Self-Regulated Learning in Kenyan Classrooms: A Test of ePEARL, a Process e-Portfolio
Bibliographic record
Abstract
To align with Kenya 2030 Vision of education for self-reliance, there is a growing need for classroom instruction that develops students' capacity to be in control of their learning.This paper reports a two-year study that tested feasibility of implementing ePEARL, an e-portfolio, in the context of Kenyan public schools.By design, the digital portfolio supports the key learning processes though the phases of self-regulated learning --forethought, performance, and self-reflection.In this study, students (N=137) from four secondary classrooms used the tool as part of classroom instruction to complete their project assignments.Repeated measures analyses revealed that, over-time, students who demonstrated fuller use of ePEARL made significantly higher gains and reported higher level of selfregulated strategies compared to their classmates who hardly used the tool.The results suggest that in order to yield important benefits, the tool should be meaningfully integrated into classroom instruction.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".