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Social-Emotional Learning and Generative AI: A Critical Literature Review and Framework for Teacher Education

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Title: Social-Emotional Learning and Generative AI: A Critical Literature Review and Framework for Teacher Education
Language: English
Authors: Danah Henriksen (ORCID 0000-0001-5109-6960), Edwin Creely (ORCID 0000-0002-5009-4047), Natalie Gruber (ORCID 0000-0001-7256-7610), Sean Leahy (ORCID 0000-0001-6840-371X)
Source: Journal of Teacher Education. 2025 76(3):312-328.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 17
Publication Date: 2025
Document Type: Journal Articles
Information Analyses
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Social Emotional Learning, Artificial Intelligence, Computer Software, Risk, Preservice Teachers, Teacher Education Programs, Technology Integration, Technological Literacy, Pedagogical Content Knowledge, Privacy, Guidelines, Ethics, Bias, Individualized Instruction, Faculty Development, Cultural Awareness, Guidance, Teaching Methods, Research Reports
DOI: 10.1177/00224871251325058
ISSN: 0022-4871
1552-7816
Abstract: This article provides a critical thematic literature review that explores the intersection of generative artificial intelligence (GenAI) and social-emotional learning (SEL), analyzing its implications for teacher education. GenAI offers promising applications for enhancing SEL competencies such as self-awareness, empathy, and social skills through tools like real-time emotional feedback and personalized learning experiences. However, the integration of GenAI into SEL also presents significant challenges, including risks of depersonalization, algorithmic bias, and privacy concerns. This paper introduces a conceptual framework designed to prepare both pre-service and in-service teachers to navigate these complexities, emphasizing ethical considerations, human oversight, and cultural sensitivity. The framework highlights strategies to operationalize cultural sensitivity within AI systems, recognizing the limitations of current technologies in accounting for diverse social and emotional norms. By addressing both opportunities and risks, we aim to provide a balanced analysis of GenAI's potential in SEL as well as guidance for teacher education programs.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1469503
Database: ERIC
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  Data: Social-Emotional Learning and Generative AI: A Critical Literature Review and Framework for Teacher Education
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  Data: <searchLink fieldCode="AR" term="%22Danah+Henriksen%22">Danah Henriksen</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5109-6960">0000-0001-5109-6960</externalLink>)<br /><searchLink fieldCode="AR" term="%22Edwin+Creely%22">Edwin Creely</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-5009-4047">0000-0002-5009-4047</externalLink>)<br /><searchLink fieldCode="AR" term="%22Natalie+Gruber%22">Natalie Gruber</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-7256-7610">0000-0001-7256-7610</externalLink>)<br /><searchLink fieldCode="AR" term="%22Sean+Leahy%22">Sean Leahy</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6840-371X">0000-0001-6840-371X</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Teacher+Education%22"><i>Journal of Teacher Education</i></searchLink>. 2025 76(3):312-328.
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: 17
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Social+Emotional+Learning%22">Social Emotional Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Software%22">Computer Software</searchLink><br /><searchLink fieldCode="DE" term="%22Risk%22">Risk</searchLink><br /><searchLink fieldCode="DE" term="%22Preservice+Teachers%22">Preservice Teachers</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Education+Programs%22">Teacher Education Programs</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Integration%22">Technology Integration</searchLink><br /><searchLink fieldCode="DE" term="%22Technological+Literacy%22">Technological Literacy</searchLink><br /><searchLink fieldCode="DE" term="%22Pedagogical+Content+Knowledge%22">Pedagogical Content Knowledge</searchLink><br /><searchLink fieldCode="DE" term="%22Privacy%22">Privacy</searchLink><br /><searchLink fieldCode="DE" term="%22Guidelines%22">Guidelines</searchLink><br /><searchLink fieldCode="DE" term="%22Ethics%22">Ethics</searchLink><br /><searchLink fieldCode="DE" term="%22Bias%22">Bias</searchLink><br /><searchLink fieldCode="DE" term="%22Individualized+Instruction%22">Individualized Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Faculty+Development%22">Faculty Development</searchLink><br /><searchLink fieldCode="DE" term="%22Cultural+Awareness%22">Cultural Awareness</searchLink><br /><searchLink fieldCode="DE" term="%22Guidance%22">Guidance</searchLink><br /><searchLink fieldCode="DE" term="%22Teaching+Methods%22">Teaching Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Research+Reports%22">Research Reports</searchLink>
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  Data: 10.1177/00224871251325058
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  Data: 0022-4871<br />1552-7816
– Name: Abstract
  Label: Abstract
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  Data: This article provides a critical thematic literature review that explores the intersection of generative artificial intelligence (GenAI) and social-emotional learning (SEL), analyzing its implications for teacher education. GenAI offers promising applications for enhancing SEL competencies such as self-awareness, empathy, and social skills through tools like real-time emotional feedback and personalized learning experiences. However, the integration of GenAI into SEL also presents significant challenges, including risks of depersonalization, algorithmic bias, and privacy concerns. This paper introduces a conceptual framework designed to prepare both pre-service and in-service teachers to navigate these complexities, emphasizing ethical considerations, human oversight, and cultural sensitivity. The framework highlights strategies to operationalize cultural sensitivity within AI systems, recognizing the limitations of current technologies in accounting for diverse social and emotional norms. By addressing both opportunities and risks, we aim to provide a balanced analysis of GenAI's potential in SEL as well as guidance for teacher education programs.
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  Data: 2025
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  Data: EJ1469503
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        Value: 10.1177/00224871251325058
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      – Text: English
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    Subjects:
      – SubjectFull: Social Emotional Learning
        Type: general
      – SubjectFull: Artificial Intelligence
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      – SubjectFull: Computer Software
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      – TitleFull: Social-Emotional Learning and Generative AI: A Critical Literature Review and Framework for Teacher Education
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