Title:	STATISTICAL TOOLS TO ENHANCE PEER-REVIEW PROCESSES IN LARGE GROUPS
Author(s):	Joan Codina , Josep M. Fontana
ISBN:	972-8924-22-4
Editors:	Kinshuk, Demetrios G Sampson, J. Michael Spector and Pedro Isaías
Year:	2006
Edition:	Single
Keywords:	peer-to-peer review, assessment, LMS, collaborative learning
Type:	Short Paper
First Page:	313
Last Page:	316
Language:	English
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Paper Abstract:	The use of peer-review methods in the evaluation of students’ work is becoming increasingly popular due mainly to pedagogical considerations. This paper argues for the integration of several statistical techniques in the peer-review process that would increase the efficiency and reliability of this process by providing the teacher with tools that make the necessary supervision task less daunting and more productive. Crucially, the model proposed here makes it possible for students to be not only evaluated by the quality of their work but also by the quality of their evaluation of the work of their peers. The statistical tools are intended to minimize the need for direct intervention on the part of the teacher by establishing a ranking of reviewers according to their reliability and quickly identifying significant discrepancies in the evaluation of specific assignments. The system thus allows the teacher to be able to focus his/her attention on the subset of assignments whose evaluation has been signaled as problematic. This is especially useful in courses with large groups of students where the evaluation of assignments can be enormously tedious and labour intensive. This approach allows computers to play a more useful role in the continuous assessment of the student’s work, restricted until now mainly to certain types of activities such as cloze tests or multiple-choice quizzes whose pedagogical value and possibilities are rather limited. The work presented here is intended as a preliminary proposal before its implementation in an LMS for further testing and improvement.
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