An Exploratory Digital Board Game Approach to the Review and Reinforcement of Complex Medical Subjects Like Anatomical Education: Cross-sectional and Mixed Methods Study
Notice bibliographique
Résumé
BACKGROUND: Serious games have the potential to resolve educational problems faced by medical students, such as insufficient rehearsal due to boredom and lack of motivation. However, serious games' relatively novel concepts in science and many genres of games that are common in recreation remain underresearched in the literature. Board games are one such genre that, despite their potential, affordability, and flexibility, are rarely designed for medical students, and little is known about student perceptions of them and their compatibility with rehearsal. OBJECTIVE: In this cross-sectional study, we sought to elicit, via an exploratory mixed methods approach, student perceptions of a digital serious board game specifically designed for the gamified rehearsal of complex medical subjects, with the chosen topic of anatomy. METHODS: A digital serious board game, based on self-determination theory (SDT), was first designed and developed to facilitate the rehearsal of anatomy information. Students were then voluntarily recruited to partake in the intervention and were randomly split into three teams of 2 players per game session, after which they were administered the Flow Short Scale (FSS), which is a 13-item measure where items were rated on a 7-point Likert scale ranging from 1 ("not at all") to 7 ("very much"). Students then participated in a focus group discussion to elicit their perceptions of the game. Findings from the FSS were subject to descriptive analysis, and the focus group discussion was subject to inductive thematic analysis. RESULTS: A total of 12 undergraduate, second-year medical students from the Lee Kong Chian School of Medicine in Singapore participated in the study. FSS results indicated a moderate level of overall flow (mean score 4.94, SD 1.07) via the subdomains of fluency (mean score 4.77, SD 1.13) and absorption (mean score 5.21, SD 1.1). Students perceived the game as fun, enjoyable, engaging, and appropriate as a rehearsal tool that alleviated the monotony of traditional methods of rehearsal. CONCLUSIONS: Our digital board game-based rehearsal tool, when based on SDT, appeared to be suitable for gamified rehearsal in a fun and enjoyable environment due to its facilitation of intrinsic motivation in its players.
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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 | 0,001 | 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 ».