Algorithms that Enhance Empathy? The Potential and Limitations of AI in SEL
Social-emotional learning (SEL) has been gaining momentum in school districts as educators recognize that teaching students how to manage emotions, build healthy relationships, and make responsible decisions is crucial to their overall success.¹ However, despite growing recognition of SEL’s importance, its adoption still remains a particularly tricky challenge.
Recent data shows that while nearly two-thirds of schools have implemented a formal SEL curriculum, a third has not. Among those without such programs, 46% of school leaders cite time as the biggest barrier to adoption. Even for those schools with a formal SEL curriculum, 72% report struggling to implement these lessons effectively due to time constraints.2
Given this overall struggle surrounding its implementation, how can we make SEL more doable amidst most districts’ busy schedules and limited resources? This is where AI can come into the picture. Taking advantage of machine learning may just be the solution we need to make SEL in education not only more feasible but perhaps more scalable and more personal as well.
References
- Stanford, L., & Meisner, C. (2023, July 27). Social-emotional learning persists despite political backlash. Education Week. https://www.edweek.org/leadership/social-emotional-learning-persists-despite-political-backlash/2023/07
- Prothero, A. (2024, April 16). What’s really holding schools back from implementing SEL? Education Week. https://www.edweek.org/leadership/whats-really-holding-schools-back-from-implementing-sel/2024/04
- Anonymous. (2023). Social Emotional Learning and AI. AI in Education. https://edtechbooks.org/ai_in_education/social_emotional_learning_and_ai
- Cipriano, C., Strambler, M. J., Naples, L. H., Ha, C., Kirk, M., Wood, M., Sehgal, K., Zieher, A. K., Eveleigh, A., McCarthy, M., Funaro, M., Ponnock, A., Chow, J. C., & Durlak, J. (2023). The state of evidence for social and emotional learning: A contemporary meta-analysis of universal school-based SEL interventions. Child Development, 94, 1181–1204. https://doi.org/10.1111/cdev.13968
- Collaborative for Academic, Social, and Emotional Learning. (n.d.). What does the research say? CASEL. https://casel.org/fundamentals-of-sel/what-does-the-research-say/
- Payton, J., Weissberg, R.P., Durlak, J.A., Dymnicki, A.B., Taylor, R.D., Schellinger, K.B., & Pachan, M. (2008). The positive impact of social and emotional learning for kindergarten to eighth-grade students: Findings from three scientific reviews. Chicago, IL: Collaborative for Academic, Social, and Emotional Learning
- Miles, N. C. (2024, June 23). Are you 80% angry and 2% sad? Why ‘emotional AI’ is fraught with problems. The Guardian. https://www.theguardian.com/technology/article/2024/jun/23/emotional-artificial-intelligence-chatgpt-4o-hume-algorithmic-bias
- Rhue, Lauren, Racial Influence on Automated Perceptions of Emotions (November 9, 2018). Available at SSRN: https://ssrn.com/abstract=3281765 or http://dx.doi.org/10.2139/ssrn.3281765
- Tatineni, S. (2019). Ethical considerations in AI and data science: Bias, fairness, and accountability. International Journal of Information Technology and Management Information Systems, 10, 11-20.
- Brännström, A., Wester, J., & Nieves, J. C. (2024). A formal understanding of computational empathy in interactive agents. Cognitive Systems Research, 85, 101203. https://doi.org/10.1016/j.cogsys.2023.101203
- Koenecke, A., Nam, A., Lake, E., Nudell, J., Quartey, M., Mengesha, Z., Toups, C., Rickford, J. R., Jurafsky, D., & Goel, S. (2020). Racial disparities in automated speech recognition. Proceedings of the National Academy of Sciences, 117(14), 7684-7689. https://doi.org/10.1073/pnas.1915768117
- Langreo, L. (2023, September 20). What AI training do teachers need most? Here’s what they say. Education Week. https://www.edweek.org/leadership/what-ai-training-do-teachers-need-most-heres-what-they-say/2023/09
- Ng, D.T.K., Leung, J.K.L., Su, J. et al. Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world. Education Tech Research Dev71, 137–161 (2023). https://doi.org/10.1007/s11423-023-10203-6
About the Author
Mariel Guevara
Mariel Guevara is a Junior Research Analyst at The Decision Lab. She is currently pursuing her MA degree in Developmental Psychology at Ateneo de Manila University. She has held several research positions in the past spanning different technology-mediated interventions tackling issues such as substance use prevention, mental health promotion, and civic engagement. She is especially passionate about making mental health services more accessible in the Philippines. In her free time she enjoys playing video games, going on nature walks, and playing sports.
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