XXII Conference of the Italian Chapter of AIS
Emerging technologies for transforming organisations and society
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Teaching with AI in higher education: from insight to impact

Call for contributions to the workshop

  • Duration: 2,5 hours
  • Date: 17th October 2025, 10.30am-12.30pm
  • Submission deadline: 30th September 2025
  • Notification of acceptance: by 7th October 2025
  • Organizing co-chairs: Leonardo Caporarello, Roberta Cuel, Aurelio Ravarini

Introduction

Generative AI is profoundly transforming pedagogical practices and, in the long term, strategic planning in higher education. A recent systematic review (TechTrends, June 2025) maps the rapid adoption of GenAI across teaching, assessment, and curriculum design. Similarly, Shata & Hartley (2025) highlight persistent gaps in frameworks and guidelines for effectively adopting GenAI in higher education, calling for interdisciplinary use cases and robust policy development.
Emerging research highlights the importance of ethical considerations, continuous professional development, and institutional support for AI adoption (Caporarello (ed.), 2025; Caporarello, 2025; Fukami, 2025 in press). Only a few and very recent surveys among instructors show that while trust in GenAI tools varies, distrust also exists and often is associated with a fear of replacement. The research on faculty experiences suggests that GenAI adoption is shaped by a wide range of factors including job structure, academic freedom, ethical ambiguity, and institutional support collectively influence educators’ propensity to either embrace or resist the utilization of these technological tools (Awadallah Alkouk & Khlaif, 2024; Ivanov et al., 2024). Interestingly, students appear less inclined to prefer AI-based replacements, except in cases where faculty continue to rely on outdated, traditional teaching methods (Caporarello & Trabskaia, under review). These insights underscore the importance of building trust and evidence-based guidelines.

Meanwhile, studies show that students value AI tutors for their accessibility and support, though ethical ambiguity and unclear institutional policies hinder widespread and effective usage. In the UK, nearly all students now use GenAI in coursework, prompting universities to redesign teaching models, assessments, train staff, and share best practices to ensure academic integrity and pedagogical value (Adams, 2025; Zhang et al., 2025).
This workshop aims to advance these discussions by bringing together higher education scholars and educators to critically engage with the pedagogical, ethical, and institutional dimensions of AI adoption in teaching practices, from instructional design to policy development. 

Objectives

  1. Share concrete experiences and practices in the use of AI in teaching and learning across all levels (undergraduate to executive education)
  2. Showcase live or demonstrative examples of AI-supported educational methodology
  3. Present emerging conceptual work on AI-supported pedagogy, feedback and curriculum design
  4. Facilitate critical comparison of AI-enabled teaching practices across diverse contexts
  5. Co-create an actionable teaching agenda on AI-enabled pedagogy that informs both classroom practice and future research directions

Target Participants

Diversity of perspectives, scenarios, and settings is a foundational value of this workshop. We welcome participation from:

  • Faculty experimenting the integration of Ai into their teaching designs
  • Doctoral candidates conducting empirical or theoretical research on AI in education
  • Learning designers and EdTech professionals
  • Researchers studying AI adoption and its impact in educational contexts

Participation is free of charge for all the conference attendees.

Submission Guidelines

We invite the following types of submission:

  1. Experience Reports (max 2 pages): detailed case studies on the use of AI use in educational settings
  2. Position Papers (max 2 pages): conceptual models, ethical frameworks, or normative analyses
  3. Research-in-Progress Abstracts (max 1 page): early-stage empirical or theoretical investigations of the use of AI in education

Submissions should be in English, follow APA format, and be sent in PDF format by email to the organizing co-chairs: leonardo.caporarello@unibocconi.it, roberta.cuel@unitn.it, aravarini@liuc.it.

Publication opportunity

All contributions will be evaluated and considered for an online publication with ISBN. We are also exploring further publication opportunities, which will be announced during the workshop.

Timeline

  • 30th September 2025, submission deadline
  • 7th October 2025, notification of acceptance
  • 17th October 2025 morning, workshop at ITAIS 2025

Contact

For inquiries or additional information, feel free to reach out to any of the organizing chairs.

References

  • Adams, R. (2025, February 26). UK universities warned to stress-test assessments as 92% of students use AI. The Guardian. https://www.theguardian.com/education/2025/feb/26/uk-universities-warned-to-stress-test-assessments-as-92-of-students-use-ai
  • Awadallah Alkouk, W., & Khlaif, Z. N. (2024). AI-resistant assessments in higher education: Practical insights from faculty training workshops. Frontiers in Education, 9, 1499495. https://doi.org/10.3389/feduc.2024.1499495
  • Caporarello, L. (ed.) (2025). AI in education – The urgency of the now. Real-world applications, challenges, and lessons for educators. Independently published.
  • Caporarello, L. (2025). Who wants to learn forever? Bocconi University Press.
  • Caporarello, L., & Trabskaia, I. (under review). Fear of educators’ replacement by AI: Students’ perspective in the management education settings. In Maheshkar, C., & Coelho, A. (Eds.), Perspectives and challenges of management education. Nova Science Publishers.
  • Chaieb, M.,Cuel, R., and Bouzaabia, R., (under review). Reconceptualizing of GenAI Adoption in Higher Education: A Task-Based Perspective, The International Journal of Management Education,
  • ChatGPT and AI in education: A systematic review. (2025). TechTrends, 69(3), 45–60. https://link.springer.com/article/10.1007/s11528-025-01100-1
  • Fukami, C., et al. (in press). Human-centered business education in an artificial intelligence-driven world. Journal of Management Inquiry https://doi.org/10.1177/10564926251364213
  • Ivanov, S., Soliman, M., Tuomi, A., Alkathiri, N. A., & Al-Alawi, A. N. (2024). Drivers of generative AI adoption in higher education through the lens of the Theory of Planned Behaviour. Technology in Society, 77, 102521. https://doi.org/10.1016/j.techsoc.2024.102521
  • Lyu, W., et al. (2025). Understanding the Practices, Perceptions, and (Dis)Trust of Generative AI among Instructors: A Mixed-methods Study in the U.S. Higher Education. arXiv https://arxiv.org/abs/2502.05770
  • Mah, D-K, et al. (2025). Faculty perceptions and institutional readiness for AI in higher education. Frontiers in Education, vol 10. https://www.frontiersin.org/articles/10.3389/feduc.2025.1484904/full
  • Shata, A., & Hartley, K. (2025). Artificial intelligence and communication technologies in academia: Faculty perceptions and the adoption of generative AI. International Journal of Educational Technology in Higher Education, 22(14). https://doi.org/10.1186/s41239-025-00511-7
  • Zhang, Y., Liu, M., & Gomez, R. (2025). Engineering education and AI tutors: A case study of practical adoption. arXiv https://arxiv.org/abs/2506.05699