Investigating Students’ Online Self-Regulated Learning Skills and Their E-Learning Experience in a Prophetic Communication Course
Bibliographic record
Abstract
Prophetic communication (PC) is an Islamic perspective with which to view everyday communication phenomena. While there are currently many negative aspects to the use of social media and the internet, online learning is highly useful for supporting the PC learning process—especially during the COVID-19 pandemic. Before the current pandemic, online learning was typically conducted in a blended manner with face-to-face meetings. However, this shifted during the pandemic, and PC learning was undertaken entirely online. Since the students themselves are one of the success factors of online learning implementation, it is important to examine the students’ self-regulated learning skills in an online PC course throughout the semester. Quantitative and qualitative data were gathered from four classes. Data analyses were also conducted to address the research aim. The findings revealed that, overall, students apply self-regulated online learning skills. However, improvement and facilitation are still needed to enhance evaluation skills. From the qualitative data gathered, we constructed and categorized several themes into positive learning experiences, challenges, online learning strategies, and suggestions with which to improve online class management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".