Measuring and Validating Assumptions About Self-Regulated Learning with Multimodal Data

Author:

Salehian Kia FatemehORCID,Bernacki Mathew L.,Greene Jeffrey A.

Publisher

Springer International Publishing

Reference60 articles.

1. Azevedo, R. (2018). Using hypermedia as a metacognitive tool for enhancing student learning? The role of self-regulated learning. In Educational psychologist (pp. 199–209). Routledge.

2. Azevedo, R., & Cromley, J. G. (2004). Does training on self-regulated learning facilitate students’ learning with hypermedia? Journal of Educational Psychology, 96(3), 523.

3. Azevedo, R., Taub, M., & Mudrick, N. V. (2017). Understanding and reasoning about real-time cognitive, affective, and metacognitive processes to foster self-regulation with advanced learning technologies. In Handbook of self-regulation of learning and performance (pp. 254–270). Routledge.

4. Azevedo, R., Taub, M., Mudrick, N. V., Martin, S. A., & Grafsgaard, J. (2018). Using multi-channel trace data to infer and foster self-regulated learning between humans and advanced learning technologies. In Handbook of self-regulation of learning and performance (2nd ed., pp. 254–270). Routledge.

5. Ben-Eliyahu, A., & Bernacki, M. L. (2015). Addressing complexities in self-regulated learning: A focus on contextual factors, contingencies, and dynamic relations. Metacognition and Learning, 10(1), 1–13.

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