Encouraging Empirical Research and European/American Andragogy Coming Closer as Distance Education Grows in Strength
Bibliographic record
Abstract
Billington found that with 60 male and female doctoral students aged 37 to 48, there were seven andragogical factors that helped them grow, or if absent made them regress or not grow. Rachal clearly identified seven criteria for implementing future empirical studies of andragogy. Taylor et al. asserted that no conversation on teaching adults is complete without discussing andragogy. However, Grace considered andragogy in the USA and Canada as being complicit in sidelining cultural and social concerns as well as decontextualizing adult learning, while having been effectively dismantled in the 1980s and 1990s. Showing the strength of andragogy through its long history in Europe, Savicevic indicated that comparative andragogy has eight elements that are essential in addressing this scientific research topic. Sopher stressed Knowles was best viewed as humanistic, philosophically. Henschke also found deep captivating involvement in both European and American andragogy. This chapter explores this.
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How this classification was reachedexpand
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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".