Motivation and emotion/Book/2026/Artificial intelligence and academic motivation

Artificial intelligence and academic motivation:
How does artificial intelligence influence students’ motivation to learn, engage, and achieve?

Overview

Figure 1. An image of an AI robot teaching a young student Imagine this... You're sitting at your desk. On your desk is your open laptop with an empty blank page which is for an assignment that is due tomorrow night. You've been putting it off for weeks now, knowing you will have to do severall hours to research, plan and write it out. You just felt too unmotivated to write it, thinking you would do it the next day which happened to become a regular occurance. You're just not sure what to do. You only have tonight and not many hours left. You then think about your friends, they had recently gotten into using AI to help write a lot of their work. They had always recommended you to use it, but you were never that interested in it, prefering to use your own work. However, the situation was dire, and the sound of AI seemed very good right now. You get onto ChatGPT and start to enter in the assignment questions. After a few hours you're done. You finished your assignment on time. AI had significantly helped write and perfect a lot of the material. You find that it was so much easier to just do this than to bother to research for days on end. Maybe you'd do this next time too.

• Artifical Intelligence (AI) is often defined as technology that stimulates human intelligent behaviours, and is trained to learn human behaviours such as learning, judgement, and decision-making (Zhan & Lu, 2021). AI is rapidly developing and creating new advancements regularly in recent years, particularly in various aspects in the education systems (Pertiwi et al., 2024). AI has been making its way into classrooms to help further aid learning in everyday student learning habits to help with overall student achievement and motivation to learn.
• It is important to understand the recent emerging involvement of AI in academic settings as it while there are positive effects of using AI platforms, there are still issues to be addressed such as over reliance of the platforms. Being too over reliant on generative AI can lead to the habitual avoidance of using ones cognitive and critical thinking skills, particulary in the development of children (Fan et al., 2024).
• It is also important for us all to understand what motivates students to learn in the first place, and by doing that undertand how we can ethically keep utilising the use of AI in everyday academic settings. By doing so, it is possible to promote students motivation to learn, and be able to raise their overall learning achievement (Hmoud et al., 2024).

Focus questions What factors influence students' motivation to learn? What are the positive and negative effects of AI on students' motivation? How has AI changed the way students approach learning? How does reliance on AI influence students' learning habits?

What motivates students?

Understanding motivation

• Motivation is split into two main sub-categories (Legault, 2016).
• Entrinsic motivation is often defined as when people perform a task in order to attain an outcome that is separable from the action itself, like getting a reward (Legault, 2016).
• Intrinsic motivation is defined as when people are curious and interested, while seeking out challenges and developing their skills and knowlege without the presence of a reward (Domenico & Ryan, 2017; Legault, 2016).

Known factors influencing motivation to learn

• School management has been found to be highly influential on students learning in school, showing that encouragement to be diligent and loving to do what you are doing is beneficial in motivation in shcool settings (Hodis & Hodis, 2022.)
• Another motivation is having good social support around people encourages them to motivate not only themselves, but also each other (Hodis & Hodis, 2022). Having negative influences around you decreases motivation.
• One of the most important factors that can increase motivation is simply having a well educated teacher that encourage students in a positive manner. When students are young, it is also beneficial to have educated parents who try to ecourage learning in children in settings out of school (Hodis & Hodis, 2022).

Quiz:

"A desire to engage in an activity because it is personally interesting, enjoyable, or satisfying, rather than because of external rewards or pressures".

Which type of motivation is this?

	Achievement Motivation
	Extrinsic Motivation
	Intrinsic Motivation
	Affiliation Motivation

Effects of AI on student motivation

Positive effects of using AI

• Research had shown that generative AI powered systems that are acting as effective agents can support and and help improve learning and regulation processes in students (Fan et al., 2025)
• AI has been found to engage students in meaningful ways by fostering curiosity, autonomy, and instrinsic motivation in their learning journies (Pertiwi et al., 2024).
• Can reduce overall learner anxiety (Hmoud et al., 2024).

Negative effects of using AI

• Reinforces state of metacognitive laziness and adds to the lack of development in the use of critical thinking skills, making students become over-reliant using AI (Fan et al., 2025).
• Though can generate content from existing data and providing people with high-quality materials, it cannot provide contextualised in person explanations that a teachr can provide, so it cannot fully replace teachers. (Fan et al., 2025).
• Potential privacy and security issues (Oseni, 2021) .

Impact of AI on student learning

Students approach to learning

• Students currently prioritise learning that is increasingly fast and optimaly (Zhai et al., 2024).
• Students have instant support for understanding any question through AI chatbots (Hmoud et al., 2024).
• Students are becoming more engaged since AI started to become implemented (Vieriu & Petra, 2025).

Change of approach to learning due to AI

• Students have the ability to access most information online with the click of a finge due to AI, unlike before where most information is told trough textbooks and teachers (Parhanuddin et al., 2025).
• Learning is more personalised and suited to each individual (Parhanuddin e al., 2025).
• Ideas can be brainstormed through AI (Vieriu & Petra, 2025).

AI reliance on student learning habits

Are students becoming too reliant?

• A study found that there is overreliance in using AI, and that this overreliance tends to impact cognitive abilities as individuals increasingly choose fast and optimal solutions over solutions that are slower from practicality (Zhai et al., 2024).
• By using AI too much, students can gain an overdependance on specific abilities such as decision-making, critical thinking, and analytical reasoning (Zhai et al., 2024).
• Through this trend which continues to develop and transform as AI is becoming more prelavent, potential erosion of critical cognitive skills may happen an worsen (Zhai et al., 2024).

What do learning habits look like today?

• More personalised learning due to the implementation of AI, targeting each inidviduals students specific needs to help acheive higher achievements (Parhanuddin et al., 2025).
• Studying with more digital tools that integrate AI, rather than just focusing on paper text books (Parhanuddin et al., 2025).
• Collaboration with peers and online chat (Hmoud et al., 2024).

Conclusion

• AI has shown both positive and negative effects on students and the entire academic setting.
• Learning ways have changed and developed to involve AI, which contiues to change as AI does.
• Further study should be conducted to better help each academic setting understand how they can ethically involve the use of AI to be beneficial for learning so that students are still using critical thinking skills.

See also

• Artifical Intelligence (Wikipedia)
• Motivation (Wikiversity)
• Intrinsic motivation in artificial intelligence (Wikipedia)

References

Di Domenico, S. I., & Ryan, R. M. (2017). The emerging neuroscience of intrinsic motivation: A new frontier in self-determination research. Frontiers in Human Neuroscience, 11, 145. https://doi.org/10.3389/fnhum.2017.00145

Fan, Y., Tang, L., Le, H., Shen, K., Tan, S., Zhao, Y., ... & Gašević, D. (2025). Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes, and performance. British Journal of Educational Technology, 56(2), 489-530. https://doi.org/10.1111/bjet.13544

Hmoud, M., Swaity, H., Hamad, N., Karram, O., & Daher, W. (2024). Higher education students’ task motivation in the generative artificial intelligence context: The case of ChatGPT. Information, 15(1), 33. https://doi.org/10.3390/info15010033

Hodis, F. A., & Hodis, G. M. (2022). Key factors that influence students’ motivation to learn: Implications for teaching. Set: Research Information for Teachers, 2, 37-41. https://doi.org/10.18296/set.1509

Legault, L. (2016). Intrinsic and extrinsic motivation. Encyclopedia of personality and individual differences, 10, 978-3. https://doi.org/10.1007/978-3-319-28099-8_1139-1

Oseni, A., Moustafa, N., Janicke, H., Liu, P., Tari, Z., & Vasilakos, A. (2021). Security and privacy for artificial intelligence: Opportunities and challenges. arXiv preprint arXiv:2102.04661. https://doi.org/10.1145/1122445.1122456

Parhanuddin, L., Tohri, A., & Suhardi, M. (2025). The Effect of AI (Artificial Intelligence) in Education on Student Motivation: A Systematic Literature Review. Journal for Lesson and Learning Studies, 8(1), 1-10. https://doi.org/10.23887/jlls.v8i1.91141

Pertiwi, R. W. L., Kulsum, L. U., & Hanifah, I. A. (2024). Evaluating the impact of artificial intelligence-based learning methods on students' motivation and academic achievement. International Journal of Post Axial: Futuristic Teaching and Learning, 49-58. https://doi.org/10.59944/postaxial.v2i1.279

Vieriu, A. M., & Petrea, G. (2025). The impact of artificial intelligence (AI) on students’ academic development. Education Sciences, 15(3), 343. https://doi.org/10.3390/educsci15030343

Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students' cognitive abilities: a systematic review. Smart Learning Environments, 11(1), 28. https://doi.org/10.1186/s40561-024-00316-7

Zhang, C., & Lu, Y. (2021). Study on artificial intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, 23, 100224. https://doi.org/10.1016/j.jii.2021.100224

External links

• How AI could save (not destroy) education (TED talk)
• How AI has accelerated the demise of critical thinking in universities (ABC News)