Synthetic media, generative AI, and Barbie in education

Abstract

Since the mass adoption of ChatGPT, educators have been prompted to rethink text assessment practices and respond to mounting concerns about academic integrity (Dawson et al., 2024; Nikolic et al., 2024). Critical, meaningful learning is often at odds with performative assessment models that prioritise measurable outputs (Wise et al., 2024). At the same time, social media and mainstream narratives promote AI promises of personalised learning and educational transformation, glossing over deeper ethical questions and its potential dehumanising effects (Bender, 2024). Yet the philosophical, social and ethical aspects of generative artificial intelligence (GenAI) use in education are more important than ever (Sidorkin, 2024). The practical implications are substantial as GenAI implementations frequently emphasise technological capabilities and operational efficiency over critical examination of learning theories, student autonomy, and the pedagogical implications of transferring educational authority to AI systems (Zawacki-Richter et al., 2024). Rather than viewing GenAI as purely transformative or destructive, it may be seen as a constructed vision that reflects social, cultural assumptions about personalisation and agency (Rahm, 2023).

Moreover, the AI technology industry aims to “create progressively more complex simulacra of the human body and its surroundings” (Ferreira et al., 2023, p. 10), which has profound implications for society and education. This research uses metaphor to examine how synthetic media, such as generative AI, may reshape teaching practice and educational relationships (Vallis et al., 2025). Examining GenAI in education through the cultural lens of ‘Barbie’ shows how evolving attitudes towards empowerment and authenticity are mutually shaping technology’s role in learning (Vallis, 2025). The hyperreal setting of ‘Barbieland’ is presented as analogous to the promises of individualised empowerment in educational technology, which often mask superficial solutions that reinforce existing inequalities (Baker & Hawn, 2022). In the 2023 film, Barbie evolves from plastic figure to ‘real’ human, paralleling the accelerating development of synthetic media and AI-generated video, which may disconnect teachers and students from embodied human interactions in education. This blurring of the real and artificial challenges our understanding of authenticity (Vallis, 2024). Educational uses of AI, where the focus on efficiency and personalisation comes at the expense of deeper pedagogical intent (Baker & Hawn, 2022), risk replicating an inauthentic consumer-oriented ‘Barbie’ logic that prioritises appearance over genuine connection.

The presentation introduces ‘(Re)generative Education’ as an alternative concept that emphasises adaptive, collaborative approaches to human-AI interaction in learning environments. Western-centric narratives of technological empowerment are contrasted with an Indigenous perspective from Ellen van Neerven’s ‘Water’ (2014) to reveal how dominant cultural narratives limit our imagination of human-AI collaboration in education. More holistic evaluation criteria and collaborative design are needed when integrating AI, to avoid the rigid either-or thinking sometimes found in education technology discussions (Matthews, 2021). This includes educational development that build critical technological fluency rather than operational competence alone and creating mechanisms for ongoing feedback. Connecting cultural analysis to operational practice supports more thoughtful, equitable, and pedagogically sound approaches to AI integration that honour diverse ways of knowing while still making purposeful use of its technological affordances.