Developing a Program to Strengthen Cooperative Learning Management Competencies of University Lecturers in Nanning
Bibliographic record
Abstract
The objectives of this research were: 1) to explore existing situations, desirable situations, and the need to develop cooperative learning management competencies of university lecturers; and 2) to develop a program to strengthen cooperative learning management competencies of university lecturers. A multi-phase mixed methods research approach was employed, divided into two phases: Phase 1, which explored existing situations, desirable situations, and the need to develop cooperative learning management competencies among university lecturers. The samples were 380 university lecturers and administrators in Nanning, Guangxi. The research instrument was a 5-rating scale questionnaire with reliability of the existing situation equal to 0.981, and desirable situation equal to 0.984; Phase 2 involved developing a program to strengthen cooperative learning management competencies of university lecturers. Informants were 5 outstanding university lecturers and 7 experts to evaluate the program. Research instruments included an interview form and a program evaluation form. Statistics used to analyze data were mean, standard deviation, and modified priority needs index. The research results were: 1) The existing situations of university lecturers' competencies in cooperative learning management were at a moderate level, while desirable situations were at a very high level. The need to develop cooperative learning management competencies of university lecturers were ranked from high to low: media and learning resources, measurement and evaluation, design of cooperative learning management activities plan, curriculum analysis, and cooperative learning activities management; and 2) A program to strengthen cooperative learning management competencies of university lecturers comprising 2.1) rationale, 2.2) objectives: to educate and develop the abilities and skills university lecturers in managing cooperative learning, 2.3) content consists five modules: curriculum analysis, designing cooperative learning activities, managing cooperative learning activities, media and learning resources, and measurement and evaluation, 2.4) methods of development consist of two stages: stage 1 was intensive workshop, and stage 2 was on-the-job development, 2.5) Media and learning resources, and 2.6) Measurement and evaluation consists of a test, observation form, and abilities and skills evaluation form. The results of the program evaluation were at the highest level in propriety, feasibility, and utility.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".