Can Artificial Intelligence Make Learning More Visible and Less Fatiguing?

The integration of generative artificial intelligence in higher education opens new perspectives for making learning more transparent and accessible. However, its use raises questions about its real impact: does it help students reason better, develop their creativity and ethical sense, or does it simply make processes less understandable for teachers?

A recent study explored these issues by designing a learning environment where interactions between students and artificial intelligence are systematically recorded and analyzed. The goal was to understand how structured AI support influences the cognitive load perceived by learners—that is, the mental effort they feel when facing complex tasks. The results show that this support effectively reduces this load, not only directly but also indirectly by strengthening students’ confidence in their own creativity.

Confidence in one’s creativity, called belief in one’s creative potential, plays a key role here. It refers to the conviction a person has in their ability to innovate and solve problems in an original way. In an educational context where tasks require the integration of diverse knowledge and complex decision-making, this confidence allows students to see challenges not as insurmountable obstacles, but as opportunities to seize. Thus, the more students interact with a transparent and well-structured AI, the more their belief in their creativity is reinforced, which in turn reduces the mental fatigue they feel.

The transparency of AI is another central element. It means that artificial intelligence systems clearly explain their functioning, their data sources, and their limitations. Without this transparency, students might uncritically adopt AI suggestions, which would weaken their ability to think autonomously. Conversely, when AI is transparent, learners develop a more thoughtful relationship with the tool, which improves their engagement and their ability to manage the complexity of tasks.

The study was conducted among 276 second-, third-, and fourth-year students from various fields such as business, engineering, or social sciences. These students participated in a course based on concrete projects, such as planning and analyzing new products. They used generative AI tools to conduct market research, generate creative ideas, and assess the feasibility of their proposals. All their interactions with AI were recorded, allowing teachers to track their reasoning, strategies, and any misunderstandings.

The collected data confirms that AI support reduces perceived cognitive load, especially when students have strong confidence in their creativity. Additionally, AI transparency enhances this effect: the more students understand how AI works, the more they benefit from its help without losing their ability to think critically.

These results suggest that AI does not just provide ready-made information or answers. If well-designed, it can also help students better manage their mental effort and strengthen their confidence in terms of creativity. However, this only works if AI is integrated transparently and responsibly into the educational environment. Without these conditions, the risks of dependence or loss of autonomy remain real.

The study also shows that students do not all use AI in the same way. Some use it mainly to save time, while others use it as a thinking partner to explore new ideas. These differences highlight the importance of tailored educational support, which guides students toward a reflective and creative use of AI.

In the end, this research highlights that the impact of AI in education depends not only on the technology itself but especially on how it is integrated into teaching practices. Transparent AI, combined with structured educational support, can transform learning by making thinking processes more visible and helping students approach challenges with more confidence and creativity.

Bibliography

Report Source

DOI: https://doi.org/10.1007/s12528-026-09496-2

Title: Enhancing visible learning in higher education through transparent and responsible AI: an empirical model based on cognitive load and creative self-beliefs

Journal: Journal of Computing in Higher Education

Publisher: Springer Science and Business Media LLC

Authors: Min Jou; Yungwei Hao