Students’ perception on blending mathematics teaching with kindness
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper showcases the effectiveness of integrating deliberate acts of kindness (DAKs) into mathematics education at the university level. Kindness was incorporated into engaged labs, mid-class online quizzes, small-group collaboration, and final grade calculations. Instructors also learned students’ names, valued their input, and shared personal anecdotes. We analyse both qualitative and quantitative survey responses from 248 first-year students of an introductory calculus class at a large Canadian university. This study explores the interplay among student perceptions of school kindness, active and effective learning, classroom supportiveness, optimism, prosocial and social goals, life satisfaction, and academic self-efficacy. The results show that instructors’ caring behaviours were correlated with positive perceptions of instructor kindness. Furthermore, students of empathetic caring instructors had significantly higher school kindness scale scores. The insights from this study motivate educators to incorporate DAKs into their teaching to enhance student well-being. Additionally, these findings can inform future pedagogical studies and foster advancements in pedagogy research.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it