Ace
Short answer: AI is changing study methods in three big ways: explanations are instant, practice questions can be generated from any material, and feedback arrives straight away. These help when they make you think and test yourself. The risk is "cognitive offloading": letting AI do the thinking, which can feel efficient while weakening what you remember and understand.
How is AI changing the way students study?
1. From searching to asking
Instead of searching through textbooks and forums, students ask an AI to explain a concept in their own words, with examples. That's faster, but the explanation still needs checking against your course material.
2. From making flashcards to generating practice
Writing your own questions used to take hours, so many students skipped self-testing altogether. AI can now turn notes into practice questions quickly. That matters, because testing yourself is one of the most effective ways to learn (Roediger & Karpicke, 2006; Dunlosky et al., 2013).
3. From waiting for feedback to getting it instantly
Feedback used to arrive days later, after marking. Now you can get it immediately after each answer. Feedback is what turns practice into learning, especially after mistakes (Butler & Roediger, 2008).
4. From one pace to your pace
AI can slow down, give another example or go deeper, the way a personal tutor would. One-to-one tutoring has long been known to be unusually effective (Bloom, 1984), and well-designed AI tutoring has shown promising results in research (Kestin et al., 2025).
5. From fixed materials to any material
Lecture slides, PDFs and recorded lectures can now all become something interactive. The material you already have can become your practice.
What is the hidden risk of studying with AI?
When AI gives you the answer, the effort that builds memory disappears. Researchers call this cognitive offloading. One study found that people who relied more heavily on AI tools tended to score lower on critical thinking, with offloading part of the explanation (Gerlich, 2025). In a large maths study, students with unrestricted chatbot access did better while practising but worse on a later test without it (Bastani et al., 2025). The pattern is consistent: AI that thinks for you feels helpful and teaches you less.
How should you adapt your study methods?
- Ask AI to quiz you, not tell you. "Ask me one question at a time on this lecture and wait for my answer."
- Try first, ask second. Attempt a problem before asking for help, and ask for hints rather than full solutions.
- Use your own course material. Your exam is written from your lectures, not from the internet.
- Check answers against the source. AI can be confidently wrong. Our guide on whether you can trust AI answers explains how to spot errors.
- Keep spacing your practice. Come back to the same topic over days and weeks.
Ace is built around these principles: it turns your own lecture slides, PDFs or YouTube lectures into practice questions and shows the line from your notes behind every answer. See also AI in education in 2026.
Frequently asked questions
Does using AI make you a worse learner?
Not necessarily. It depends on whether AI does the thinking for you or makes you think. Using it to quiz yourself and get feedback is very different from using it to produce answers.
What is cognitive offloading?
Relying on an external tool to do mental work for you. Some offloading is useful, like a calculator, but offloading the thinking you're supposed to be learning weakens that learning.
What's the best way to study with AI?
Give it your own material, have it test you, answer before seeing the solution, and check its answers against your notes.
Sources
- Roediger, H. L., & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249–255.
- Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students' learning with effective learning techniques. Psychological Science in the Public Interest, 14(1), 4–58.
- Butler, A. C., & Roediger, H. L. (2008). Feedback enhances the positive effects and reduces the negative effects of multiple-choice testing. Memory & Cognition, 36(3), 604–616.
- Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, 13(6), 4–16.
- Kestin, G., Miller, K., Klales, A., Milbourne, T., & Ponti, G. (2025). AI tutoring outperforms in-class active learning: An RCT introducing a novel research-based design in an authentic educational setting. Scientific Reports, 15, 17458.
- Gerlich, M. (2025). AI tools in society: Impacts on cognitive offloading and the future of critical thinking. Societies, 15(1), 6.
- Bastani, H., Bastani, O., Sungu, A., Ge, H., Kabakcı, Ö., & Mariman, R. (2025). Generative AI without guardrails can harm learning: Evidence from high school mathematics. Proceedings of the National Academy of Sciences, 122(26), e2422633122.
