An Online Summer Course for Prematriculation Medical Students
Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
Objective: An online summer course was developed to enhance students' skills in cooperative learning and self-directed learning, Internet search strategies, problem solving, creativity, and project-management skills. The four-week course was offered in the summer of 2000 to the class of 2004 as a voluntary, no-cost, no-credit opportunity. It was delivered over the Internet using WebCT and included both asynchronous and synchronous learning experiences. Description: Eighteen of the 50 students in the incoming class registered for the course and were divided into four teams. A second-year student facilitated each team to guide discussion and keep the team on track. Two faculty served as mentors to each facilitator, providing assistance as needed. Approximately eight hours of work were built into each week, including pre- and post-tests, evaluations, content material, self-directed learning exercises, bulletin board, and chat. The bulletin board was used to solve problems, share information, and make project status reports and to organize weekly chat sessions. The first two weeks of the course consisted of introductory, socialization, and team-building exercises and included a module on Internet search skills. The third week of the course was organized around a clinical problem (the students were required to research several specific aspects of diabetes mellitus), and in the fourth week the teams organized and developed papers on the clinical problem. A one-hour participant forum was conducted during orientation week so that students and facilitators could meet each other and share their reactions about what had and had not worked in the summer course. Information Technology Institute (ITI) of Halifax, Canada, developed this course under contract with the University of South Dakota School of Medicine. ITI was selected for the project because of the company's background in collaborative learning, group processes, and problem-based learning. One of the authors (DK) worked with the medical school and ITI to develop course content and evaluation mechanisms. Discussion: Pre- and post-tests examined the participants' knowledge, opinions, and skills with several statistically significant findings. After they completed the online course, the participants' knowledge of collaborative learning and teamwork increased from a mean of 21.7% to 51.7% (p = .01); knowledge of self-directed learning increased from a mean of 60% to 80% (p = .03). The overall increase in knowledge as measured by change in the pre- and post-tests was from 50.2% to 67% (p = .01). The students ratings of their information-retrieval skills increased from a mean of 3.58 to 3.87 (p = .03) after the completion of the course. In response to the question “I am continuously searching for better solutions to problems,” the mean response increased from 3.87 to 4.27 (p = .01). The students' opinions and learning about interpersonal and communication skills also showed a positive change, from 4.05 to 4.23 (p = .01). Students responded positively to the course in the formal evaluation and during the reflection period. All reported that they would recommend the course to a friend who had been accepted to medical school. Proposed changes to the course include reducing or compressing the socialization exercises and increasing the content on clinical problem solving.
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 | 0,005 | 0,002 |
| 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 | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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