Game-Based Social-Emotional Learning for Youth: School-Based Qualitative Analysis of Brain Agents
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".