The Relationship Between Teacher Transformational Leadership and Students’ Motivation to Learn in Higher Education
Bibliographic record
Abstract
This quantitative study sought to examine whether there existed relationships between teacher transformational leadership and students’ motivation to learn. In aggregate, 171 undergraduates recruited from a public Chinese university participated in the study through a random sampling. The participants were administered two instruments: the Multi-factor Leadership Questionnaire (MLQ) 5X-short to measure students’ perceptions of the teacher transformational leadership in the educational context and the Motivated Strategies for Learning Questionnaires (MSLQ) to measure students’ motivation to learn. The data collected were analyzed by Pearson’s correlation and multiple regressions using the Statistical Package for Social Sciences (SPSS). The results from the multiple regression analyses further verified the findings in the previous literature that teacher transformational leadership could contribute to the students’ increased motivation to learn. It is recommended in the study that professional development be the best practice to facilitate the problems and all the college teachers should attend the professional development about transformational leadership behaviors, and implement the newly-acquired knowledge and skills to elevate students’ motivation to learn.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".