Abstract
In this section, we explore how unobtrusive observations can improve our understanding of learning processes. Unobtrusive observation refers to the detection and analysis of aspects of learning extracted or surmised from digital traces of a learner’s engagement with technologies. The articles covered in this section delve into various aspects of learning processes, such as self-regulated learning, emotions, motivation, entrepreneurial skills, and problem-solving. Although the topics discussed are diverse, they all centre around a common theme of aligning learner trace data with identified theoretical constructs.
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Dawson, S. (2023). Unobtrusively Measuring Learning Processes: Where Are We Now?. In: Kovanovic, V., Azevedo, R., Gibson, D.C., lfenthaler, D. (eds) Unobtrusive Observations of Learning in Digital Environments. Advances in Analytics for Learning and Teaching. Springer, Cham. https://doi.org/10.1007/978-3-031-30992-2_7
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DOI: https://doi.org/10.1007/978-3-031-30992-2_7
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