Evaluating an Adaptive Intervention in Collaboration Scripts Deconstructing Body Image Narratives in a Social Media Educational Platform

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Abstract

Social Media is an important disseminator of body image representations and the body cult. The growing popularity of social media among children and adolescents makes minors a vulnerable group to the internalization of body ideals and stereotypes. Developing educational interventions that provide adolescents with skills to better understand the body image in social media is therefore necessary to counteract the effects of deceitful representations and discourse. This paper evaluates an adaptive educational intervention to define the suitable approach to teach adolescents about body image and stereotyping in social media. In particular, the paper examines and compares three approaches to identify the dominant body image stereotype in students’ social media: The self-reported methods, the analysis of social preferences, and the use of xAPI to track users’ behavior. Results showed that the use of xAPI combined with self-reported answers can provide better input from adolescents’ preferences. Moreover, it allows the automatic distribution of suitable counter-narratives to students participating in computer-supported collaborative learning activities embedded in an educational social media platform.

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Lobo-Quintero, R., Theophilou, E., Sánchez-Reina, R., & Hernández-Leo, D. (2022). Evaluating an Adaptive Intervention in Collaboration Scripts Deconstructing Body Image Narratives in a Social Media Educational Platform. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13632 LNCS, pp. 205–217). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-20218-6_14

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