Engagement with Electronic Portfolios: Challenges from the Student Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Much of the evidence and research available on the use of e-portfolios focuses on faculty and institutional perspectives and/or consists mainly of anecdotes about how useful the e-portfolio has been to learners. While it is generally agreed that e-portfolios have great potential to engage students and promote deep learning, the research that has been conducted to date focuses very little on student perceptions of value of the e-portfolio for their learning. If students do not accept the e-portfolio as a holistic means with which to document their learning in different contexts and more importantly, agree or wish to use the e-portfolio as an integral part of their educational experience, then the potential impact the e-portfolio will have on learning will not be realised. This paper highlights four themes arising out of research that is underway within an international framework of collaboration between the University of Edinburgh, the University of British Columbia and the University of Waterloo.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it