Measuring Empathy Among Secondary School Teachers in Sabah: A Quantitative Study
Bibliographic record
Abstract
Teacher empathy is one of the most important attributes of effective pedagogy because it influences the quality of teacher-student interactions. The purpose of the study was to examine the empathy among secondary school teachers in Sabah, Malaysia. It aimed to determine (1) the level of empathy among teachers, (2) if there were any significant differences in perceived empathy based on gender, age, and job experience, and (3) if any of the empathy items were significantly different from the hypothesized value of 3.5. The Toronto Empathy Questionnaire was administered to a sample of 69 teachers from the Kota Kinabalu area on Google Forms. Data were subsequently transferred onto a spreadsheet and analyzed by using SPSS 26.0. First, descriptive statistics indicated that a majority of Sabahan teachers tend to have an average level of empathy. Second, the t-test revealed significant differences in perceived empathy by way of age and job experience at p < .05. Third, the Wilcoxon signed rank test showed that 14 of the empathy items were significantly different from the hypothesized value at p < .001, with only one item being significantly different at p < .05. In light of the findings, some recommendations were made on ways to enhance teacher empathy in Sabah, Malaysia.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".