Enhancing the Efficacy of Lecturers in Educating Student Cohorts Consisting of Culturally Diverse Groups in a Medical University
Bibliographic record
Abstract
Lecturers exert a potent influence over the achievement of all students, low-income culturally diverse students in particular. Although recent research has confirmed that lecturer involvement is critical for promoting academic engagement of low-income and ethnically diverse students in America and other countries, other literature suggests that lecturers have lower expectations for and fewer interactions with these students. These findings have prompted calls for promoting lecturers self-efficacy for working with students from diverse backgrounds, especially in a country like Malaysia, where there is a coexistence of students of various ethnic diverse groups, such as Chinese, Malays and Indians. The purposes of this article are (a) to summarize briefly the literature that examines the effect of lecturers efficacy on academic and behavioral outcomes of students, especially culturally diverse students; (b) to disseminate the findings of a lecturer-training program designed to promote lecturer efficacy in relation to culturally diverse students; and (c) to provide lecturers, administrators, and lecturer trainers with methods to increase lecturer efficacy when working with culturally diverse learners.
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How this classification was reachedexpand
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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".