A Hopeful Future? Preparedness and Optimism-Pessimism About the Future of Post-secondary Education
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.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".