## Rows: 3614## Columns: 16Generative artificial intelligence has rapidly become part of university learning. Students now use AI tools for studying, research, writing assistance and problem solving. While these technologies provide new opportunities for learning, they also raise questions about trust, academic performance and the future of education. Using survey data from more than 3,600 students, this story explores how AI is reshaping the university experience and how students are adapting to an increasingly AI-driven learning environment.
Artificial intelligence tools are now widely used by students across different disciplines. The chart below shows the most preferred AI tools among students and highlights how generative AI has become part of everyday academic life.
The visualisation shows that ChatGPT, Gemini and Copilot are the most commonly used AI tools among students. This suggests that generative AI has become a mainstream learning resource rather than a niche technology. The diversity of tools used also indicates that students are exploring different AI platforms depending on their academic needs and personal preferences.
While AI tools are widely adopted, students from different disciplines may prefer different platforms. This visualisation compares AI tool preferences across academic streams to reveal how AI usage varies between fields of study.
The heatmap highlights differences in AI preferences across academic disciplines. Although tools such as ChatGPT, Gemini and Copilot are widely used, the intensity of usage varies between streams. This suggests that students select AI tools based on the type of academic work they perform, including research, coding, writing and problem-solving activities.
Students spend different amounts of time using AI tools each day. This visualisation explores the relationship between daily AI usage and the perceived impact on academic performance.
The relationship between AI usage and academic performance is not entirely straightforward. While many students who use AI frequently report positive academic outcomes, there are also students who experience little or no improvement. This suggests that simply using AI more often does not guarantee better results. Instead, the effectiveness of AI may depend on how students integrate these tools into their learning process.
Students at different stages of their university journey may view AI differently. This visualisation explores how trust in AI tools varies across years of study.
Trust in AI is not uniform across all students. Some students report very high levels of trust, while others remain cautious. Differences across years of study may reflect increasing academic experience, changing learning requirements, and greater awareness of both the strengths and limitations of AI technologies.
Awareness of AI technologies may influence whether students are willing to pay for access to advanced AI tools. This visualisation explores the relationship between AI awareness and willingness to invest in AI services.
Students with higher levels of AI awareness are generally more willing to invest in AI tools. This suggests that AI is increasingly viewed as a valuable academic and professional resource rather than simply a free convenience. As AI becomes more integrated into education and employment, students may see access to advanced AI tools as an investment in their future skills and career opportunities.
The findings suggest that artificial intelligence is no longer an emerging technology within higher education. Students across different disciplines are actively using AI tools and incorporating them into their daily learning activities. However, attitudes towards AI remain mixed, particularly regarding trust and academic impact. As universities continue to adapt to generative AI, understanding how students use and perceive these technologies will become increasingly important. The future of higher education is likely to involve collaboration between human learning and AI-assisted support rather than a replacement of traditional educational practices.
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Generative AI tools were used during the planning and development of this assignment to assist with brainstorming, code refinement and structural feedback. All visualisations, analysis, interpretation and final written content were reviewed, edited and verified by the author.