Development and Evaluation of a Serious Game Application to Engage University Students in Critical Thinking About Health Claims: Mixed Methods Study
Notice bibliographique
Résumé
BACKGROUND: Misleading health claims are widespread in the media, and making choices based on such claims can negatively affect health. Thus, developing effective learning resources to enable people to think critically about health claims is of great value. Serious games can become an effective learning resource in this respect, as they can affect motivation and learning. OBJECTIVE: This study aims to document how user insights and input can inform the concept and development of a serious game application in critical thinking about health claims in addition to gathering user experiences with the game application. METHODS: This was a mixed methods study in 4 successive phases with both qualitative and quantitative data collected in the period from 2020-2022. Qualitative data on design and development were obtained from 4 unrecorded discussions, and qualitative evaluation data were obtained from 1 recorded focus group interview and 3 open-ended questions in the game application. The quantitative data originate from user statistics. The qualitative data were analyzed thematically, and user data were analyzed using nonparametric tests. RESULTS: The first unrecorded discussion revealed that the students' (3 participants') assessment of whether a claim was reliable or not was limited to performing Google searches when faced with an ad for a health intervention. On the basis of the acquired knowledge of the target group, the game's prerequisites, and the technical possibilities, a pilot of the game was created and reviewed question by question in 3 unrecorded discussions (6 participants). After adjustments, the game was advertised at the Oslo Metropolitan University, and 193 students tested the game. A correlation (r=0.77; P<.001) was found between the number of replays and total points achieved in the game. There was no demonstrable difference (P=.07) between the total scores of students from different faculties. Overall, 36.3% (70/193) of the students answered the evaluation questions in the game. They used words such as "fun" and "educational" about the experiences with the game, and words such as "motivating" and "engaging" related to the learning experience. The design was described as "varied" and "user-friendly." Suggested improvements include adding references, more games and modules, more difficult questions, and an introductory text explaining the game. The results from the focus group interview (4 participants) corresponded to a large extent with the results of the open-ended questions in the game. CONCLUSIONS: We found that user insights and inputs can be successfully used in the concept and development of a serious game that aims to engage students to think critically about health claims. The mixed methods evaluation revealed that the users experienced the game as educational and fun. Future research may focus on assessing the effect of the serious game on learning outcomes and health choices in randomized trials.
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 | 0,019 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 ».