Factors Affecting Teacher Motivation to Teaching Effectiveness: A Study at the Tertiary Level in Bangladesh
Bibliographic record
Abstract
Teacher motivation is an essential element to teaching effectiveness in any context. In Bangladesh, teacher motivation at the tertiary level also plays a pivotal role and is considered one of the key determinants in the teaching and learning process. Unfortunately, teacher's motivation has not received much attention from educational researchers or policymakers yet. This study investigates the external factors affecting teacher motivation more specifically teacher in-service motivation to teaching effectiveness at the tertiary level in Bangladsh. Both quantitative and qualitative research methods have been employed as the main techniques to gather information for the study. To collect data, a 12-item questionnaire survey content, and One-on-One interviews were applied. A total of 52 academics teaching undergraduates and postgraduates participated in the questionnaire survey and 7 teachers were interviewed in the study. After analyzing the data, the study finds several factors tremendously affecting teachers' motivation and eventually teachers' performance and effectiveness. It also reveals that good pay or salary, job security, opportunity of systematic academic promotion and up-gradation, less workload and stress, adequate teacher education and professional development, and congenial local and central administrative policy prompt teachers to be more professional and committed to teaching and learning procedures. Conversely, low pay, job insecurity, lack of professional development and promotion, overwork and stress and failure to maintain a professional environment directly demotivate teachers to be committed and effective to teaching. Therefore, teacher's in-service motivation needs to be addressed properly as it is found as one of the most crucial factors that determines the teacher's role to teaching effectiveness at the tertiary level of education in Bangladesh.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".