Teaching and learning for new futures and better lives: The journey of McMaster Continuing Education from 2016-2021
Bibliographic record
Abstract
The purpose of McMaster Continuing Education (MCE) is to serve non-traditional learners—often called adult learners—as they seek ways to advance their careers and pursue their love of lifelong learning. Like others who attend university, these learners deserve the best we have to offer. Recognizing this goal, the reader is invited to learn about themes that characterize continuing education in Canada and the earliest days of continuing education at McMaster University. The reader is also invited to reflect on how MCE has advanced learning for adults since 2016 when new leadership and a new strategic plan guided its development. Last, this chapter positions MCE as a leader in the use of innovative learning strategies and explores how it was well equipped when the global pandemic of 2020 challenged educational institutions around the world. How MCE navigated its transition to remote learning for students and educators prior to the pandemic and its plans for teaching and learning in post-pandemic times may be helpful to other units wanting to nurture some of the practices MCE discovered during the pandemic.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".