Cracking the AIEd code: Dialogic-relational academic advising

Abstract

To contribute to cracking the theoretical AI in education code, interviews with academic advisors at a European university were analysed using a dialogic-relational translation device to develop a sociomaterial framework for building EdTech and AIEd theory. The four personas (Consultant, Coach, Counsellor, Collaborator) emerging from the data analysis represent the mental models of academic advisors regarding using technology in their practice. These personas could be used to understand the underlying dynamic of the academic advising practice, for developing personalised training, or to design future human-centred AI-infused academic advising systems. The dialogic-relational framework could also be adapted to create translation devices to analyse and build EdTech and AIEd theory regarding other educational teaching-learning-assessment practices.

Keywords

• academic advising
• educational technology
• ai in education
• sociomaterialism
• dialogic-relational framework
• mental models
• personas