Chapter 1
Chapter 1
This report forms part of the work program supporting the Australian Network for Quality Digital Education. The Network brings together leaders from across education, industry, social purpose and philanthropic organisations, government and research, in the common purpose of ensuring that all Australian students benefit from the best educational technology, and the benefits of educational technology are leveraged to tackle the persistent learning divide. Members of the Network have provided valuable engagement, input and feedback as part of the report's development, though the report does not represent a consensus or endorsed Network view.
The Network is chaired by Leslie Loble AM, who is Industry Professor at the UTS Centre for Social Justice and Inclusion.
Professor Jason M. Lodge is Professor of Educational Psychology and Director of the Learning, Instruction, and Technology Lab in the School of Education, The University of Queensland.
This report investigates a profound new challenge driven by AI's power to rapidly access information and provide a semblance of thinking: the risk that students will outsource too much of the cognitive work that is crucial to establishing the knowledge, skill and 'thinking infrastructure' that enables both schooling success and lifelong capacity for ongoing learning, understanding, reflection, creativity and achievement.
Preface
Preface
Artificial intelligence and especially generative artificial intelligence are propelling a new dynamic for Australian education, simultaneously unlocking compelling opportunities and substantial challenges for teaching and learning. Teachers and students find themselves on the front line of this paradox as they navigate in real time questions of how to best use artificial intelligence for learning and knowledge gain.
Today, in Australia, nearly eighty percent of students report using artificial intelligence, and two-thirds of early secondary teachers - fourth highest usage in the OECD - merely three years since ChatGPT burst through.
As artificial intelligence becomes a near-universal feature of Australian education, we cannot disentangle discussions of artificial intelligence from discussions of what will make Australian education most effective and equitable. Yet the education sector often feels like it's the tail while others have the whip hand. Just as it gets on top of one aspect of artificial intelligence, significant new dimensions emerge.
For teachers and for policy makers, all of this can sometimes feel overwhelming, especially when there is such limited research or even consistent experience with a technology that is intentionally designed to keep changing, from prompt to prompt, version to version, year to year. Retaining agency over the design, use and governance of artificial intelligence thus becomes an essential component of successful integration of artificial intelligence in education.
The artificial intelligence dynamic is nuanced and complex in education. It can both counteract - or compound - non-technological factors that propel learning gaps and educational outcomes, from teacher shortages to uneven distribution of resources and concentrations of disadvantage. The impact depends on decisions regarding an artificial intelligence tool's quality, accessibility and, above all, effective pedagogical use.
On the positive side of the ledger, some of the strongest available evidence points to sustained learning gains from artificial intelligence-enabled adaptive tutoring systems. Educational technology also can assist students with disability, who now comprise a quarter of Australian school classrooms. Artificial intelligence reduces teacher workloads, freeing time for more valuable educational interactions. And by providing quality teaching resources, well-designed digital tools can help support consistent access to high-quality, content-rich curriculum, a key factor in securing educational equity.
Securing the benefits of this technology relies on access to quality resources, digital inclusion, skills and understanding, and teacher expertise in how to effectively incorporate artificial intelligence for maximal student learning gain. Without these foundational elements, the risk rises both for uneven distribution of artificial intelligence's benefits and for challenges in obtaining positive educational outcomes.
This report investigates a related, and profound, new challenge that we face with AI's power to rapidly access information and provide a semblance of thinking: the risk that students will outsource too much of the cognitive work that is crucial to establishing the knowledge, skill and 'thinking infrastructure' that enables both schooling success and lifelong capacity for ongoing learning, understanding, reflection, creativity and achievement.
There is a growing body of evidence that using artificial intelligence can short-circuit the cognitive effort required for sustainable, deep learning, thus creating "false mastery" with potentially long-term consequences. This cognitive offloading from human to artificial intelligence is especially risky for school students ('novice' learners who are building foundational knowledge and skills) when they turn to artificial intelligence as a tempting substitute, not an amplifier, increase their dependency on the tool and lose access to deeper learning.
Cognitive outsourcing also introduces extra equity risks. Research suggests that students who possess high levels of content knowledge and strong metacognitive skills are better able to leverage artificial intelligence to accelerate and deepen their learning and critical thinking. Conversely, students lacking such skills, often those already experiencing disadvantage, are potentially more susceptible to harmful offloading and missing the learning they need. The unstructured use of artificial intelligence risks even wider equity divides.
The good news is that research studies also suggest these harmful effects can be counteracted through purposeful teaching and learning strategies and effective design of artificial intelligence education technology.
These strategies reinforce the importance of quality teaching, with artificial intelligence in a subsidiary, supporting position.
So, while the extent and scale to which students shift their knowledge and skill acquisition to artificial intelligence raises fundamental questions for teaching and learning - questions that cannot be answered solely by teaching artificial intelligence literacy - it also brings an important opportunity to validate and bolster the role of teachers.
This does not mean tackling harmful cognitive outsourcing is solely the responsibility of teachers, however. The ecosystem that supports effective teaching and learning (including quality curriculum) must respond, too, and how we navigate the nuance of positive and negative cognitive outsourcing with artificial intelligence will depend on good decisions across schooling and public policy.
Part of empowering teachers also means ensuring we direct the design of artificial intelligence tools so teachers have trustworthy resources to use. A large proportion of educational technology contains little explicit learning content, nor grounding in evidence-based pedagogy, especially general-purpose artificial intelligence chatbots lacking educational guidance or reliable evidence basis. The work tasked by Education Ministers for development of educational technology national standards and quality assurance procedures is essential and urgent.