Enhancing Understanding and Retention in Undergraduate ECE Courses through Concept Mapping
Notice bibliographique
Résumé
Abstract Concept mapping is well recognized for its effectiveness in promoting deep learning and aiding students in understanding knowledge acquisition in complex subjects. In undergraduate ECE courses, instructors usually present topics one by one, followed by examples and applications. Instructors can easily navigate all course information due to their well-established understanding of the entire course and the connections between its topics. However, students face the challenge of establishing the connection between their existing knowledge and the new concepts and reinforcing those connections through repeated practice. In this work, we introduced concept mapping as an assessment tool to help students build these links and enhance their learning experience. The goal is to improve students' comprehension, retention, and interconnectivity of complex course topics. We have systematically integrated concept mapping into four distinct courses: a freshman course about electronics (ECE 110), a sophomore course about signal processing (ECE 210), and two junior-level courses about electromagnetics (ECE 329) and green energy (ECE 333). In each course, students were asked to create their own concept maps before midterm exams. The maps were scored qualitatively by the instructor based on the number of concepts and their structures. This exercise was designed to encourage students to consolidate their knowledge and foster a deeper understanding of the course material by visualizing and summarizing the relationships between key topics. This type of active learning also empowers students to take ownership of their learning by creating and revising their concept maps. A fundamental aspect of our course improvement work involved gathering feedback from students regarding their perceptions of the effectiveness of concept mapping in these courses. In each course, a survey was administered at the end of the semester to gauge students' experiences, opinions, and reflections. Our findings from the surveys indicate that concept mapping is perceived positively by a significant proportion of the students, especially if it's actively used as an instruction tool during the semester. Students reported that concept mapping enhanced their understanding of the course material.
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.
Comment cette classification a été obtenuedéplier
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».