AI in Education
Augment, Not Replace: Reframing AI’s Place in the Classroom
There is a growing sense that artificial intelligence is reshaping the conditions under which students learn. Yet, amid the excitement surrounding its capabilities, a more fundamental question remains: what is happening to students’ thinking in the process? A recent report by Lodge and Loble provides a timely opportunity to pause and consider this question more carefully, shifting attention away from the novelty of the technology and towards the cognitive work that sits at the heart of learning.

The report argues that AI will only enhance learning if it supports students’ cognitive effort rather than replacing it, meaning the real determinant of its educational impact is pedagogy, not the technology itself. While AI can support learning when used well, unstructured use may allow students to bypass the cognitive effort, or productive struggle, needed to build knowledge and expertise. Lodge and Loble use the term performance paradox to describe the result of this scenario: students may perform better on tasks with AI assistance but retain less understanding when the tool is removed. They differentiate between beneficial offloading, where AI supports lower-order tasks, and detrimental offloading, where students outsource the learning process itself. These are concepts that are becoming increasingly familiar in current discussions about AI and learning.
Ultimately, the report reinforces the importance of the teacher, arguing that AI should augment rather than replace human expertise, since teachers are best placed to guide the cognitive effort, judgement, and self-regulated learning that underpin deep understanding.
What I particularly appreciated about the report was its balanced tone. Rather than throwing the analogue baby out with the digital bathwater, Lodge and Loble recognise both the possibilities and the risks associated with AI in education. The clear definitions of key terms are especially helpful for navigating what is often a confusing and rapidly evolving conversation, and the reference list alone provides a valuable resource for anyone wishing to explore the research base more deeply. The report also feels timely given our own work examining the impact of generative AI on young minds. Most importantly, it frames AI not as a replacement for teachers, but as a tool that can amplify what skilled educators already do in their classrooms: helping to prepare students thoughtfully and responsibly for the world beyond the school gates.
At a time when schools are navigating both the promise and uncertainty of AI, this report serves as a helpful reminder that the core work of education remains unchanged. Learning still depends on effort, guidance, and relationships. The challenge ahead is not simply to adopt new technologies, but to do so in ways that preserve (and indeed strengthen) the conditions under which deep learning can occur.
Reference
Lodge J. M. and Loble L (2026). Artificial intelligence, cognitive offloading and implications for education, University of Technology Sydney, doi:10.71741/4pyxmbnjaq.31302475.
You can read the full report here.

Dr Timothy Scott
Tim has held leadership roles in schools across Australia and abroad for 26 years, alongside teaching History and Modern Languages. He is currently the Barker Institute Principal Research Fellow. His research focuses on intercultural learning and pedagogical translanguaging, refugee education, and student voice in improving educational practice. He is a lead researcher for the Barker Institute’s ongoing decade-long longitudinal study, The Barker Journey. Alongside his research work, Tim currently teaches History and IGCSE Global Perspectives. His PhD examined socio-political influences on contemporary German conceptions of history and archaeology.




