Vol. 16 No. 2 (2025): MEDIA EDUCATION – Studi, ricerche e buone pratiche
Best practices

IA e progettazione formativa: una partnership tra intelligenza artificiale e intelligenza umana

PDF
  • Serena Marrandino
Serena Marrandino
Future Education Modena, Italia
DOI: https://doi.org/10.36253/me-18674

Published 2025-12-30

Keywords

  • Artificial Intelligence,
  • instructional design,
  • ADDIE Model,
  • generative AI,
  • human-AI collaboration

Copyright (c) 2025 Serena Marrandino

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

This paper presents a proposal for using Artificial Intelligence (AI) as a support tool for instructional design, targeting learning professionals, instructional designers, HR, and teachers. The aim is to offer practical insights for integrating AI consciously, moving beyond mere automation to embrace the concept of a cognitive “teammate.” The article analyzes AI’s strengths (divergent thinking, predictive capabilities) and risks (bias, homogenization), proposing mitigation strategies based on human supervision. Finally, it illustrates the practical application of AI across the ADDIE model phases, demonstrating how the synergy between human and artificial intelligence can enhance the creative and decision-making processes in training.

PDF

References

  1. Alster, K. (2024). The future of instructional design: 2024 survey insights. Synthesia. https://www.synthesia.io/post/state-of-instructional-design-survey
  2. Bisbee, J., Clinton, J. D., Dorff, C., Kenkel, B., & Larson, J. M. (2024). Synthetic replacements for human survey data? The perils of large language models. Political Analysis. https://www.cambridge.org/core/journals/political-analysis/article/synthetic-replacements-for-human-survey-data-the-perils-of-large-language-models/B92267DC26195C7F36E63EA04A47D2FE
  3. Hardman, P. (2024). The post-AI instructional designer: How the ID role is changing, and what this means for your key skills, roles & responsibilities. Dr. Philippa Hardman Substack. https://drphilippahardman.substack.com/p/the-post-ai-instructional-designer
  4. Hardman, P., Dell’Acqua, F., Ayoubi, C., Lifshitz-Assaf, H., Sadun, R., Mollick, E. R., Mollick, L., Han, Y., Goldman, J., Nair, H., Taub, S., & Lakhani, K. R. (2024). Structured prompting for educators: Experiments in how to get the best out of your favourite generative AI tools. Dr. Philippa Hardman Substack. https://drphilippahardman.substack.com/p/structured-prompting-for-educators
  5. Hewitt, L., Ashokkumar, A., Ghezae, I., & Willer, R. (2024). Predicting results of social science experiments using large language models. https://samim.io/dl/Predicting%20results%20of%20social%20science%20experiments%20using%20large%20language%20models.pdf
  6. Hubert, K. F., Awa, K. N., & Zabelina, D. L. (2024). The current state of artificial intelligence generative language models is more creative than humans on divergent thinking tasks. Scientific Reports, 14, 3440. https://www.researchgate.net/publication/378127702
  7. Janssen, M., Brous, P., Estevez, E., Barbosa, L. S., & Janowski, T. (2020). Data governance: Organizing data for trustworthy artificial intelligence. Government Information Quarterly. https://www.sciencedirect.com/science/article/abs/pii/S0740624X20302719
  8. Keppler, S., Sinchaisri, W. P., & Snyder, C. (2024). Backwards planning with generative AI: Case study evidence from US K-12 teachers. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4924786
  9. Kim, J., Shin, S., Bae, K., Oh, S., Park, E., & del Pobil, A. P. (2020). Can AI be a content generator? Effects of content generators and information delivery methods on the psychology of content consumers. Telematics and Informatics. https://www.sciencedirect.com/science/article/abs/pii/S0736585320301118
  10. Learn Worlds. (2024). Master ChatGPT for course creation with the art of prompting [E-book]. https://www.learnworlds.com/master-chat-gpt-ebook/
  11. Learn Worlds. (2024). Maximizing your course success: Utilizing ChatGPT & prompt engineering [E-book]. https://www.learnworlds.com/chat-gpt/
  12. Luong, A., Kumar, N., & Lang, K. R. (2020). Algorithmic decision-making: Examining the interplay of people, technology, and organizational practices through an economic experiment. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3529679
  13. Qin, S., Jia, N., Luo, X., Liao, C., & Huang, Z. (2023). Perceived fairness of human managers compared with artificial intelligence in employee performance evaluation. Journal of Management Information Systems. https://www.tandfonline.com/doi/full/10.1080/07421222.2023.2267316
  14. Raghu, M., Blumer, K., Corrado, G., Kleinberg, J., Obermeyer, Z., & Mullainathan, S. (2019). The algorithmic automation problem: Prediction, triage, and human effort. https://www.semanticscholar.org/paper/The-Algorithmic-Automation-Problem%3A-Prediction%2C-and-Raghu-Blumer/f5ee2ef5672122aa6a82f91e68cfcfcc8f229628