Education in the Age of Polycrisis: Implications for AI and Analytics

A year ago in Dublin, the LAK25 conference convened a workshop on “Grand Challenges” that could productively advance the field. A shortlist of candidates emerged from the day, of which participants ranked “Learning Analytics in the age of global polycrisis” as most urgent, and was presented to the conference in the plenary panel.

In a nutshell: One approach to defining grand challenges is to agree on education’s most urgent, intractable challenges and focus our efforts on those.

“The polycrisis” is shorthand for the causally entangled, globalised systems now threatening humanity’s wellbeing. These systems degrade each other with cascading impacts and reinforcement loops. The evidence is that we are now locked into climate trajectories which will create extraordinarily turbulent futures. Authoritative government and NGO reports confirm the entangled security, political, ecological, social, psychological and infrastructure challenges to society. The COVID19 pandemic was archetypal, and right now, we are witnessing the cascading effects of supply threats to the petrochemicals powering modern society.

Given such system shocks, our infrastructures, curricula and assessments must be resilient and fit for purpose. Our students, educators and administrators must be supported amid stressors including heat, health, finance. Climate anxiety is very real in our young people, and for many, deeper questions arise around meaning and purpose in a world that seems to be unravelling (termed by some “the metacrisis”).

If these are the conditions for learning, does this change our thinking about the distinctive contributions that our work in Learning Analytics and AI could make?

This interactive workshop is intended to help you get to grips with these challenges, learn how others are responding, open up conversations on what this might mean for our research field, and perhaps spark personal reflections on the implications for your own work.

These are complex questions, and we very much look forward to some mutual learning!

Lunch is provided at 13:00 - 14:00, with the option to stay on for informal conversation after.

Bio

Simon Buckingham Shum is Professor of Learning Informatics at the University of Technology Sydney where he has directed the Connected Intelligence Centre (CIC) since 2014. CIC is a transdisciplinary innovation centre inventing, piloting, evaluating and scaling data-driven personalised feedback to students. Prior to this he was at the UK Open University’s Knowledge Media Institute (1995-2014).

Simon comes from a Human-Computer Interaction background, and his career-long fascination with software’s ability to make thinking visible has seen him active in communities including Hypertext, Computer-Supported Argumentation, eDemocracy, Educational Technology, Learning Analytics and AI in Education. He has contributed to Social Learning Analytics, Dispositional Analytics, Writing Analytics, Collaboration Analytics, and Belonging Analytics, and researched how LA develops as a discipline and community, such as the organisational process of institutionally embedding LA, and the impact of the LAK Doctoral Consortium.

His current interests include conversational agents for deeper thinking, interactive tools for human+LLM coding of data, the design of productive friction in the human-AI user interface, and how LA/AIED research needs to help prepare learners for the profound turbulence of the polycrisis.