Project-Based Learning and E-Portfolios for Preservice Teachers in Japanese Language Education
Bibliographic record
Abstract
This study involved classroom action research that aimed to 1) develop the learning management competency for preservice teachers using the project-based learning approach and e-portfolios and 2) study the reflection of those preservice teachers in terms of learning management using the project-based learning approach and e-portfolios. The target groups for this research comprised 27 fourth-year students of the Teaching Japanese Language Program, Faculty of Education, Khon Kaen University. I divided the research tools into two categories: (a) tools for learning management (four learning management plans and teaching logs) and (b) tools for collecting research data (the portfolio assessment form and e-portfolios). The research results revealed the project-based learning approach and e-portfolios improved the Japanese language and culture learning management competency in each indicator at different levels; in addition, the results reflected the Japanese language and culture learning management focusing on learners and the use of learning materials stimulated learners’ interest and systematic working and helped them appreciate the efficiency of work and ability to work with others.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".