Mobile Multimodal Learning Analytics Conceptual Framework to Support Student Self-Regulated Learning (MOLAM)

Abstract

Online distance learning is highly learner-centred, requiring different skills and competences from learners, as well as alternative approaches for instructional design, student support, and provision of resources. Learner autonomy and self-regulated learning (SRL) in online learning settings are considered key success factors that predict student performance. Research suggests that learners may struggle in online, open, and mobile learning environments when they do not use critical SRL strategies. This chapter argues that the effective use of SRL would be beneficial in these contexts, although this can be difficult for both learners and educators, particularly when students are learning online and/or independently. The chapter introduces a Mobile Multimodal Learning Analytics approach (MOLAM) aimed at guiding learners, teachers and researchers wanting to develop, successfully employ and/or evaluate learning analytics approaches for mobile learning activities for the purposes of measuring and fostering student SRL in diverse online learning environments. MOLAM is especially valuable for continuous measurement and interventions, thus fostering students’ transferable SRL skills, strategies, and knowledge across formal, informal, and non-formal online learning settings. The chapter concludes suggesting that mobile multimodal learning analytics should be performed with careful integration of relevant support mechanisms and frameworks to protect student privacy and ensure their agency.