What are the Effects of Project-based English Curriculum on the Development of Learners' Competencies? A Case Study of a Japanese University English Language Program
Bibliographic record
Abstract
Japanese English education reform continues to falter, and the same is true of university English education. However, amidst these circumstances, transmission-oriented English education is gaining attention as a methodological approach to English language educational reform. Transmission-oriented English education, in which the authors are also engaged, is a model for reform that shifts the emphasis from the traditional reception-based approach in English education to a more communicative, active learning approach. However, while these educational practices have shown results in terms of excitement in the classroom and subjective satisfaction among learners, there is a lack of objective proof, and the accumulation of research to verify the results objectively is an urgent need. In this paper, we examine the results of the GTEC (Global Test of English Communication)-Academic and TOEIC (Test of English for International Communication), which objectively measure English proficiency, and the GPS (Global Proficiency Skills)-Academic, which objectively measures basic social competencies, in two different groups of participants to determine whether the presence or absence of transmission-oriented English education has contributed to the growth of abilities ranging from subsets of English skills to socially necessary competencies by utilizing statistical verification. One interesting result was that the experimental group that took transmission-oriented English education for one year scored significantly higher in English writing than the group that did not, and since there were no statistically significant differences in any of the other components of English proficiency, we concluded that this could be considered an outcome of transmission-oriented English education.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".