14 Authentic Graduate Education for Personal and Workplace Transformation
Bibliographic record
Abstract
The purpose of this chapter is to examine the creation of authentic learning environments in the light of adult education and transformative learning theory, using a graduate course as a case example. Authentic learning environments and authentic workplaces have much in common. They tend to be ones in which collaborative partnerships prevail over hierarchical power relationships; leadership is enabling rather than controlling; differences are viewed as rich resources for learning rather than challenges to be “managed”; reflection and critical thinking are encouraged through the development of vibrant communities of practice; conflicting ideas are surfaced through genuine dialogue; and wholeness is valued — both in the individual as a whole person, and in the understanding of groups and organisations as living systems. Traditional universities are challengingplaces in which to create learning environments that fit this description. Through an analysis of the design and implementation of Course 1130, the chapter attempts to provide specific ideas for how graduate education can contribute to significant personal change in the values, attitudes and behavior of adult learners.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".