Computer-Based Feedback and Its Effects on Learning and Motivation: A Network Meta-Analysis

• In Event: Antecedents and Outcomes of Motivation Within Digital Environments

Abstract

Providing feedback is simple in computer-based testing environments and can support student learning. But what type of feedback is most effective for enhancing student performance and motivation? In this meta-analysis, we present a novel network-analysis approach that allowed to rank four common feedback types regarding their effects on performance and motivational outcomes. Specifically, 184 effect sizes from 73 experimental studies allowed us to compare knowledge of results, knowledge of correct response, elaborated feedback, and answer-until-correct feedback with a no feedback control group. Elaborated feedback was the most effective feedback type to improve recall and transfer task performance as well as test-taking motivation compared to the other feedback types. Subgroup analyses identified moderating factors for the effectiveness of different feedback interventions.

Authors

• Ute Mertens, Leibniz Institute for Science and Mathematics Education

• Bridgid Finn, Educational Testing Service

• Marlit Annalena Lindner, IPN - Leibniz Institute for Science and Mathematics Education