Game-Based Social-Emotional Learning for Youth: School-Based Qualitative Analysis of Brain Agents
Notice bibliographique
Résumé
Background: Adverse childhood experiences such as violence, substance use, and family disruption disproportionately affect youth in urban communities, increasing the risk of emotional and behavioral challenges. Social-emotional learning (SEL) and trauma-informed programming are effective strategies for mitigating these effects, fostering resilience, and promoting mental well-being. Game-based learning is a promising, engaging method for delivering SEL content. STRYV365 developed Brain Agents, a trauma-informed, game-based SEL intervention aimed at improving emotional regulation, coping strategies, and interpersonal skills among students in grades 5 through 9. Objective: This study explored students' experiences with and perceptions of Brain Agents, evaluating its effectiveness in fostering SEL skills and resilience across 4 diverse urban schools in Milwaukee, Wisconsin. Methods: A cluster-randomized, incomplete block factorial crossover design was implemented from 2022-2024. Of 1626 eligible students, 329 (20%) had caregiver consent and student assent. Among these, 180 students in grades 5-9 played Brain Agents at school over 4-5 weeks, for an average of 10 sessions and 23 minutes per session. SEL-related outcomes were assessed using surveys, focus groups, and interviews. Qualitative data were analyzed using Dedoose software, with thematic coding conducted by multiple coders to ensure reliability. Results: Student demographics included 189/321 (58.9%) Black, 112/321 (34.9%) White, and 221/321 (68.8%) from economically disadvantaged backgrounds. Baseline surveys of 277 children revealed that 202 (72.9%) of students had experienced the death of someone close, 147 (53.1%) had a close contact incarcerated, and 39 (14.1%) reported feeling nervous or anxious daily. Strengths included 230 (83.0%) students reporting life satisfaction and 183 (66.1%) able to calm down when upset. Game performance data from 328 students indicated varying levels of achievement, with a median of 3 (IQR 1.5-4) missions completed, 4 (IQR 2-6) stars earned, 8 positive energies collected, and 2 (IQR 1-2.5) crew members rescued. Grades 7-8 had the highest engagement, while grade 9 students had the lowest participation. Qualitative analysis from 62 participants identified 8 core themes: qualities of most pride, neighborhood relationships, challenges in life, emotions associated with loss of control, coping strategies, future goals, experiences with Brain Agents, and suggestions to improve the game. Students most frequently cited anger as a cause of emotional dysregulation and named coping strategies such as self-calming, asking for help, and perseverance. Feedback on Brain Agents highlighted improved focus, emotional control, and critical thinking, with younger students more positively engaged. Suggested improvements included better graphics, more customization, and cooperative play. Conclusions: Brain Agents was positively received by students, particularly those in earlier grades, and demonstrated potential as an effective trauma-informed SEL tool. The findings support the role of game-based interventions in enhancing resilience and emotional intelligence among youth exposed to adversity. Broader implementation may extend benefits to diverse student populations and settings.
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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 | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| 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 ».