The Development of Research-Based Learning Management in the Curriculum Design and Development Course for Teacher Students
Bibliographic record
Abstract
The purposes of the current study are to develop research-based learning management in the Curriculum Design and Development course for student teachers and to study the effectiveness of the research-based learning management in the Curriculum Design and Development course for student teachers. The instruments were a structured interview form, a learning management quality assessment, learning management, a learning achievement test, and a questionnaire. The data were analyzed by mean score, standard deviation, t-test, and content analysis. The results of the study indicate that there were 6 components including ground theories, objectives, instruction processes, social system, principles in responses and supportive system, and learning management in the research-based learning management. In detail, there were 5 stages in learning management including ideas and information analysis, planning and creative design, action-taking, presentation and reflection, and evaluation and improvement. The result of the study shows that there was a significant difference between the students’ learning achievement before and after learning with the developed learning management. The students’ attitudes toward learning management were found at a high level in every aspect.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".