Bibliographic record
Abstract
Motivation is one of the leading factors which can affect learners learning foreign languages, it has been observed by researchers for a long time. Since 1990s, the study of motivation puts more attention on the combination between the main motivation theories and the practical school study situation. If learners’ motivation can be cultivated, it can accelerate other factors to promote learners’ ability. Key Words: motivation,theory review,strategy study Resume La motivation est un des facteurs cruciaux qui peuvent influencer les apprennants des langues etrangeres, ce qui a ete observe par les chercheurs pour longtemps. Depuis les annees 90 du 20e siecle, l’etude de la motivation prete plus d’attention a la combinaison entre les theories de mativation et la situation d’apprentissage dans les ecoles de pratique. Si la motivation des apprenants peut etre cultivee, elle peut aussi accelerer d’autres facteurs pour promouvoir la competence des apprenants. Mots-cles : motivation, revue de theorie, etude de la strategie 摘 要 學習動機是影響學生外語學習的主要因素之一，長期以來受到外語學習研究者的廣泛關注。進入二十世紀九十年代以來，外語學習動機研究更注重將動機理論與學校外語教育情景相結合。通過激發學習者英語學習動機，以動機教育促進其他因素的發展，能更好地促進學生的英語學習。 關鍵詞：學習動機；理論回顧；策略研究
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".