Temporal learning analytics to explore traces of self-regulated learning behaviors and their associations with learning performance, cognitive load, and student engagement in an asynchronous online course.
- DOI
- 10.3389/fpsyg.2022.1096337
- Published
- 2023-01-23
- Container
- Front Psychol
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
uncertain Score 53/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.3389/fpsyg.2022.1096337,
title = {Temporal learning analytics to explore traces of self-regulated learning behaviors and their associations with learning performance, cognitive load, and student engagement in an asynchronous online course.},
author = {Sun JC and Liu Y and Lin X and Hu X.},
year = {2022},
journal = {Front Psychol},
doi = {10.3389/fpsyg.2022.1096337},
url = {https://doi.org/10.3389/fpsyg.2022.1096337}
}RIS
TY - JOUR TI - Temporal learning analytics to explore traces of self-regulated learning behaviors and their associations with learning performance, cognitive load, and student engagement in an asynchronous online course. AU - Sun JC AU - Liu Y AU - Lin X AU - Hu X. PY - 2022 JO - Front Psychol DO - 10.3389/fpsyg.2022.1096337 UR - https://doi.org/10.3389/fpsyg.2022.1096337 ER -
APA
JC, S., Y, L., X, L., & X., H. (2022). Temporal learning analytics to explore traces of self-regulated learning behaviors and their associations with learning performance, cognitive load, and student engagement in an asynchronous online course.. Front Psychol. https://doi.org/10.3389/fpsyg.2022.1096337
Source records
- europe-pmc · retrieved 2026-09-27T02:44:18.086Z
- doaj · retrieved 2026-09-27T02:44:18.086Z