Research on Professional Skill Training implemented into College Education System
Bibliographic record
Abstract
In the process of deepening the reform of higher education, one of the important issues concerned together by government, enterprise and schools is how to improve the quality of higher education and improve Students professional skills and overall quality. For the sake of meeting the needs of society and the requirements of employment units “comprehensive” talent, improving students’ professional skills and capability, this paper suggested to embed professional skill training into college education system. On the basis of establishing training model in college education system, this paper divided the model into the inner circle and outer circle. Meanwhile it pointed out setting up“2+1+1”college course to ensure the model implement successfully. Key words: professional skill training, college education system Resume: Dans le processus de l’approfondissement de la reforme de l’education superieure, un des plus importants problemes preoccupant a la fois le gouvernement, les entreprises et les ecoles est comment ameliorer la qualite de l’education superieure et developper la competence professionnelle des etudiants. Afin de repondre aux besoins de la societe et aux exigences des employeurs de chercher des talents « comprehensifs », et d’elever la competence et les capacites professionnelles des etudiants, l’article present propose d’implanter l’entrainement de la competence professionnelle dans le systeme educatif universitaire. Sur la base de l’etablissement du modele d’entrainement, l’article divise le modele en cercle interne et cercle externe. Il suggere en meme temps d’instaurer le cours universitaire « 2+1+1 » pour assuer l’application resussie du modele. Mots-Cles: entrainement de la competence professionnelle, systeme educatif universitaire
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".