eaSEL: Promoting Social-Emotional Learning and Parent-Child Interaction through AI-Mediated Content Consumption
Open accessAbstract
As children increasingly consume media on devices, parents look for ways this usage can support learning and growth, especially in domains like social-emotional learning. We introduce eaSEL, a system that (a) integrates social-emotional learning (SEL) curricula into children's video consumption by generating reflection activities and (b) facilitates parent-child discussions around digital media without requiring co-consumption of videos. We present a technical evaluation of our system's ability to detect social-emotional moments within a transcript and to generate high-quality SEL-based activities for both children and parents. Through a user study with N=20 parent-child dyads, we find that after completing an eaSEL activity, children reflect more on the emotional content of videos. Furthermore, parents find that the tool promotes meaningful active engagement and could scaffold deeper conversations around content. Our work paves directions in how AI can support children's social-emotional reflection of media and family connections in the digital age.
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A second focus is emotion recognition and regulation in virtual environments, including the development of prosocial behavior and empathy.
“Asecond focus is emotion recognition and regulation in virtual environments, including the development of prosocial behavior and empathy [121,122].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [121]
Section 2.2 (p. 2) describes digital-media approaches to children's emotion processing and regulation. The SEL skills listed in Appendix B (pp. 23–24) include recognizing others' feelings, empathy, and helping. But the study concerns activities alongside children's videos, not virtual environments, and its Conclusion (p. 15) reports increased emotion-word use and reflection—not demonstrated development of prosocial behavior or empathy. (LLM, conf=0.84)
Experimental — accuracy not yet measuredA third line of research leverages AI to strengthen parent-child interaction and family collaboration, reinforcing emotional bonds, empathy, and parental involvement.
“A third line of research leverages AI to strengthen parent-child interaction and family collaboration, reinforcing emotional bonds, empathy, and parental involvement [121,123].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [121]
Section 6.2 (p. 13) describes eaSEL’s prompts as supporting parent involvement and parent-child bonding, and the Discussion (p. 14) says parents perceived that they could deepen family conversations. The paper does not show that eaSEL increased children’s empathy or establish a measured improvement in emotional bonds; its discussion of higher empathy refers to earlier studies (Section 2.3, p. 2). (LLM, conf=0.84)
Experimental — accuracy not yet measuredSome studies integrate social-emotional and interdisciplinary tasks, where AI provides focused evaluations and follow-up recommendations that help students refine learning strategies and strengthen self-regulation.
“Some studies also integrate social-emotional and interdisciplinary tasks, where AI provides focused evaluations and follow-up recommendations that help students refine learning strategies and strengthen self-regulation [121,129,151].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [121]
The Introduction (p. 1) describes AI-generated social-emotional learning activities for children and follow-up conversation starters for parents. The Conclusion (p. 15) reports improved social-emotional reflection, but the paper does not describe AI providing focused evaluations of students or recommendations to refine learning strategies, nor does it establish strengthened self-regulation. (LLM, conf=0.87)
Experimental — accuracy not yet measuredParents and teachers raise questions about age appropriateness, ethical risk, and the costs of integration.
“Parents and teachers likewise raise questions about age appropriateness, ethical risk, and the costs of integration [103,116,121,123,134].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [121]
Section 4.5 (p. 9) reports parent concerns about age-inappropriate language and themes, and calls for child-focused content-safety safeguards. Section 7.2 (p. 14) discusses minimizing parent effort, but the paper does not report teachers raising these questions or establish costs of integration. (LLM, conf=0.86)
Experimental — accuracy not yet measuredAt the relational level, AI can foster more positive peer affect and teamwork and is positively appraised by parents and teachers for enabling parent-child dialogue and instructional support.
“At the relational level, AI can foster more positive peer affect and teamwork [107,120] and is positively appraised by parents and teachers for enabling parent-child dialogue and instructional support [71,121,123].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [121]
The Discussion (p. 14) reports parents’ positive evaluations of eaSEL for supporting children’s learning and scaffolding deeper family conversations. The study procedure (p. 10) describes feedback from parents, not teachers, so teacher approval is not supported by this source. The peer-affect and teamwork clause is attached to different citations. (LLM, conf=0.88)
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References 86 · Cited by 24
Research works printed but not linked: 7
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- Authors
- Shen, J. J., King Chen, J., Findlater, L., & Dietz Smith, G.
- Affiliations
- MIT Media Lab (US)
- Apple, Seattle, Washington, USA
- Apple (United States) (US)
- Venue
- Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2025-04-25
- Pages
- 1-18
- OpenAlex
- W4406975823
- Cited by
- 24
- References
- 86
- Citations by year
- 2026: 16 · 2025: 8
- FWCI
- 274.84
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- arXiv (Cornell University)
- Topics
- Social Sciences › Education › Child Development and Digital Technology
- Social Sciences › Education › Early Childhood Education and Development
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- social-emotional learning, parent-child interaction, children's media use, emotional reflection, parent-child dyads
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