Encouraging self-regulated learning through electronic portfolios
Bibliographic record
Abstract
At the Centre for the Study of Learning and Performance (CSLP) at Concordia University in Montreal, Quebec, we have developed the Electronic Portfolio Encouraging Active Reflective Learning Software (ePEARL) to promote student self-regulation and enhance student core competencies. This paper summarizes the literature on electronic portfolios (EPs), describes ePEARL, and documents our research findings to date including analyses of teacher and student reactions. Participants in this study were 62 school teachers, mostly from elementary schools, and their students (approximately 1200) from seven urban and rural English school boards across Quebec. Student and teacher post-test questionnaire responses suggested that the use of portfolios, and the learning processes they support, were positively viewed and learned well enough to be emerging skills among students. Contrariwise, teachers commented that teaching SRL strategies was new and thus required a change in teaching strategies, strategies that they were not yet accustomed to. Focus groups also revealed the challenges of using portfolios to teach children to self-regulate. And finally, the analysis of student portfolios evidenced only small amounts of student work or high levels of student self-regulation. Résumé : Au Centre d’études sur l’apprentissage et la performance (CEAP) de l’Université Concordia à Montréal, Québec, nous avons conçu le logiciel de portfolio électronique réflexif pour l’apprentissage des élèves (PERLE) afin d’encourager l’apprentissage autorégulé chez les élèves et d’accroître leurs compétences de base. Cet article présente un résumé de la documentation sur les portfolios électroniques, une description de PERLE, ainsi que nos résultats de recherche documentés à ce jour, y compris des analyses des réponses des enseignants et des élèves. Les participants à cette étude se composaient de 62 enseignants, la plupart dans des écoles primaires, et de leurs élèves (environ 1200) provenant de sept commissions scolaires anglophones urbaines et rurales du Québec. Les réponses des élèves et des enseignants au posttest suggèrent que les portfolios et les processus d’apprentissage qu’ils soutiennent ont été perçus de manière positive et qu’ils ont été suffisamment assimilés pour se traduire par de nouvelles compétences chez les élèves. En revanche, les enseignants ont mentionné qu’enseigner les stratégies d’apprentissage autorégulé était nouveau et que cela exigeait de modifier leurs stratégies d’enseignement pour en adopter d’autres auxquelles ils n’étaient pas encore habitués. Les groupes de discussion ont également fait ressortir les défis liés à l’utilisation des portfolios dans le but d’apprendre l’autorégulation aux enfants. Enfin, l’analyse des portfolios des élèves a révélé que seulement une petite portion des travaux d’élèves démontrait des niveaux élevés d’autorégulation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".