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Does Reviewing Lead to Better Learning and Decision Making? Answers from a Randomized Stock Market Experiment

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  • Patrick Wessa
  • Ian E Holliday

Abstract

Background: The literature is not univocal about the effects of Peer Review (PR) within the context of constructivist learning. Due to the predominant focus on using PR as an assessment tool, rather than a constructivist learning activity, and because most studies implicitly assume that the benefits of PR are limited to the reviewee, little is known about the effects upon students who are required to review their peers. Much of the theoretical debate in the literature is focused on explaining how and why constructivist learning is beneficial. At the same time these discussions are marked by an underlying presupposition of a causal relationship between reviewing and deep learning. Objectives: The purpose of the study is to investigate whether the writing of PR feedback causes students to benefit in terms of: perceived utility about statistics, actual use of statistics, better understanding of statistical concepts and associated methods, changed attitudes towards market risks, and outcomes of decisions that were made. Methods: We conducted a randomized experiment, assigning students randomly to receive PR or non–PR treatments and used two cohorts with a different time span. The paper discusses the experimental design and all the software components that we used to support the learning process: Reproducible Computing technology which allows students to reproduce or re–use statistical results from peers, Collaborative PR, and an AI–enhanced Stock Market Engine. Results: The results establish that the writing of PR feedback messages causes students to experience benefits in terms of Behavior, Non–Rote Learning, and Attitudes, provided the sequence of PR activities are maintained for a period that is sufficiently long.

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  • Patrick Wessa & Ian E Holliday, 2012. "Does Reviewing Lead to Better Learning and Decision Making? Answers from a Randomized Stock Market Experiment," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-14, May.
    • Handle: RePEc:plo:pone00:0037719
    DOI: 10.1371/journal.pone.0037719
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    References listed on IDEAS

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    1. Patrick Wessa, 2009. "A framework for statistical software development, maintenance, and publishing within an open-access business model," Computational Statistics, Springer, vol. 24(2), pages 183-193, May.
    2. Smith, Vernon L & Suchanek, Gerry L & Williams, Arlington W, 1988. "Bubbles, Crashes, and Endogenous Expectations in Experimental Spot Asset Markets," Econometrica, Econometric Society, vol. 56(5), pages 1119-1151, September.
    3. Patrick Wessa & Antoon De Rycker & Ian Edward Holliday, 2011. "Content-Based VLE Designs Improve Learning Efficiency in Constructivist Statistics Education," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-15, October.
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