Fostering pre-service teachers' social and emotional learning and professional identity through self-explanation-integrated CIDI-based GenAI digital storytelling.

Saved in:

Bibliographic Details
Title:	Fostering pre-service teachers' social and emotional learning and professional identity through self-explanation-integrated CIDI-based GenAI digital storytelling.
Authors:	Ma, Zhi-Qiang¹ mzq1213@jiangnan.edu.cn, You, Xin-Ya¹ 6232006014@stu.jiangnan.edu.cn, Zhang, Kai¹ zkican@163.com, Wu, Qing¹ wq6712@outlook.com, Hwang, Gwo-Jen^2,3,4 gjhwang.academic@gmail.com
Source:	Educational Technology & Society. Jul2026, Vol. 29 Issue 3, p286-313. 28p.
Subject Terms:	Generative artificial intelligence, Student teachers, *Social emotional learning, Professional identity, Human-artificial intelligence interaction, Introspection, Digital storytelling
Abstract:	The development of social and emotional learning (SEL) competence is vital for pre-service teachers' professional identity. Although generative AI (GenAI)-supported digital storytelling can promote this development, it may also induce cognitive load and technostress if not properly guided. Therefore, this study proposed a self-explanation-integrated CIDI (Clarify, Ideate, Develop, Implement) approach to facilitate SEL internalization and ease GenAI-related stress. It explored participants' perceptions of human-AI interaction through metaphor analysis and interviews. A total of 177 pre-service teachers were recruited for the study and assigned to either the S-CIDI (self-explanation-integrated CIDI) group (n = 90) or the C-CIDI (conventional CIDI) group (n = 87). Results showed that the S-CIDI model significantly improved learning performance and enhanced professional identity. Although social-emotional competence (SEC) improved in both groups, stress mindset increased across all conditions. Metaphor analysis and interviews revealed that the S-CIDI group exhibited weaker critical reflection on the AI-generated content, suggesting that caution is needed against the potential suppression of autonomous thinking by highly structured support. In metaphorical representations, both groups commonly described AI agents as "Assistants." The S-CIDI group preferred authoritative metaphors such as "Tutor," whereas the C-CIDI group tended to use metaphors like "Partner," emphasizing human-AI collaboration and co-creation concepts. The interviews further revealed that although both models promoted the development of social-emotional competence and professional identity, they showed differences in technology perception and agency construction, with the S-CIDI model potentially fostering over-reliance and diminishing critical autonomy. [ABSTRACT FROM AUTHOR]
	Copyright of Educational Technology & Society is the property of International Forum of Educational Technology & Society (IFETS) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database:	Education Research Complete

Description
Abstract:	The development of social and emotional learning (SEL) competence is vital for pre-service teachers' professional identity. Although generative AI (GenAI)-supported digital storytelling can promote this development, it may also induce cognitive load and technostress if not properly guided. Therefore, this study proposed a self-explanation-integrated CIDI (Clarify, Ideate, Develop, Implement) approach to facilitate SEL internalization and ease GenAI-related stress. It explored participants' perceptions of human-AI interaction through metaphor analysis and interviews. A total of 177 pre-service teachers were recruited for the study and assigned to either the S-CIDI (self-explanation-integrated CIDI) group (n = 90) or the C-CIDI (conventional CIDI) group (n = 87). Results showed that the S-CIDI model significantly improved learning performance and enhanced professional identity. Although social-emotional competence (SEC) improved in both groups, stress mindset increased across all conditions. Metaphor analysis and interviews revealed that the S-CIDI group exhibited weaker critical reflection on the AI-generated content, suggesting that caution is needed against the potential suppression of autonomous thinking by highly structured support. In metaphorical representations, both groups commonly described AI agents as "Assistants." The S-CIDI group preferred authoritative metaphors such as "Tutor," whereas the C-CIDI group tended to use metaphors like "Partner," emphasizing human-AI collaboration and co-creation concepts. The interviews further revealed that although both models promoted the development of social-emotional competence and professional identity, they showed differences in technology perception and agency construction, with the S-CIDI model potentially fostering over-reliance and diminishing critical autonomy. [ABSTRACT FROM AUTHOR]
ISSN:	11763647
DOI:	10.30191/ETS.202607_29(3).SP08