XXIII Conference of the Italian Chapter of AIS
Responsible and Intelligent Digital Future for People, Organisations, and Society
|

Teaching and Researching with AI in Higher Education: from insight to impact

2nd edition: Workshop at ItAIS 2026 (XXIII Conference of the Italian Chapter of AIS)

  • Duration: 10:45AM – 01:00PM
  • Date: October 23rd 2026
  • Submission deadline: September 29th 2026
  • Notification of acceptance: October 5th 2026
  • Organizing co-chairs: Leonardo Caporarello, Roberta Cuel, Aurelio Ravarini

Introduction

The first edition of this workshop (ItAIS 2025) brought together educators from several European universities and did not end when the session closed. It seeded the AI4EDU (AI for Higher Education) community, a cross-institutional initiative that has since continued to compare experiences, build a shared knowledge base, and channel the discussion into collective publications rather than isolated research pipelines.

The community’s work over the past year has been organised around a set of unresolved tensions that recurred across very different institutional projects – from a student-built AI learning platform, to conversational assessment and learner “digital twin” systems, to decision-centred AI curricula and studies on AI and creativity. Eight fault lines emerged:

  1. The adoption paradox: distrust and fear of replacement coexisting with near-universal student use.
  2. Cognitive vs. motivational engagement: designing for genuine thinking when a tool lets students offload much of it.
  3. Assessment redesign: what to do when submitted work may have been largely AI-generated.
  4. Digital twins vs. surveillance: where learner modelling stops being support and becomes monitoring.
  5. Identity and plagiarism: authorship when the artefact is coproduced with a machine.
  6. Anthropomorphism risk: distinguishing useful personalisation from the anthropomorphising pull of these tools, especially with younger students.
  7. What grades certify: what a mark actually attests once AI is in the loop.
  8. The shifting artefact problem: assessing and teaching against a technology that changes underneath you.

None of this can be resolved by tweaking individual courses. It requires rethinking, at multiple levels, the role of teachers and of universities themselves. This edition invites the wider ItAIS community into that conversation.

Objectives

  • Share concrete experiences and practices in the use of AI in teaching, researching, and learning across all levels (undergraduate to executive education).
  • Showcase live or demonstrative examples of AI-supported educational methodology.
  • Present emerging conceptual work on AI-supported pedagogy, feedback and curriculum design.
  • Facilitate critical comparison of AI-enabled practices across diverse contexts.
  • Advance the eight fault lines toward a shared agenda: and a collective manifesto on AI in higher education: that informs both classroom practice and future research.

Target Participants

Diversity of perspectives, scenarios, and settings remains a foundational value. We welcome:

  • Faculty experimenting with the integration of AI into their teaching and researching 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.
  • Members of, and newcomers to, the AI4EDU community.

Participation is free of charge for all conference attendees.

Submission Guidelines

We invite the following types of submission:

  • Experience Reports (max 2 pages): detailed case studies on AI use in educational settings.
  • Position Papers (max 2 pages): conceptual models, ethical frameworks, or normative analyses: including contributions that engage directly with one or more of the eight fault lines.
  • Research in Progress Abstracts (max 1 page): early-stage empirical or theoretical investigations.

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

Publication opportunity

Accepted contributions will be published in online proceedings with an ISBN. Further details will be provided.

References

Adams, R. (2025, February 26). UK universities warned to stresstest assessments as 92% of students use AI. The Guardian. https://www.theguardian.com/education/2025/feb/26/ukuniversitieswarnedtostresstestassessmentsas92ofstudentsuseai

Awadallah Alkouk, W., & Khlaif, Z. N. (2024). AIresistant assessments in higher education: Practical insights from faculty training workshops. Frontiers in Education, 9, 1499495. https://doi.org/10.3389/feduc.2024.1499495

Canavesi, A., Bertolotti, F., Cattaneo, L., Buonanno, G., Mari, L., & Ravarini, A. (2025). From developers to players: Exploring the dual impact of gamebased learning on student engagement, learning and skill development. Journal of Research in Educational Sciences, 16(2), 31–50.

Canavesi, A., & Ravarini, A. (2024). Innovative methodologies of active learning to develop the competencies of the future of work. Journal of Higher Education Theory and Practice, 24(4). https://doi.org/10.33423/jhetp.v24i4.6941

Caporarello, L. (Ed.). (2025). AI in education – The urgency of the now. Realworld applications, challenges, and lessons for educators. Independently published.

Caporarello, L. (2025). Who wants to learn forever? Bocconi University Press.

Caporarello, L., & Trabskaia, I. (in press). Fear of educators’ replacement by AI: Students’ perspective in the management education settings. In C. Maheshkar & A. Coelho (Eds.), Perspectives and challenges of management education. Nova Science Publishers.

Chaieb, M., Cuel, R., & Bouzaabia, R. (2026). Reconceptualizing of GenAI adoption in higher education: A taskbased perspective. The International Journal of Management Education, 24(1), 101365. https://doi.org/10.1016/j.ijme.2026.101365

Fukami, C. V., Hamilton, A. L., Rivers, C., Holland, A., Brady, M., Fellenz, M., Allen, S. J., Caporarello, L., FischbacherSmith, D., FischbacherSmith, M., von Delft, S., Wittmer, D., Allen, D., Aghdasi, F., Brett, J. M., Morse, L., & Leben, D. (2025). Human-centered business education in an artificial intelligencedriven world. Journal of Management Inquiry. Advance online publication. https://doi.org/10.1177/10564926251364213

Ivanov, S., Soliman, M., Tuomi, A., Alkathiri, N. A., & AlAlawi, 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

Jin, Y., & Sercu, L. (2025). ChatGPT interventions in higher education: A systematic review of experimental studies. Journal of Computer Assisted Learning, 41(4), e70072.  https://doi.org/10.1111/ejed.70262Digital Object Identifier (DOI)

Lyu, W., Zhang, S., Chung, T. (R.), Sun, Y., & Zhang, Y. (2025). Understanding the practices, perceptions, and (dis)trust of generative AI among instructors: A mixed methods study in the U.S. higher education. Computers and Education: Artificial Intelligence, 8, 100383. https://doi.org/10.1016/j.caeai.2025.100383

Pattier, D. (2024). ChatGPT and Education: A Systematic Review. Revista Entropía Educativa, 2(1), 80-102.

Perozzo, H., Sengewald, J., & Ravarini, A. (2025). Mastering the machine: How prompt engineering transforms generative AI learning. In Proceedings of the Americas Conference on Information Systems (AMCIS 2025). Association for Information Systems.

Ravarini, A., & Canavesi, A. (Eds.). (2024). Una didattica per l’università: Educazione e innovazione nell’esperienza LIUC (Università Cattaneo Libri). Guerini Next. ISBN 9788868965440.

Ravarini, A., Canavesi, A., & Passerini, K. (2024). From users to allies: Exploring educator and generative AI roles in shaping the future of higher education. In Proceedings of the 10th International Conference on Higher Education Advances (HEAd’24) (pp. 2–9). Universitat Politècnica de València.

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/s41239025005117.