Analyzing Multimodal Multichannel Data about Self-Regulated Learning with Advanced Learning Technologies: Issues and Challenges

Author:

Azevedo Roger,Gašević Dragan

Publisher

Elsevier BV

Subject

General Psychology,Human-Computer Interaction,Arts and Humanities (miscellaneous)

Reference24 articles.

1. Theoretical, methodological, and analytical challenges in the research on metacognition and self-regulation: A commentary;Azevedo;Metacognition & Learning,2009

2. Defining and measuring engagement and learning in science: Conceptual, theoretical, methodological, and analytical issues;Azevedo;Educational Psychologist,2015

3. Using multi-channel trace data to infer and foster self-regulated learning between humans and advanced learning technologies;Azevedo,2018

4. Data mining methods for assessing self-regulated learning;Biswas,2018

5. Emotion and emotion regulation in academic settings;Boekaerts,2015

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1. Towards prescriptive analytics of self‐regulated learning strategies: A reinforcement learning approach;British Journal of Educational Technology;2024-01-10

2. Facial Expression Recognition for Examining Emotional Regulation in Synchronous Online Collaborative Learning;International Journal of Artificial Intelligence in Education;2024-01-02

3. Detector-driven classroom interviewing: focusing qualitative researcher time by selecting cases in situ;Educational technology research and development;2023-12-22

4. Self-regulation of resources in higher education;Zeitschrift für Pädagogische Psychologie;2023-12-12

5. Lifelong learner needs for human-centered self-regulated learning analytics;Information and Learning Sciences;2023-12-11

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