A Hopeful Future? Preparedness and Optimism-Pessimism About the Future of Post-secondary 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
This study investigates the following research questions in the Canadian and US contexts: 1) To what extent do those working at post-secondary institutions expect the future of post-secondary education to change over the next five years? 2) Do they feel ready for the changes that the future might bring? 3) Are they feeling optimistic or pessimistic about the future? In Spring 2023, Bay View Analytics and the Canadian Digital Learning Research Association (CDLRA) conducted US and Canadian survey studies to address these questions. Overall, the findings from both countries suggest that those working in post-secondary education expect the future to be different from the present and rate themselves as somewhat ready for these changes. Feelings of optimism and pessimism vary by country and may be explained by contextual factors unique to the differences between Canadian and US culture and policies; however, the qualitative analysis did not reveal any distinctive reasons for such differences. Overall, the findings clearly indicate that post-secondary education is well-poised for further digital transformation in the near future.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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