CLIL in Practice in Japanese Elementary Classrooms: An Analysis of the Effectiveness of a CLIL Lesson in Japanese Traditional Crafts
Bibliographic record
Abstract
This study focuses on how elementary school students learn and think about the development and sustainability of Japanese traditional crafts through a CLIL lesson. The Japanese Course of Study (MEXT, 2017) emphasizes the importance of fostering regionalism and the development of Japanese traditional culture. This plays a significant role in global education. Students must have the knowledge, ability and the will to talk about Japanese culture to non-Japanese people in English. Fostering student’s cross-cultural understanding is crucial to achieve this. The researcher carried out the CLIL lesson with a total of 175 elementary students in Nara, Japan. The students were given instruction in the history, the present situation and the construction of Nara Fans, which are a traditional product of Japan. The results show that students were able to use various English target expressions during the lesson and were not bothered about whether the lesson was in Japanese or English but instead concentrated on the lesson content. In addition, the students learned that Nara is popular among foreigners and that there are many ruins in their surrounding area. In conclusion, CLIL lessons should be continued in various subjects, while taking into consideration individual support for each student, and the importance of constant verification of lesson targets and content.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".