Increasing Students’ English Language Learning Levels via Lesson Study
Bibliographic record
Abstract
The study aims to develop students’ higher cognitive skills e.g. analysis, synthesis and assessment and to increase their academic successes by reflecting their cognitive skills in psychomotor skills in practice with the help of lesson study. Therefore, the aim of the study is to increase students’ English as a foreign language learning level. Action research was used in the study. “English Achievement Test” and “Semi-Structured Interview Form” developed by the researchers were used as data collection instruments. English achievement test was used as pre-test and post-test to define students’ English language levels, and semi-structured interview form was used to determine teachers’ views about lesson study practice. According to research result, lesson study has increased students’ learning levels significantly. Moreover, teachers stated that lesson study was highly beneficial and affected their professional development in a positive way. It was stated by teachers in the study that lesson study had the teachers a chance to observe and assess their teaching qualities and so, it made the students’ learning levels increase significantly. Furthermore, all of the teachers agreed that lesson study as an in-service training model could be an approach used for both other lessons and nationally.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".