Problems in Top-Down Goal Setting in Second Language Education: A Case Study of the “Action Plan to Cultivate ‘Japanese with English Abilities’”
Bibliographic record
Abstract
This study critically examines the “Action Plan to Cultivate ‘Japanese with English Abilities,’” which the Japanese Ministry of Education has implemented as part of its reform of English education. Specifically, the paper appraises on the basis of up-to-date research findings on L2 learning the attainment goals the Ministry of Education through its Action Plan has set for junior and senior high school students. In this regard, it is shown that there is no empirical data to justify the Action Plan’s adoption of particular standardized tests into the definition of these goals, and that the goals defined in terms of English proficiency cannot be achieved within the available instructional time. This study thereby identifies flaws in the Action Plan which are caused mainly by the lack of input from those who are acquainted with the reality of L2 learning (i.e., teachers and researchers). The study also suggests possible ways for improving policy making and specifies the types of research that would be instrumental in formulating realistic and effective educational policies. 文部科学省が「『英語が使える日本人』の育成のための行動計画」の中で掲げる中学校・高等学校卒業段階での達成目標を、これまでの第２言語学習に関する研究成果と照らし合わせて批判的に検証した。その結果、この達成目標に関わる次のような問題点を指摘した: (1)目標設定に特定の検定試験が取り込まれたことを正当化できる客観データがない、(2)習熟度を基準に設定された目標は、中学校および高等学校で確保されている授業時間内には達成できない。また、これらの問題を解決すべく、教育実践の指針となる効果的な目標設定のあり方や、そのために必要な実証研究について考察した。
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".