A Study of the Relationship Between Tutor's Personality and Teaching Effectiveness: Does culture make a difference?
Bibliographic record
Abstract
Good tutoring requires appropriate interpersonal and pedagogical skills. Tutor personality is a major factor affecting how tutors communicate and deals with students, and yet it is a largely unexplored context of distance education. Using the Chinese Personality Assessment Inventory (CPAI)* this paper examines how the personality of tutors’ affects their teaching effectiveness at a distance learning institution in Hong Kong. The results are compared to those reported by Chan (2001) in a similar study using the Myers-Briggs Type Indicator (MBTI). The results indicate that certain scales on the Chinese Tradition factor of the CPAI are significantly related to tutors’ teaching performance, and that the MBTI could not subsume all the CPAI scales. Future research with the CPAI should explore whether this Chinese Tradition factor is unique to the Chinese culture or whether it comprises elements of a universal domain useful in understanding key interpersonal aspects of personality that have been absent from Western personality inventories.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".