Imagine a student using a writing assistant powered by a generative AI chatbot. Because the bot provides practical suggestions and encouragement, insights are easier to realize, drafts are quickly polished, and feedback loops are immediate. It will be stimulating. But if this AI support goes away, some students will report feeling less confident or less willing to have interaction.
These results raise the query: Can AI tools really increase student motivation? And what conditions could make or break this recovery?
As AI tools turn out to be more widely utilized in the classroom, the answers to those questions are of great importance. While general-use tools like ChatPGT or Claude remain popular, increasingly students are discovering AI tools designed specifically to support learning, like Khan Academy's Khanmigo, which personalizes instruction. Others, like ALEKS, offer adaptive feedback. Both tools adapt to the learner's learning level and highlight progress over time, helping students feel capable and see improvement. However, there are still many unknowns concerning the long-term impact of those tools on learner progress, a subject I proceed to explore as an academic psychologist.
What the evidence shows to date
Recent studies suggest that AI can increase motivation, not less than in certain groups, when used under the proper conditions. A 2025 experiment with university students showed that when AI tools delivered high-quality performance and enabled meaningful interaction, students' motivation and confidence of their ability to finish a task – called self-efficacy – increased.
For foreign language learners, a study from 2025 found that university students who used AI-driven personalized systems enjoyed learning more and had lower anxiety and better self-efficacy than those that used traditional methods. A current intercultural evaluation A study with participants from Egypt, Saudi Arabia, Spain and Poland who studied different majors found that positive motivational effects are strongest when the tools emphasize autonomy, self-direction and important considering. These individual findings are consistent with a more comprehensive, systematic review of generative AI tools Positive effects on student motivation and engagement were found across all cognitive, emotional and behavioral dimensions.
An upcoming meta-analysis by my team on the University of Alabama, which synthesized 71 studies, reflected these patterns. We found that, on average, generative AI tools have moderate positive effects on motivation and engagement. The impact is bigger when the tools are used consistently over time fairly than in one-off trials. Positive effects were also observed when teachers provide scaffolding, when students retain agency in using the tool, and when output quality is reliable.
But there are caveats. More than 50 of the studies we reviewed didn’t depend on a transparent theoretical framework for motivation, and among the methods used were, in our opinion, weak or inadequate. This raises concerns concerning the quality of the evidence and highlights how far more careful research is required before one can say with certainty that AI promotes students' intrinsic motivation, fairly than simply making tasks easier within the moment.
When AI backfires
There are also studies that paint a more sobering picture. A giant study of greater than 3,500 participants found that while human-AI collaboration improved task performance, intrinsic motivation decreased once the AI was removed. Students reported more boredom and fewer satisfaction, suggesting that overreliance on AI can undermine confidence in their very own abilities.
Another study suggested that although learning success often increases through the usage of AI tools, the rise in motivation is smaller, inconsistent or short-lived. Quality is just as essential as quantity. If AI delivers inaccurate results or students feel like they’ve little control over their use, motivation quickly declines. Confidence drops, engagement wanes, and students begin to view the tool as a crutch fairly than a support. And since there aren't many long-term studies on this area, we still don't know whether AI can truly maintain motivation long-term or whether its advantages fade once the novelty wears off.
Not all AI tools work the identical way
The influence of AI on student motivation shouldn’t be universal. Our team's meta-analysis shows that while AI tools have a positive effect on average, the dimensions of this effect is determined by how and where they’re used. When students engage with AI repeatedly over time, when teachers guide them in thoughtful use, and when students feel in command of the method, the motivational advantages are much stronger.
We also noticed differences between settings. College students appeared to realize greater than younger learners, STEM and writing courses tended to realize greater than other subjects, and tools designed for feedback or tutoring support outperformed people who simply generated content.
Charlie Riedel/AP
There can also be evidence that general-purpose tools resembling ChatGPT or Claude don’t reliably promote intrinsic motivation or deeper engagement with content in comparison with learning-specific platforms resembling ALEKS and Khanmigo, which more effectively support persistence and self-efficacy. However, these tools often require subscription or licensing costs. This raises questions of equity, as the scholars who may benefit most from motivational support can also be the least capable of afford it.
These and other recent findings should only be regarded as a start line. Because AI is so latest and changing so quickly, what we all know today may not apply tomorrow. In an article entitled The death and rebirth of educational research within the age of AIthe authors argue that the speed of technological change signifies that traditional studies are already outdated before they’re even published. At the identical time, AI opens the door to latest types of learning which are more participatory, flexible and imaginative. Taken together, the information and reviews point to the identical lesson: context, quality, and agency are only as essential because the technology itself.
Why it matters to all of us
The lessons from this growing body of research are clear. The presence of AI doesn’t guarantee higher motivation, but it could actually make a difference if the tools are developed and used with care and understanding of student needs. When used thoughtfully and in a way that strengthens students' sense of competence, autonomy, and connection to others, it could actually be a robust ally in learning.
However, without these safeguards, improving performance within the short term could end in high costs. Over time, the very qualities that matter most risk being weakened – motivation, persistence, critical considering and the uniquely human skills that no machine can replace.
For teachers, which means while AI could be a useful partner in learning, it should never be used as a substitute for real teaching. For parents, it means being attentive to how children use AI at home and whether or not they are exploring it, practicing it and constructing skills, or just counting on it to finish tasks. For policymakers and technology developers, this implies creating systems that support student alternative, provide reliable feedback, and avoid encouraging over-reliance. And for the scholars themselves, it’s a reminder that AI could be a tool for growth, but only when paired with their very own commitment and curiosity.
Regardless of technology, students have to feel empowered, autonomous and connected. Without these basic psychological needs, their motivation will diminish – with or without AI.
