Do AI Tutors Build Understanding or Just Assisted Performance?

Introduction

AI tutors can improve learning, but they can also create a misleading form of success. Students often perform better when an AI system is available to explain concepts, generate examples or suggest next steps. The harder question is what happens after the AI disappears. Can the student still solve the problem alone, explain the idea from memory, or apply it in a new context?

This distinction matters because education is not mainly about assisted performance. It is about building durable understanding. In the optimistic vision of AI-enabled learning at scale, intelligent tutors could make personalised educational support available to billions of people. But if those systems merely help students complete tasks while quietly weakening independent reasoning, the long-term gains could be much smaller than they first appear.

The evidence so far suggests a mixed picture. AI tutors can produce real learning gains, especially when they guide students through reasoning and practice. Yet there is also growing evidence that answer-giving systems can create dependence, leading students to confuse temporary support with genuine mastery. The design of the tutor appears to matter as much as the underlying AI.

Why Assisted Performance Can Feel Like Real Learning

One of the oldest findings in cognitive science is that understanding something in the moment is not the same as learning it permanently.

Students frequently experience what researchers call an illusion of competence. A worked example looks obvious once it has been explained. A chatbot’s answer feels clear. A step-by-step solution creates the impression that the learner could reproduce the process later. Yet when the support disappears, the knowledge often proves far less secure.

Generative AI may amplify this problem because it produces explanations that feel highly personalised and conversational. Unlike a textbook, it responds instantly. Unlike a search engine, it packages information into a coherent narrative. The interaction creates a strong subjective feeling of understanding.

That feeling is not worthless. Confidence and engagement matter. But educational psychologists have long argued that durable learning requires effortful retrieval, practice, error correction and independent problem-solving. If AI removes too much of that effort, students may perform better during study while learning less overall. Research increasingly focuses on separating these two outcomes: immediate task success and lasting competence.[ResearchGate]researchgate.netResearch Gate Distinguishing performance gains from learning whenDistinguishing performance gains from learning when…June 18, 2025 — 15 May 2026 — Generative artificial intelligence (AI)…Published: June 18, 2025

This is one reason many researchers prefer the term “cognitive offloading” to simple automation. The concern is not that students use tools. Calculators, dictionaries and search engines are also tools. The concern is that advanced AI can absorb parts of the reasoning process itself, reducing the mental work that helps build expertise.

What the Exam Evidence Shows

The strongest tests of educational value are often the simplest: remove the tool and see what remains.

Several recent studies suggest that AI assistance can improve immediate performance while producing weaker results when students later work independently.

A multi-university study reported by researchers from Carnegie Mellon, Oxford, MIT and UCLA found that participants receiving AI assistance initially solved more problems, but performed substantially worse after the assistance was removed. The AI-assisted group scored around 20% lower on later tasks and skipped more questions when forced to rely on their own reasoning. The decline was especially pronounced when participants had used AI to obtain direct answers rather than hints or clarifications.[New York Post]nypost.comParticipants in the study took a fraction-based math test, with half receiving temporary assistance from an AI tool. While AI users initi…

Other emerging research points in a similar direction. A large-scale analysis of millions of mathematics-learning interactions found evidence that students spent less time working through AI-susceptible problems after the release of advanced language models. The researchers also found weaker performance on proctored retention assessments, suggesting that some apparent gains reflected assistance during learning rather than durable understanding.[arXiv]arxiv.orgFaster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They BuildMay 20, 2026…Published: May 20, 2026

These findings do not prove that AI tutoring is harmful. They do show that educational success cannot be measured solely by completion rates, homework scores or student satisfaction. A system may make learning feel easier while reducing the struggle that helps knowledge stick.

The distinction is especially important because AI tutors are often marketed using metrics such as engagement, completion and confidence. Those outcomes matter, but they are not the same as long-term mastery.

The Evidence Is Not One-Sided

The dependence story is only half the picture.

A growing body of research suggests that well-designed AI tutoring systems can improve learning outcomes without simply replacing student effort.

A 2025 randomised study involving university students found that AI tutor access improved exam performance by roughly 0.23 standard deviations compared with textbook-only study. Importantly, the researchers reported that the tutoring system did not appear to crowd out reading effort. Students still engaged with the underlying material rather than relying exclusively on the AI.[Econstor]econstor.euAI Tutoring Enhances Student Learning Without Crowding…by M Fischer · 2025 · Cited by 7 — We study how AI tutoring affects lea…

Another study published in Scientific Reports found that students using a carefully designed AI tutor learned more in less time than students receiving active-learning classroom instruction on the same material. The researchers attributed part of the advantage to tutoring methods that mirrored established educational practices rather than simply providing answers. Students also reported higher engagement and motivation.[Nature]nature.comAI tutoring outperforms in-class active learningby G Kestin · 2025 · Cited by 187 — We find that students learn significantly more…

The important point is that not all AI tutoring systems operate in the same way.

An AI that solves the problem for the student is educationally different from an AI that asks questions, identifies misconceptions and pushes the learner to explain their reasoning. Research increasingly suggests that these design differences strongly influence whether AI becomes a learning aid or a crutch.[ScienceDirect]sciencedirect.comLess stress, better scores, same learning: The dissociation…by P Bassner · 2025 · Cited by 6 — Generative AI is reshaping…

Why Socratic Tutors May Be Less Risky

Many of the most promising educational AI projects are built around a surprisingly old idea: do not tell students the answer too quickly.

The educational model often described as Socratic tutoring relies on guided questioning. Instead of supplying solutions immediately, the tutor prompts the learner to think through the problem, identify assumptions and generate explanations.

Khan Academy’s Khanmigo is built around this principle. The organisation explicitly argues that the system should guide learners toward answers rather than simply providing them.[Khanmigo]khanmigo.aiMeet Khanmigo: Khan Academy's AI-powered teaching…Khanmigo, built by nonprofit Khan Academy, is a top-rated AI for education…

More recent research prototypes follow a similar direction. Systems such as SocratiCode and SocraticAI have experimented with structured questioning, incremental hints, reflection prompts and usage constraints designed to keep students cognitively engaged rather than passively consuming solutions. Early findings suggest that learners often develop better problem-solving habits when the AI acts more like a coach than an answer engine.[arXiv]arxiv.orgFaster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They BuildMay 20, 2026…Published: May 20, 2026

This reflects a broader insight from learning science. Educational support tends to work best when it reduces unnecessary frustration without eliminating productive struggle.

Too little support leaves learners stuck. Too much support leaves them dependent.

The challenge is finding the middle ground.

Design Choices That Reduce Over-Reliance

The dependence problem is not necessarily an unavoidable feature of AI tutoring. It may be partly a design problem.

Several approaches appear promising:

Delayed assistance. Students attempt a problem first before receiving help. This preserves retrieval practice and reveals genuine gaps in understanding.

Hint ladders rather than answers. The system provides progressively stronger guidance instead of immediately solving the task.

Mandatory explanation. Learners must explain why an answer works rather than simply accepting it.

Reflection prompts. Students are asked what they learned, what confused them and how they would solve a similar problem independently.

Periodic AI-free assessment. Knowledge is tested without assistance so that both students and teachers can distinguish learning from supported performance.

Usage limits. Some experimental systems deliberately restrict interaction patterns that encourage dependency, including repetitive answer-seeking behaviour.[arXiv]arxiv.orgFaster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They BuildMay 20, 2026…Published: May 20, 2026

These strategies all aim at the same goal: preserving student agency. The AI remains available as a guide, but the learner still performs the intellectual work required for mastery.

The Deeper Question for AI-Abundant Education

The debate around dependence reaches beyond exam scores.

The broader AI bloom vision imagines a world where personalised intellectual support becomes abundant. A child in a remote village, an adult retraining for a new career, or an elderly learner exploring a new subject could potentially receive educational guidance that was once available only to wealthy families or elite institutions.

If that vision works, AI could expand human capabilities on a massive scale. More people might gain access to advanced knowledge, scientific literacy, technical skills and creative opportunities.

But abundance alone is not enough.

An educational system that makes learners permanently reliant on external intelligence would be a weaker achievement than one that helps them develop their own capabilities. The most valuable AI tutor is probably not the one that answers every question. It is the one that gradually makes itself less necessary.

In that sense, the deepest benchmark for AI tutoring may not be whether students perform well with the system. It may be whether they become more capable without it.

The long-term promise of AI-enabled education depends on that distinction. If AI tutors mainly automate thinking, they risk creating cognitive dependence. If they help people build stronger reasoning, curiosity and self-directed learning, they could become one of the clearest examples of how abundant machine intelligence expands rather than replaces human potential.

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Endnotes

1. Source: researchgate.net
Title: Research Gate Distinguishing performance gains from learning when
Link:https://www.researchgate.net/publication/392818529_Distinguishing_performance_gains_from_learning_when_using_generative_AI

Published: June 18, 2025

2. Source: sciencedirect.com
Link:https://www.sciencedirect.com/science/article/pii/S2666920X25001778

3. Source: arxiv.org
Link:https://arxiv.org/abs/2605.21629

Published: May 20, 2026

4. Source: econstor.eu
Link:https://www.econstor.eu/bitstream/10419/336607/1/557.pdf

5. Source: nature.com
Link:https://www.nature.com/articles/s41598-025-97652-6

6. Source: khanmigo.ai
Link:https://www.khanmigo.ai/

7. Source: khanmigo.ai
Link:https://www.khanmigo.ai/learners

8. Source: arxiv.org
Link:https://arxiv.org/abs/2605.17857

9. Source: arxiv.org
Link:https://arxiv.org/abs/2512.03501

10. Source: researchgate.net
Link:https://www.researchgate.net/publication/399367159_AI_Tutoring_Enhances_Student_Learning_Without_Crowding_Out_Reading_Effort

11. Source: researchgate.net
Link:https://www.researchgate.net/publication/396808798_Leveraging_Khanmigo_Generative_AI-Powered_Tool_for_Personalized_Tutoring_to_Learn_Scientific_Concepts

12. Source: arxiv.org
Link:https://arxiv.org/html/2507.18882v1

13. Source: arxiv.org
Link:https://arxiv.org/html/2507.07357v1

14. Source: nypost.com
Link:https://nypost.com/2026/05/28/health/how-using-ai-for-just-10-minutes-can-backfire-on-your-brain/

15. Source: linkedin.com
Link:https://www.linkedin.com/posts/shuchi-singh-6a80a7128_oecd-digital-education-outlook-2026-summary-activity-7422223054895853570-ZAG-

16. Source: reruption.com
Link:https://reruption.com/en/knowledge/industry-cases/khanmigo-khan-academys-gpt-4-ai-tutor-scaling-education

Additional References

17. Source: iatrox.com
Link:https://www.iatrox.com/blog/ai-tutors-harm-exam-learning-evidence

18. Source: povertyactionlab.org
Link:https://www.povertyactionlab.org/initiative-project/ai-powered-tutoring-unleashing-full-potential-personalized-learning-khanmigo

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Link:https://www.linkedin.com/posts/scottbelsky_fair-points-from-an-implications-reader-toby-activity-7336382464887570433-8_eB

21. Source: medium.com
Link:https://medium.com/%40adnanmasood/the-quiet-math-of-edtech-can-ai-tutors-really-teach-737195005abf

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Title: how khan academy is building a better ai tutor our most recent learnings
Link:https://blog.khanacademy.org/how-khan-academy-is-building-a-better-ai-tutor-our-most-recent-learnings/

Published: May 2026

24. Source: yolearn.ai
Title: ai learning assistant vs traditional study methods comparison
Link:https://www.yolearn.ai/blog/ai-learning-assistant-vs-traditional-study-methods-comparison

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Title: what the research shows about generative ai in tutoring
Link:https://www.brookings.edu/articles/what-the-research-shows-about-generative-ai-in-tutoring/

26. Source: facebook.com
Link:https://www.facebook.com/groups/131041333333435/posts/754477390989823/