The Nebulous, Essential Dimensions in Effective University Teaching: The Ethic of Care and Relational Acumen
Bibliographic record
Abstract
This paper examines the interrelationships between teaching beliefs and approaches, instructional design, relationships with students, and academics’ and students’ perceptions of effective teaching and learning. Mixed methodology was utilised and included interviews with academics and students, and questionnaires, inventories, and learning journals. As anticipated educationally optimal instructional design was appreciated by academics and students, however, it was not the most significant aspect in influencing students’ perceptions of ‘good’ or effective teaching. Differences were found between two teaching academics’ beliefs about students and these translated into varied approaches to teaching, interactions with students, and different capacities to establish positive classroom environments and relationships. Academics’ ethic of care and relational acumen were the pivotal components in students’ criteria for effective teaching, which may present a quandary to academic developers. Findings indicate the importance of relational acumen and an ethic of care and may also have significance for university leaders in matching academic teaching activities to faculty strengths and potentially explaining negative student feedback in well-designed units.
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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 | 0.021 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.027 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".