The Development of Instructional Packages using Growth mindset for Enhancing Positive Psychological Capital of Among Higher Education
Bibliographic record
Abstract
This study aimed to develop instructional packages using a growth mindset framework to enhance positive psychological capital among students of the Faculty of Education, Kasetsart University. The sample consisted of 30students enrolled in the course on Educational Psychology and Guidance for Teachers, selected by purposive sampling. The research employed a positive psychological capital scale and a feedback questionnaire on the activities. Statistical analysis included mean, standard deviation, and the wilcoxon signed-rank test. The results indicated that the instructional packages effectively enhanced positive psychological capital, with the mean score increasing from 3.93 to 4.24, which is at the highest level. The wilcoxon signed-rank test showed that the p-value was less than 0.05, indicating that these iprovements were statistically significant at the .05 level. Additionally, students' feedback on the activities was positive, indicating that the activities helped enhance self-understanding, motivation, and a more positive outlook on themselves and their lives.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".