Multimodal Learning Analytics in K–8 Research: A Systematic Review

• In Event: Data-Driven Decision Making

Abstract

This systematic review aimed to (a) examine how multimodal learning analytics has been applied in K-8 research to date and (b) provide methodological guidance and recommendations to bridge the gap between theory and practice. We identified 14 studies to be included in the review through electronic and manual search. The results highlighted that (a) the application of multimodal learning analytics in K-8 research is varied; (b) even though studies explicitly stated how multimodal data were collected and analyzed, they rarely mentioned the data fusion and its process, and transparency; and (c) multimodal learning analytics has the potential to improve learning outcomes, but more guidance is needed to conduct sound research using multimodal learning analytics. Implications and recommendations are provided.

Authors

• Secil Caskurlu, Florida State University

• Ceren Ocak, Georgia Southern University

• Chih-Pu Dai, Texas A&M University