Investigation and Analysis on the Present Situation of Educational Belief of Normal University Students
Bibliographic record
Abstract
The cultivation of educational belief of normal college students is conducive to promoting the professional development of teachers, strengthening the construction of teachers' team, improving teachers' accomplishment and ensuring the healthy development of basic education.A questionnaire survey on the educational beliefs of 811 normal college students in a normal college in Chengdu shows that, A questionnaire survey on the educational beliefs of 811 normal college students in a normal college in Chengdu shows that.Although it just about 42.4% normal college students basically known the knowledge of education belief.While it’s important to set up the education belief for 95.8% of normal students. As for the lowly education profile atmosphere of society and college ,which is in short of the scientifically manage and cultivate system so that to emergent the shortage of education belief for the large mount of college normal students. For the future researching statement the different gender, grand , background, minority and free or unfree normal students to make the difference to the education belief of cognitive ability ,expectation, attitude, emotion quality. Firstly, the cultivation of normal students education belief to induce them to set up the lofty education dream mission for the ultimateness demand direction. Secondly ,it should be builded up to the roundly cultivate and stimulate system.At last, it should be increasing the normal students as themselves to the main part of self-education.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".