Roba Abbas, School of Business, University of Wollongong, Australia

Polyxeni (Xenia) Vassilakopoulou, University of Agder, Norway

Matti Mäntymäki, Turku School of Economics, University of Turku, Finland

Track Call

This track seeks to provide a forum for exploring information systems (IS) pedagogical innovation and the dynamic interplay between research and teaching within the rapidly evolving artificial intelligence (AI) landscape. We call for papers that explore the transformative potential and current impact of AI in University education, investigating challenges and opportunities. We welcome both conceptual and empirical research and all methodological approaches. We particularly encourage papers offering critical perspectives.

Track Areas

  • Critical perspectives on the impact of AI on IS and business education, including curricula at both undergraduate and postgraduate levels
  • Critical perspectives on the impact of AI on the research-teaching nexus as related to the digital transformation of higher education
  • Examples of research-led teaching and teaching-led research in IS and business programmes that involve AI including: programmes that demonstrate pedagogical innovation; consider the social, ethical, regulatory, and other implications of AI; and / or strengthen the research teaching nexus
  • Examples of IS pedagogical innovation in which AI and digital literacy or fluency are core components
  • IS and business programmes involving AI that integrate interdisciplinary, scholarly, industry and / or government perspectives in the design of assessments and teaching and learning activities
  • IS pedagogical approaches with respect to AI, digital transformation, and socio-technical systems including: strategies for developing students’ AI competencies; innovative use of AI for student tutoring; AI-enabled adaptive learning; experiential learning with industry or community partners; pedagogical approaches that foster critical thinking about AI; processes for aligning learning outcomes with AI trends and societal needs; institutional support structures for faculty development and support with respect to pedagogical innovation; and experiences from University policies on AI use for teaching, learning and evaluation