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Enregistrement W2028700992 · doi:10.1111/j.1365-2929.2006.02595.x

Games as active learning strategies: a faculty development workshop

2006· article· en· W2028700992 sur OpenAlexaffabout
Kalyani Premkumar, Deirdre Bonnycastle

Notice bibliographique

RevueMedical Education · 2006
Typearticle
Langueen
DomainePsychology
ThématiqueEducational Games and Gamification
Établissements canadiensUniversity of Saskatchewan
Organismes subventionnairesnon disponible
Mots-clésInteractivityContext (archaeology)Variety (cybernetics)Medical educationActive learning (machine learning)TeamworkReading (process)Computer sciencePsychologyMultimediaMathematics educationMedicineArtificial intelligence

Résumé

récupéré en direct d'OpenAlex

Context and setting‘Games as Active Learning Strategies’ was 1 of 7 active learning workshops offered to faculty at the College of Medicine, University of Saskatchewan, Saskatoon, Canada. The workshop was interactive and conducted in a computer laboratory. Why the idea was necessary There is evidence to show that games, defined by some as ‘fun with a purpose’, foster active learning, allow for interactivity, promote collaboration, peer-learning and teamwork, and increase motivation. Despite their potential to enhance learning, there is very little use of games in the teaching and learning of medicine. We therefore designed and developed a workshop that would enable participants to create a game using self- generated questions. What was done A literature review was completed to identify: the rationale for using games; different types of games available; and the use and examples of games in medicine. We then designed and developed the 2.5-hour interactive workshop. The objectives were to: discuss the rationale for using games; provide examples of a variety of games used effectively in medical education, and create game(s) using PowerPoint. (PowerPoint was used because most faculty use it in day-to-day teaching and free templates are available.) We were excited by the response to the workshop. Participants included representatives from physical therapy, continuing professional learning, pathology, nursing, family medicine and the Lung Association. Participants were given a pre-reading package with review articles on games and were asked to bring 10 multiple-choice questions. During the workshop, different types of games were viewed and the participants then discussed theory behind their use, how each type can be used in its specific setting and cautions to bear in mind while using the games. Next, following a demonstration on how to create a game using Powerpoint templates, the participants created their own games. Despite varying levels of familiarity with the software, all participants were able to create a game. At the end of the workshop, each participant received a CD containing numerous Powerpoint templates and links to examples and articles describing the use of games. Evaluation of results and impact We administered a workshop evaluation survey consisting of 13 open-ended and 10-point Likert scale questions. All participants strongly agreed (9–10/10) that the workshop was well organised and facilitated, that they learnt a lot from other participants and that their expectations were met. Participants indicated that they planned to use this information in their teaching. On follow-up we learnt that these games were being used in reviewing 2 pathology courses, during a microbiology lecture, and obstetrics course in continuing education, and for learning new information by community-based faculty. There have been requests for more such workshops at the medical college and university teaching and learning centre, a national conference and even an international venue. Whilst we are heartened by the outcome, we are aware and have reiterated to the participants the danger of the medium becoming more memorable than the message. The ultimate worth of using games is in the learning that emanates and the value of the information for practice.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,741
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

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.

Tête enseignante Opus0,023
Tête enseignante GPT0,385
Écart entre enseignants0,362 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations15
Publié2006
Routes d'admission2
Résumé présentoui

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