Teaching Mathematics in Scientific Bachelor Degrees Using a Blended Approach
Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
Mathematics plays a pivotal role in most scientific disciplines, being them meant both inside and outside academic contexts, with applications in a large part of the jobs nowadays, and also in several situations of everyday life. If on one hand this is well recognized, as an expression like the queen of the sciences show, on the other hand it is usually not among the students' preferred subjects, both from the liking and the interest points of view. Furthermore, it is still partly believed that Mathematics cannot be properly learnt by everyone, since it is perceived that, for really mastering it, a specific personal attitude is necessary. Considering all this, we designed a course in which the approach is considerably devoted to applications, being it directed at students of a scientific bachelor program not mainly focused on Mathematics, and problem solving, that is the contextualization of problems in real life situations. For this purpose, we made use of technologies such as a Learning Management System integrated with an Advanced Computing Environment and an Automated Assessment System. It has been observed that the students, which are taking a program in Biotechnology, gained curiosity and interest in the subject, thus allowing in turn a better proficiency. Since interaction between learners is promoted, the students are made active users of the contents, and their learning paths can be adapted according to the personal needs. They have been able to improve also the self-consciousness of their skills. This has been an important achievement especially for (but not limiting to) their future as scientists, considering the role transversal skills play in science, such as teamwork or flexibility. Finally, the students were specifically able to recognize how the problem solving approach will help them in both university and job careers, and how the use of the software has been helpful too.
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 | 0,000 | 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