Transitioning Students into Higher Education
Bibliographic record
Abstract
Transitioning Students in Higher Education focuses on the relationship between philosophy, pedagogy and practice when designing programs, units or courses for transitioning students to new educational spaces in the university environment. The term transition' is used to describe the academic as well as social movement and acculturation of students into new higher educational spaces. This book offers both theoretical perspectives and real-world practical examples that reveal the successes and challenges of implementing philosophically driven pedagogies with diverse transitioning cohorts. Drawing on examples from Australia, New Zealand, US and Canada, it writes through the relationship between philosophy, pedagogy and how it can effectively shape the practice of transition and develop the flourishing student. This book is split into three main sub-themes: Flourishing in Transition, Engaging Diverse Cohorts and Challenges for Educators, and sits at the intersections between philosophy and pedagogy in the practice of effectively engaging and transitioning different enabling groups. This book will be of great interest to postgraduate students, researchers and educators working in the areas of enabling or bridging education, higher/tertiary education, distance learning, and indigenous as well as culturally diverse cohorts
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".