Scientists: Neural Networks Boost Students' Interest In Learning
- 9.11.2026, 19:22
They make learning more interesting and effective.
Training neural networks improve academic performance, but indirectly: they engage students in the learning process, and it is this engagement that leads to good grades. A survey of 438 students conducted by researchers at Tongling University and Taiyuan University in China was published in the journal Frontiers in Psychology.
Students from universities in Shanxi Province participated in the online survey: They reported how often they use chatbots, AI tutors, and writing assistants; how much effort they put into their studies; and how they assess their own success. Engagement was defined as the willingness to devote energy, interest, and attention to their studies. The responses were analyzed using structural modeling, which maps out the chains of influence between different factors.
The correlation between neural networks and engagement was significant (correlation coefficient 0.52), while the correlation with grades was weaker (0.36). Engagement, in turn, is closely linked to academic performance (0.47). The direct effect of AI on grades is weak (0.18), while the indirect effect, via engagement, accounts for 0.21 of the total effect of 0.39—more than half. The educational benefits of neural networks are realized primarily through interest and immersion, rather than through quick answers.
The authors explain the mechanism as follows: instant feedback and step-by-step explanations reduce unnecessary mental load, helping students persevere with difficult tasks and figure them out on their own.
“The value of AI for education cannot be fully understood from a purely technological perspective,” the researchers write. According to them, the effect depends on whether the student’s thinking remains engaged in working with the AI or is replaced by ready-made answers.
This topic has been hotly debated for years: critics are convinced that students delegate their homework to neural networks and are losing the ability to think, while universities around the world argue over whether chatbots should be considered cheat sheets or tools. The new study adds weight to the argument of those who support the second viewpoint. Until the findings are verified through long-term observations, neural networks should be considered a tool that boosts interest in learning.
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