To What Extent are Japanese University Students Successful in Motivating Themselves to Learn English through Project-based Language Education? An Assessment of Students after Two Years of PBL-based English Language Education
Bibliographic record
Abstract
The objective of this study is to evaluate the efficacy of project-based learning (PBL) methods in teaching English at the Japanese university level from the perspective of motivational research. The case study focuses on the Project-based English Program (PEP) at a large private university in Japan, examining whether the program not only enhances English proficiency, but also motivates students to a higher level of self-determination. By analyzing these outcomes, this paper discusses the added value of PBL-based English education in terms of its effectiveness in motivating students. The analysis reveals that PEP has improved the English proficiency of the participants over the two-year curriculum, and that in terms of motivation, PEP has been successful to some extent in cultivating identified regulation, a relatively high level of self-determination among extrinsic motivation for English language learning. The results also indicate that the group tended to develop intrinsic motivation, a motivation with an even higher level of self-determination, suggesting that PBL-style classes are effective in facilitating the acquisition of high self-determined motivation. However, the results for stimulation, one aspect of intrinsic motivation, tended to show almost no acquisition, and the results for introjected regulation, an extrinsic motivation, were also scattered, suggesting that learners may retain some hesitation, conflict, and stress according to motivation theory. These findings can be utilized to improve educational programs in the future.
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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 | 0.002 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".