Cracking the Code of Electronic Games: Some Lessons for Educators
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Notice bibliographique
Résumé
Background/Context Students’ ready engagement in electronic games and the relative ease with which they sometimes learn complex rules have intrigued some educators and learning researchers. There has been growing interest in studying electronic gaming with the aim of trying to work out how learning principles that are evident in games can be harnessed to make everyday academic learning more engaging and productive. Many studies of students’ learning while gaming have yielded recommendations for teaching and learning in regular classrooms. Purpose/Objective/Research Question/Focus The intent of this work is to describe various ways in which students’ ready engagement in, and quick learning when playing, electronic games have been assumed to provide useful guidance to educators. This goal is pursued by means of analysis of the relevant research and the prescriptions for classroom teaching and learning that have emerged it. Close critical examination of these attempts to infer educational practices from electronic gaming yields three general strategies that have been pursued. The focus of this study has been on evaluating the relative value of these three general strategies. Research Design This is an analytic article that provides a description of an array of attempts to derive educational principles from the perceived success of students’ learning while they are engaged in electronic games, a meta-analytic organization of these attempts into three general categories, and an evaluation of each of these categories’ success in contributing to education or failure to do so. Conclusions/Recommendations The analysis leads to the conclusion that the three main approaches to understanding the connection between gaming and education have included, first, seeing games as teaching desirable learning skills through the simple act of playing; second, a focus on the integration of curriculum content into games; and, third, an effort to abstract learning principles embedded in electronic games and applying these to educational content. Close examination of each of these three approaches in turn leads to the conclusion that the third approach is the one that holds the greatest potential value for educational practice.
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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 | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,001 |
| 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