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- Vol 4 RE: Chapters 12, 18, App A, App C
self-regulation promptslearning analyticstrace datatransfer performanceadaptive promptingdigital learning environmentsinstructional contextJournal article Evidence summaryAt a glance
This quasi-experimental study examines whether prompts embedded in a digital learning environment can activate self-regulation strategies and whether learning-analytics trace data can explain performance. A sample of 110 higher-education students received prompts targeting cognitive, metacognitive, motivational, or resource-management processes, or participated in a control condition.
Key ideas
The researchers compared declarative knowledge, transfer, learner perceptions, and recorded online behavior. Prompting produced small effects on declarative knowledge and transfer, and prompted groups interacted with the environment differently from the control group. However, the available trace measures did not explain transfer performance sufficiently, illustrating the gap between logging observable clicks and inferring the cognitive or motivational processes that matter for learning. The authors conclude that prompts have potential as lightweight support for self-regulated learning, but learning analytics must be more closely tied to theory and instructional context.
Why it matters
They call for studies of adaptive rather than fixed prompts, richer interpretations of trace data, authentic learning settings, and closer attention to how individual learners perceive and respond to interventions.
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- TE
- Teacher Edition
- PE
- Practice Edition
- RE
- Research Edition
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