Cognitive Offloading in the Age of AI: Opportunities, Challenges, and Mechanisms
Authors: Yerin Seung; info@ciddl.org
Conversations about AI in education often fall into two camps: advocates who emphasize its potential and skeptics who warn about its risks. Yet both perspectives tend to ask the same central question: Should students use AI? While this question is important, it may not be the most meaningful one for understanding what is actually happening in classrooms. A more productive question might be: What happens to students’ thinking when they use AI, and under what circumstances does AI become more beneficial or risky? This shift moves the conversation away from simple approval or rejection of AI and toward a deeper examination of how learning itself is changing. In our recent paper by Seung and Dr. Basham (2026), Cognitive Offloading in the Age of Generative AI: What Does It Mean for Students With Learning Disabilities? (published in Learning Disability Quarterly), we explore this question through the lens of cognitive offloading, a concept that helps explain how students redistribute their mental effort when using AI.
AI Changes How We Think
Cognitive offloading refers to the ways people use tools to reduce mental effort. This is not new. Students have long relied on strategies such as taking notes, using calculators, or setting reminders to support their thinking. These tools help move some of the mental work outside the mind, so students can focus on more complex parts of a task. What makes generative AI different is how much it can take on. Students are no longer limited to offloading simple tasks like remembering information or doing calculations. They can now rely on AI to help generate ideas, summarize texts, draft responses, and even assist with problem-solving. Because of this, AI doesn’t just support thinking. It can start to take over parts of the thinking process itself. This shift raises important questions about effort, engagement, and the role of practice in learning.
A Double-Edged Sword for Learning
This expanded capacity brings both benefits and challenges. On one hand, AI can be a powerful support tool, especially for students who face cognitive difficulties. It can make learning more accessible and help students engage with material that might otherwise feel overwhelming. At the same time, there are potential downsides. When AI takes over too much of the thinking, students may miss important opportunities to practice the skills they need. If students regularly bypass these processes, they may still complete their work, but over time, they may develop less independence and a weaker understanding. This tension highlights that the key issue is not just whether AI is used, but how it is used.
Not All Students Experience This the Same Way
These dynamics are particularly important for students with learning disabilities. Many of these students already face challenges related to executive function, working memory, attention, and self-regulation. For them, AI can reduce barriers and provide meaningful support that enables participation in academic tasks. However, these same students may also be more vulnerable to overreliance. When tasks feel consistently difficult, and when confidence in one’s own abilities is low, the appeal of offloading cognitive effort becomes stronger. Over time, AI can shift from being a helpful scaffold to becoming a default strategy. This does not mean that AI is harmful for these students; rather, it underscores the importance of understanding how and why students choose to rely on it.
AI Use as a Decision-Making Process
One of the central ideas in our work is that using AI is not simply a behavior; it is a form of decision-making. When students choose whether to complete a task independently or rely on AI, they are implicitly weighing different factors. These include how difficult the task feels, how confident they are in their ability to succeed, their immediate goals, and how much they trust the tool. These decisions shape how much thinking is offloaded and how much remains with the learner. For some students, particularly those who have experienced repeated academic difficulty, AI may quickly become a go-to solution. In this sense, the use of AI reflects not just access to technology but also a complex interaction among cognitive demands, motivation, and beliefs about learning.
What This Means for Educators
If AI use is fundamentally about how students allocate their thinking, then the goal for educators is not simply to encourage or restrict its use. Instead, the focus should be on helping students develop the ability to make more intentional decisions about when and how to use AI. This involves supporting students in becoming aware of their own thinking processes and helping them evaluate whether AI is supporting or replacing their learning. It also requires thoughtful task design, where AI is integrated in ways that preserve meaningful engagement rather than bypass it. A simple but powerful question can guide this work: How does my internal state and environment impact my AI offloading decision? How can I use AI in ways to help my thinking? This question can help both educators and students maintain a focus on learning in AI-supported environments.
Moving the Conversation Forward
AI is neither inherently beneficial nor inherently harmful. Its impact depends on how it is used and how those uses interact with the learner. Understanding AI through the lens of cognitive offloading allows us to move beyond surface-level debates and toward a more nuanced view of learning in AI-integrated contexts. At the same time, many questions remain. We still need to better understand how students make decisions about offloading over time and how these decisions influence long-term learning, especially for those who already face challenges. When does AI support growth, and when does it quietly reshape learning in unintended ways?
These are the questions we explore in greater depth in the full article. Check out the full article if you're interested in how cognitive offloading, student characteristics, and instructional design intersect in AI-supported learning.
Read the full article in the Learning Disability Quarterly:
Seung, Y., & Basham, J. D. (2026). Cognitive offloading in the age of generative AI: What does it mean for students with learning disabilities? Learning Disability Quarterly. https://doi.org/10.1177/07319487261439132
If you have any questions related to the article, please reach out to Yerin Seung at yerinseung@ku.edu.
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