ALGORITHMIC NARRATIVES AND AFFECTIVE EXPRESSION: A STUDY ON THE IMPACT OF GENERATIVE ARTIFICIAL INTELLIGENCE ON THE EMOTIONAL WRITING OF STUDENTS AND FUTURE TEACHERS
Abstract
This study investigates the impact of generative artificial intelligence on emotional expression and narrative construction of the self in lower secondary school students and pre-service special education teachers. Framed within the perspective of Digital Affective Literacy, the research adopted a quasi-experimental mixed-methods design based on a within-subject comparison between narratives produced without AI and narratives generated with AI through participant-created prompts. The sample included 50 lower secondary school students and 98 pre-service special education teachers. Data collection integrated the Tromsø Social Intelligence Scale, the Emotional Expressivity Scale and the Berkeley Expressivity Questionnaire. The analysis considered emotional richness, sentiment polarity and narrative depth, operationalised through reflexivity, agency and relational complexity, together with perceived authenticity and narrative authorship. Results show that AI-supported narratives were longer, more emotionally explicit and more structured, while also revealing a tension between expressive amplification and possible narrative standardisation.
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References
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa
Bruner, J. (1990). Acts of meaning; four lectures on mind and culture. Harvard University Press.
CASEL. (2020). CASEL’S SEL. Framework: What are the core competence areas and where are they promoted? In Collaborative for Academic, Social, and Emotional Learning.
Cheng, Y., Fan, Y., Li, X., Chen, G., Gašević, D., & Swiecki, Z. (2025). Asking generative artificial intelligence the right questions improves writing performance. Computers and Education: Artificial Intelligence, 8, 100374. https://doi.org/10.1016/j.caeai.2025.100374
Creswell, J. W. (2007). Designing and Conducting Mixed Methods Research. Australian and new zealand journal of public health, 31(4).
Creswell, J. W., & Plano Clark, V. L. (2017). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
Gross, J. J., & John, O. P. (1997). Revealing feelings: Facets of emotional expressivity in self-reports, peer ratings, and behavior. Journal of Personality and Social Psychology, 72(2), 435-448. https://doi.org/10.1037/0022-3514.72.2.435
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesgn.
Immordino-Yang, M. H., & Damasio, A. (2007). We feel, therefore we learn: The relevance of affective and social neuroscience to education. Mind, Brain, and Education, 1(1), 3-10. https://doi.org/10.1111/j.1751-228X.2007.00004.x
Kring, A. M., Smith, D. A., & Neale, J. M. (1994). Individual differences in dispositional expressiveness: Development and validation of the Emotional Expressivity Scale. Journal of Personality and Social Psychology, 66(5), 934-949. https://doi.org/10.1037/0022-3514.66.5.934
Law, L. (2024). Application of generative artificial intelligence (GenAI) in language teaching and learning: A scoping literature review. Computers and Education Open, 6, Article 100174. https://doi.org/10.1016/j.caeo.2024.100174
Li, B., Tan, Y. L., Wang, C., & Lowell, V. (2025). Two years of innovation: A systematic review of empirical generative AI research in language learning and teaching. Computers and Education: Artificial Intelligence, 100445.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
McAdams, D. P. (2001). The psychology of life stories. Review of General Psychology, 5(2), 100-122. https://doi.org/10.1037/1089-2680.5.2.100
Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice (4th ed.). SAGE Publications.
Park, J., Teo, T., & Lim, C. P. (2025). A systematic literature review of generative artificial intelligence literacy education in schools. Computers and Education: Artificial Intelligence, 8, Article 100374.
Riessman, C. K. (2008). Narrative methods for the human sciences. SAGE Publications.
Roe, J., & Perkins, M. (2024). Generative AI and agency in education: A critical scoping review and thematic analysis. arXiv. https://arxiv.org/abs/2411.00631
Shi, Y., Yu, K., Dong, Y. & Chen, F. (2025). Large language models in education: A systematic review of empirical applications, benefits, and challenges. Computers and Education: Artificial Intelligence, 8, Article 100399.
Silvera, D. H., Martinussen, M., & Dahl, T. I. (2001). The Tromsø Social Intelligence Scale, a self-report measure of social intelligence. Scandinavian Journal of Psychology, 42(4), 313-319. https://doi.org/10.1111/1467-9450.00242
DOI: https://doi.org/10.32043/gsd.v10i4.1906
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Italian Journal of Health Education, Sports and Inclusive Didactics
