-155. doi:10.1080/02602930903221444
14. Goldin, I. M. (2012). Accounting for Peer Reviewer Bias with Bayesian Models. Proceedings of the Workshop on Intelligent Support for Learning Groups at the 11th International Conference on Intelligent Tutoring Systems. Chania, Greece.
15. Goldin, I. M., & Ashley, K. D. (2012). Eliciting formative assessment in peer review. Journal of Writing Research, 4(2), 203-237.
16. Gouli, E. (2006). Supporting Self- Peer- and Collaborative-Assessment through a Web-based Environment. World Conference on Educational Multimedia, Hypermedia and Telecommunications (p. 2192). Presented at the EDMEDIA.
17. Hamer, J., Kell, C., & Spence, F. (2007). Peer assessment using Aropä. Proceedings of the 9th Australasian Conference on Computing Education (Vol. 66, pp. 43-54). Ballarat, Victoria, Australia: Australian Computer Society, Inc.
18. Hamer, J., Ma, K. T. K., & Kwong, H. H. F. (2005). A method of automatic grade calibration in peer assessment. Proceedings of the 7th Australasian Conference on Computing Education (Vol. 42, pp. 67-72). Newcastle, New South Wales, Australia: Australian Computer Society, Inc.
19. Hillocks Jr, G. (1986). Research on Written Composition: New Directions for Teaching. National Council of Teachers of English, 1111 Kenyon Rd., Urbana, IL 61801 (Stock No. 40750, $19.00 member, $24.75 nonmember). Retrieved from http://www.eric.ed.gov/ERICWebPortal/detail?accno=ED265552
20. Hinds, P. J., & Kiesler, S. (Eds.). (2002). Distributed Work (1st ed.). The MIT Press.
21. Hsiao, I.-H., & Brusilovsky, P. (2008). Modeling peer review in example annotation. 16th International Conference on Computers in Education (pp. 357-362). Presented at the 16th International Conference on Computers in Education, Taipei, Taiwan.
22. Lauw, H. W., Lim, E., & Wang, K. (2007). Summarizing review scores of "unequal" reviewers. Proceedings of the 7th SIAM International Conference on Data Mining (pp. 539-544).
23. Leijen, D. A. J., & Leontjeva, A. (2012). Linguistic and review features of peer feedback and their effect on the implementation of changes in academic writing: A corpus based investigation. Journal of Writing Research, 4(2), 178-202.
24. Li, L., & Kay, J. (2005). Assess: Promoting Learner Reflection in Student Self-Assessment. Workshop on Learner Modelling for Reflection, to Support Learner Control, Metacognition and Improved Communication between Teachers and Learners at 12th International Conference on Artificial Intelligence in Education (pp. 32-41). Amsterdam.
25. Lu, R., & Bol, L. (2007). A comparison of anonymous versus identifiable e-peer review on college student writing performance and the extent of critical feedback. Journal of Interactive Online Learning, 6(2), 100-115.
26. Masters, J., Madhyastha, T., & Shakouri, A. (2008). ExplaNet: A collaborative learning tool and hybrid recommender system for student-authored explanations. Journal of Interactive Learning Research, 19(1), 51-74.
27. Miller, P. J. (2003). The effect of scoring criteria specificity on peer and self-assessment. Assessment & Evaluation in Higher Education, 28(4), 383-94. doi:10.1080/0260293032000066218
28. Neuwirth, C. M., Chandhok, R., Charney, D., Wojahn, P., & Kim, L. (1994). Distributed collaborative writing: a comparison of spoken and written modalities for reviewing and revising documents. Proceedings of the SIGCHI conference on Human factors in computing systems: celebrating interdependence, CHI '94 (pp. 51-57). New York, NY, USA: ACM. doi:10.1145/191666.191693
29. Ramachandran, L., & Gehringer, E. F. (2010). Automated Metareviewing. Proceedings of the Workshop on Computer-Supported Peer Review in Education, ITS 2010. Pittsburgh, PA.
30. Russell, A. A. (2004). Calibrated Peer Review: A writing and critical thinking instructional tool. Invention and Impact: Building Excellence in Undergraduate Science, Technology, Engineering and Mathematics (STEM) Education. American Association for the Advancement of Science.
31. Scardamalia, M., & Bereiter, C. (1994). Computer Support for Knowledge-Building Communities. Journal of the Learning Sciences, 3(3), 265-283. doi:10.1207/s15327809jls0303_3
32. Webb, N. M., Nemer, K. M., & Zuniga, S. (2002). Short circuits or superconductors? Effects of group composition on high-achieving students' science assessment performance. American Educational Research Journal, 39(4), 943.
33. Weber, G., & Brusilovsky, P. (2001). ELM-ART: An adaptive versatile system for Web-based instruction. International Journal of Artificial Intelligence in Education, 12(4), 351-384.
34. Wooley, R., Was, C. A., Schunn, C. D., & Dalton, D. W. (2008). The effects of feedback elaboration on the giver of feedback. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), 30th Annual Conference of the Cognitive Science Society (pp. 2375-2380). Presented at the 30th Annual Conference of the Cognitive Science Society, Washington, DC: Cognitive Science Society.
35. Xiong, W., Litman, D., & Schunn, C. D. (2010). Assessing Reviewers' Performance Based on Mining Problem Localization in Peer-Review Data. In R. S. J. d. Baker, A. Merceron, & P. I. J. Pavlik (Eds.), 3rd International Conference on Educational Data Mining. Pittsburgh, PA.
36. Xiong, W., Litman, D., & Schunn, C. D. (2012). Toward improving the quality of peer feedback through Natural Language Processing. Journal of Writing Research, 4(2).155-176.
37. Zeller, A. (2000). Making students read and review code. SIGCSE Bull., 32(3), 89-92. doi:10.1145/353519.343090