The Relationship between Course Evaluation and Academic Achievement of University Students Using Latent Profile Analysis
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
This study was conducted with the purpose of deriving a heterogeneous potential profile through the results of university lecture evaluation, which is students' perception of class and the product of professor-student interaction in the classroom, and identified the factors that affect it. In addition, the degree of learning flow for each potential profile was investigated and the difference was verified. For the analysis, 83,069 cases were used because of the university A course evaluation organized in the second semester of 2020, and a total of 12,919 subjects were studied. As a result of analyzing the aspects of course evaluation through class plan, content delivery, communication, response, and evaluation system, that were the sub-factors of course evaluation, the miscellaneous material profiles were classified in four. It was named as the upper group. As factors determining the latent profile using physiological data analysis. It was discovered that significant differences existed between student features (grade, major field), professor features (position), and lecture variables (category of accomplishment, lecture size). Students with lesser grades have a greater chance of succeeding quickly in the top group than do those in the humanities and social sciences, science, or engineering professions. The likelihood of being in the upper group in a course assessment as well as the likelihood of being in the upper group with higher course evaluation outcomes for general education lectures as opposed to major lectures and smaller lecture sizes increases with decreasing professor status. The level of academic obligation was then examined by potential profile based on the course evaluation outline, and the results revealed that the greater the course evaluation result, the greater the level of educational obligation. This is a significant study because it examines the variables that affect the outcomes of the university's course evaluations, which are done at the end of every semester, as well as the relationship between the outcomes of the course evaluations and academic commitment. This study established a scientific basis for colleges to prepare measures to improve the quality of education through lecture evaluation and emphasized the importance of preparing concrete measures to improve students' learning outcomes in college education.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle