Critical Aspects of a Higher Education Reform for Continuous Lifelong Learning Opportunities in a Digital Era
Bibliographic record
Abstract
In the knowledge society today, there is a strong need for providing continuous lifelong learning opportunities. Recently, the Covid-19 pandemic has acted as a catalyst for technology enhanced learning, involving new challenges for higher education. The main focus for this study has been the ongoing reform of higher education for providing lifelong learning opportunities. This study is the second phase of a Delphi study on higher education reform. Data were gathered by email interviews with an expert panel, where all respondents have genuine knowledge in the field of technology enhanced lifelong learning. The interview answers were analysed according to the Grounded Theory concepts of open coding and axial coding. The central main category for the axial coding was ‘Higher education reform for the provision of lifelong learning opportunities. This category was later found to be dependent on ‘Infrastructure’, ‘Multimodal delivery’, ‘Pedagogical change’, ‘Financial aspects’, and ‘Quality and organisation’, ‘Digital literacy’, ‘Accessibility’, and ‘Equity, diversity and inclusion’.
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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 | 0.047 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.036 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.012 | 0.011 |
| 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".