Professor and Director of the Learning, Instruction and Technology Laboratory, School of Education; The University of Queensland, Australia
Jason Lodge, PhD, PFHEA is Professor of Educational Psychology and Director of the Learning, Instruction, and Technology Laboratory in the School of Education at The University of Queensland. Jason has published over 130 refereed articles and is a national award-winning educator. He has been awarded over $5 million (AUD) in competitive funding. Jason’s research with his lab focuses on the cognitive, metacognitive, and emotional mechanisms of learning, primarily with digital technologies including artificial intelligence. Jason is an expert advisor to the Australian Department of Education and the OECD.
Artificial intelligence is being heralded as a significant leap forward for enhancing productivity and efficiency. However, this instrumental view overlooks the profound implications for how we learn, adapt, and grow in an era of machines that imitate collaborators or peers. While AI tools can streamline tasks, the educational challenge lies in developing adaptive skills and knowledge to identify when to collaborate with AI and when to rely on uniquely human capacities.
In this presentation, the speaker challenges the reductionist view of AI as merely a collection of task-specific tools, exemplified by today's large language models and generative AI. Drawing from the research being conducted in his laboratory, Professor Lodge will explore the critical distinctions between human and machine intelligence, emphasising how their complementary strengths can form powerful hybrid cognitive systems. By understanding these differences, we can better prepare learners to develop the adaptive expertise needed in an AI-integrated future – from metacognitive awareness and creative synthesis to ethical judgment and interpersonal intelligence.
The presentation concludes by advocating for a transformative vision of AI in education that addresses three interconnected dimensions: technological integration, adaptive skills and knowledge, and systemic innovation. This includes not only developing effective AI-enhanced learning environments but also equipping learners with the knowledge to critically engage with AI systems and fostering the adaptive capabilities that will remain distinctly valuable in a world where AI is ubiquitous. Special attention will be given to crucial future-ready skills such as algorithmic thinking, information discernment, collaborative problem-solving, and the ability to continuously learn and unlearn as AI capabilities evolve.