Enjeux et tensions de l’implantation et de l’utilisation du portfolio numérique en enseignement supérieur
Bibliographic record
Abstract
Ce numéro spécial repose sur différentes études liées au portfolio numérique en enseignement supérieur. Ce texte de cadrage propose un survol des visées et des cadres de référence des articles qui y sont réunis, en plus d’établir un éventail de contextes d’implantation du portfolio numérique au Canada et en Europe. Divers enjeux émanant de cette publication sont également identifiés afin de contribuer à la réflexion de ceux qui utilisent cet outil de près ou de loin, ou qui songent à son implantation dans un cours ou un programme de formation. This special issue is based on various studies related to the digital portfolio in higher education. This scoping text provides an overview of the aims and conceptual frameworks of the articles that are brought together, as well as establishing a range of digital portfolio implementation contexts in Canada and Europe. In addition, various issues emanating from this publication are identified to contribute to the reflection of those who use this tool from near or far, or who are thinking about its implementation in a course or a training program.
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 | 0.018 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.028 | 0.014 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".