Towards the mature ePortfolio: Some implications for higher education
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
Electronic portfolios [ePortfolios] are a recent addition to the language of higher education. Commencing with a summary of their role from EDUCAUSE, whose mission is to advance higher education by promoting the intelligent use of information technology, the distinctive characteristics of ePortfolios are outlined and salient differences from conventional portfolios in terms of process and outcomes are explored. Having considered the attributes of a mature ePortfolio, the paper focuses on pedagogical and technological issues for students and staff to move to mature ePortfolios. While accepting the valuable role ePortfolios can play in higher education, and that students increasingly come to the tertiary sector with expectations and experience that appear to warrant this approach, the paper concludes that decision making in this area is not yet adequately supported by research. Educators need to be open to the promise ePortfolios offer their students and staff but be aware of the implications for their adoption.
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 | 0.000 |
| 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