The Investigation of Learning Motivation and Strategy in the Normal Undergraduates
Bibliographic record
Abstract
Abstract In order to investigate the learning motivations and strategies, and their relationship in current normal undergraduates, we conducted a survey in 249 undergraduates from Qufu Normal University. The results showed that: (1) deep learning motivation and strategy were predominant in these students; (2) there were significant gender differences in learning motivation and strategy; (3) there were significant disciplinary differences in learning motivation and strategy as well; (4) deep learning motivation was significantly different between different grades of students and increased with grade. However, there was no grade difference in learning strategy. We therefore provided relevant advices and strategies in different aspects such as study environment, curriculum, mental health education, the optimization of teacher sources, family, and society, etc. Key words: Normal undergraduates; Learning motivation; Learning strategy Resume Afin d'etudier la relation de motivation actuelle des enseignants des colleges et des strategies d'apprentissage, le present etude est visee sur une enquete sur 249 etudiants de premier cycle de l'Universite normale de Qufu. Les resultats montrent que: (1) les etudiants de l’Universite Normal, la motivation et les strategies d'apprentissage repose essentiellement sur la motivation a apprendre en profondeur et les strategies d'apprentissage basees; (2) la motivation a apprendre et les strategies d'apprentissage dans les differences entre les sexes, (3) la motivation d'apprentissage et les strategies d'apprentissage dans Les categories (arts, sciences) il existe des differences; (4) la motivation profonde d'apprentissage dans chaque classe en fonction des differences significatives, et avec des grades superieurs ont montre une tendance significative. Toutefois, les differences entre les grades dans la strategie d'apprentissage n'est pas evident. Enfin, pour l'ecole dans le milieu scolaire, le curriculum, la formation des enseignants et de la sante mentale des eleves et d'autres aspects de l'optimisation et la famille et du point de vue social pour resoudre les questions pertinentes et les recommandations correspondantes mises en avant. Mots cles: Etudiant d’Universite Normal, Motivation d’apprentissage, Strategie d’apprentissage
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".