IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0037719.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0037719
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0037719&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0037719?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Noussair, C.N. & Tucker, S. & Xu, Yilong, 2014. "A Future Market Reduces Bubbles but Allows Greater Profit for More Sophisticated Traders," Other publications TiSEM 43ded173-9eee-48a4-8a15-6, Tilburg University, School of Economics and Management.
    2. Jonathan Donier & Jean-Philippe Bouchaud, 2015. "Why Do Markets Crash? Bitcoin Data Offers Unprecedented Insights," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-11, October.
    3. Benjamin Enke & Florian Zimmermann, 2019. "Correlation Neglect in Belief Formation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(1), pages 313-332.
    4. Lange, Andreas & Ross, Johannes, 2024. "Internalizing match-dependent externalities," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 356-378.
    5. Nuzzo, Simone & Morone, Andrea, 2017. "Asset markets in the lab: A literature review," Journal of Behavioral and Experimental Finance, Elsevier, vol. 13(C), pages 42-50.
    6. Brock, William A. & Hommes, Cars H. & Wagener, Florian O. O., 2005. "Evolutionary dynamics in markets with many trader types," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 7-42, February.
    7. Cars Hommes & Anita Kopányi-Peuker & Joep Sonnemans, 2021. "Bubbles, crashes and information contagion in large-group asset market experiments," Experimental Economics, Springer;Economic Science Association, vol. 24(2), pages 414-433, June.
    8. Marco Lambrecht & Andis Sofianos & Yilong Xu, 2025. "Does Mining Fuel Bubbles? An Experimental Study on Cryptocurrency Markets," Management Science, INFORMS, vol. 71(3), pages 1865-1888, March.
    9. Marco Angrisani & Marco Cipriani & Antonio Guarino, 2022. "Strategic Sophistication and Trading Profits: An Experiment with Professional Traders," Staff Reports 1044, Federal Reserve Bank of New York.
    10. Lorenzo Cominelli & Gianluca Rho & Caterina Giannetti & Federico Cozzi & Alberto Greco & Graziano A. Manduzio & Philipp Chapkovski & Michalis Drouvelis & Enzo Pasquale Scilingo, 2024. "Emotions in hybrid financial markets," Discussion Papers 2024/311, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    11. Hauser, Florian & Huber, Jürgen, 2012. "Short-selling constraints as cause for price distortions: An experimental study," Journal of International Money and Finance, Elsevier, vol. 31(5), pages 1279-1298.
    12. Draganac, Dragana & Lu, Kelin, 2025. "Pricing asset beyond financial fundamentals: The impact of prosocial preference and image concerns," Journal of Economic Dynamics and Control, Elsevier, vol. 170(C).
    13. Allain, Marie-Laure & Chambolle, Claire & Rey, Patrick & Teyssier, Sabrina, 2021. "Vertical integration as a source of hold-up: An experiment," European Economic Review, Elsevier, vol. 137(C).
    14. Nathalie Colombier & Laurent Denant Boemont & Youenn Loheac & David Masclet, 2008. "Risk aversion: an experiment with self-employed workers and salaried workers," Applied Economics Letters, Taylor & Francis Journals, vol. 15(10), pages 791-795.
    15. Huan Xie & Jipeng Zhang, 2016. "Bubbles and experience: An experiment with a steady inflow of new traders," Southern Economic Journal, John Wiley & Sons, vol. 82(4), pages 1349-1373, April.
    16. Quemin, Simon & Trotignon, Raphaël, 2021. "Emissions trading with rolling horizons," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
    17. Simon Cornée & David Masclet & Gervais Thenet, 2012. "Credit Relationships: Evidence from Experiments with Real Bankers," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(5), pages 957-980, August.
    18. Tiziana Assenza & Te Bao & Cars Hommes & Domenico Massaro, 2014. "Experiments on Expectations in Macroeconomics and Finance," Research in Experimental Economics, in: Experiments in Macroeconomics, volume 17, pages 11-70, Emerald Group Publishing Limited.
    19. Jonathan Donier & Jean-Philippe Bouchaud, 2015. "Why Do Markets Crash? Bitcoin Data Offers Unprecedented Insights," Post-Print hal-01277584, HAL.
    20. Omar Al-Ubaydli & John List, 2016. "Field Experiments in Markets," Artefactual Field Experiments j0002, The Field Experiments Website.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0037719. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.