Data Repository for: Explore, Exploit, and Prune in the Classroom: Strategic Resource Management Behaviors Predict Performance

Version
V0
Resource Type
Dataset
Creator
  • Chen, Patricia (National University of Singapore)
  • Ong, Desmond (National University of Singapore)
  • Ng, Jessica (National University of Singapore)
  • Coppola, Brian (University of Michigan)
Publication Date
2020-11-24
Description
  • Abstract

    [This is a data repository for a paper accepted at AERA Open.]

    Self-regulated learners strategically manage physical, technological, online, and social resources for learning—by selecting resources that could be useful, reflecting on how useful these resources have been, and adjusting resource use accordingly. We propose a model that conceptualizes resource management as learners’ intentional, self-reflective decisions to explore new resources, exploit (continue to use) previously useful resources, and prune (stop using) previously ineffective resources. We modeled 4,766 students’ reported exploration, exploitation, and pruning between three class exams among four cohorts of an Organic Chemistry class (i.e., over 100,000 discrete data points of resource use). Each of these behavioral mechanisms of resource management predicted students’ academic achievement: The more students reported exploring, exploiting, and pruning between their exams, the higher they performed on their subsequent exams, controlling for prior performance. These findings enrich self-regulated learning theories by concretizing the behavioral mechanisms of resource management by which learners take control of their learning.
Availability
Download
This study is freely available to the general public via web download.
Relations
  • Has version
    DOI: 10.3886/E127301V1

Update Metadata: 2020-11-24 | Issue Number: 1 | Registration Date: 2020-11-24