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dc.contributor.authorMangaroska, Katerina
dc.contributor.authorSharma, Kshitij
dc.contributor.authorGasevic, Dragan
dc.contributor.authorGiannakos, Michail
dc.description.abstractProgramming is a complex learning activity that involves coordination of cognitive processes and affective states. These aspects are often considered individually in computing education research, demonstrating limited understanding of how and when students learn best. This issue confines researchers to contextualize evidence-driven outcomes when learning behaviour deviates from pedagogical intentions. Multimodal learning analytics (MMLA) captures data essential for measuring constructs (e.g., cognitive load, confusion) that are posited in the learning sciences as important for learning, and cannot effectively be measured solely with the use of programming process data (IDE-log data). Thus, we augmented IDE-log data with physiological data (e.g., gaze data) and participants’ facial expressions, collected during a debugging learning activity. The findings emphasize the need for learning analytics that are consequential for learning, rather than easy and convenient to collect. In that regard, our paper aims to provoke productive reflections and conversations about the potential of MMLA to expand and advance the synergy of learning analytics and learning design among the community of educators from a post-evaluation design-aware process to a permanent monitoring process of adaptation.en_US
dc.publisherSociety for Learning Analytics Research (SoLAR)en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.titleMultimodal learning analytics to inform learning design: Lessons learned from computing educationen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.source.journalJournal of Learning Analyticsen_US
dc.description.localcodeCopyright (c) 2020 Journal of Learning Analytics. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.en_US

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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal