The Integration of Generative AI Models in the (Social) Media Curriculum: Best Practices

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Access status: Embargo until 2026-11-01 , 978-3-032-18888-5_28.pdf (1.19 MB)

Publication date

2026-05-01

Authors

Monachesi, PaolaISNI 000000004651581X

Editors

Auer, Michael E.
Toth, Peter

Advisors

Supervisors

Document Type

Part of book

License

taverne

Abstract

Generative AI can change the way (social media) content is created affecting human behavior and society. The goal of this paper is to present best practices in the integration of GAI models in a social media course to prepare students for a future job market dominated by AI. The objective is to foster critical thinking, particularly around biases and hallucinations, and enhance creativity, while supporting personalized learning through feedback on demand driven by prompt engineering. Findings from a case study conducted in a bachelor-level course at Utrecht University are discussed. While GAI supported personalized learning and creativity, the study highlights the need for clear guidance to help students critically assess AI-generated content. Students, GAI and the lecturer contribute with a different role and level of knowledge towards an active learning experience, triggering the creation of a hybrid intelligence that merges human and machine capabilities, opening new possibilities for educational innovation.

Keywords

creativity, experiential learning, Generative AI models, job market, social media, Taverne, Control and Systems Engineering, Signal Processing, Computer Networks and Communications

Citation

Monachesi, P 2026, The Integration of Generative AI Models in the (Social) Media Curriculum : Best Practices. in M E Auer & P Toth (eds), Innovation via Collaborative Learning in Engineering Education - Proceedings of the 28th International Conference on Interactive Collaborative Learning, ICL 2025. Lecture Notes in Networks and Systems, vol. 1846 LNNS, Springer, pp. 289-300, 28th International Conference on Interactive Collaborative Learning, ICL 2025, Budapest, Hungary, 1/10/25. https://doi.org/10.1007/978-3-032-18888-5_28, conference