arXiv (OAI)
open access
Understanding Self-Regulated Learning Behavior Among High and Low Dropout Risk Students During CS1: Combining Trace Logs, Dropout Prediction and Self-Reports
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- The role of learning engagement in shaping the relationship between self-efficacy, interaction, emotion regulation and perceived learning in online education#306292
- Understanding the Struggles and Resilience of Learners At-Risk of Dropping Out (LARDO): A Phenomenological Analysis#433413
- Are We Strategically Coping with Flexible Learning? Insights From ‘Frontliners’ in Higher Education#86043
- Self-directed learning ability and online student engagement among nursing students: the mediating role of information literacy and the moderating role of self-control.#338335
- Practice Effects Confound the Emotion–Performance Link in Self-Regulated Learning: A Reanalysis of Lin et al. (2026)#390046
Record · ID 173311
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive