Conditions and Factors Moderating Mobile-Assisted Language Learning: A Meta-Analysis

• In Event: Fairmont Roundtable Session Seven
  In Roundtable Session: Systematic Review and Meta-Analysis SIG Roundtable (Table 9)

Abstract

This meta-analysis synthesized 71 studies between 2009 and 2022 to comparatively examine the efficacy of three Mobile-Assisted Language Learning conditions. Condition 1—mobile devices vs. desktop computers learning¬—had a large overall effect size of g = 0.98. Condition 2— mobile devices vs. mobile devices minus experimental feature learning—had a medium effect size of g = 0.45. Condition 3—mobile devices vs. paper-based learning—had a large effect size of g = 0.92. Moderator analyses showed that application type, assessment type, and target language moderated the effect sizes in all conditions. However, the significance of the other nine moderators was condition dependent (e.g., feedback was only significant in Condition 3). Recommendations for app developers, practitioners, and researchers are discussed.

Authors

• Adnan Mayof, Washington State University
  Presenting Author

• Olusola Olalekan Adesope, Washington State University
  Presenting Author

• Yuliya Ardasheva, Washington State University - Tri Cities
  Presenting Author