Escape Room Game Design Has Teaching Potential for Engaging With Misinformation Behaviors
Notice bibliographique
Résumé
A Review of: Cho, Y., Coward, C., Lackner, J., Windleharth, T. W., & Lee, J. H. (2023). The use of an escape room as an immersive learning environment for building resilience to misinformation. Journal of Librarianship and Information Science, 57(2), 524-538. https://doi.org/10.1177/09610006231208027 Objective – To evaluate the efficacy of game-based learning as a tool to teach misinformation recognition strategies, with an additional focus on cognitive bias, emotion, and attitudes related to misinformation. The authors also explore librarians’ responses to the use of the game as library educational programming to identify strengths and areas of concern in the game design process. Design – Mixed-methods user study combining participant survey data with inductive and deductive coding of qualitative data extracted from video recordings and open-ended questions. Setting – Washington State public libraries, primarily city and suburban locations. Subjects – 80 public library patrons and 6 public librarians in gameplay; 50 patrons additionally completed the optional survey. Methods – For this exploratory study, authors designed a misinformation escape room game based on interviews with librarians, college student input, and escape room developer collaboration. The authors recruited and trained public librarians to host the game and facilitate follow-up discussions, then recruited 80 participants via communication channels chosen by the public librarians, including newsletters, websites, and social media. The game was run 17 times across six locations. Game participation and discussions were recorded and transcribed. Following the game, participants were asked to complete a survey that included quantitative and qualitative responses, and librarians participated in a focus group after completing all of their game sessions. Researchers then coded the responses with both predefined and emergent codes. Main Results – Researchers found that participants were exposed to new misinformation techniques during the game, especially deepfake images and videos. Participants stated in the follow-up discussion that the use of misinformation created a sense of vulnerability, and they reflected on their individual responsibility regarding the spread of misinformation, including that once misinformation is shared, it cannot truly be unshared. As a result of the game, many participants highlighted the need for greater caution and critical thinking when engaging with information. Participants appreciated that the game was both fun and cooperative while affirming that it improved their awareness of misinformation techniques. Conclusion – The combination of immersive experience, collaborative play, and the post-game discussion led to better awareness of modern misinformation techniques and a willingness to reflect on the experience of engaging in misinformation. The post-game debrief is particularly important as it allows participants to form connections between the game and real-world misinformation experiences. Further research could pursue more conclusive evidence regarding patterns in misinformation experiences, or a longitudinal study could explore the game’s long-term effects on participants’ attitudes and behaviors.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,003 |
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 source (Gemma direct ou Codex distillé), 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 ».