AI Self-efficacy – the confidence in one’s capabilities to effectively interact, understand, learn about, and use AI technologies – is essential for students participating in an AI-driven world. A recent study by Bewersdorff et al. (2024) explores how cognitive, affective, and behavioral variables related to AI build university students’ self-efficacy in AI. Conducted among 1,465 students from the United States, the United Kingdom, and Germany, the authors used a path model to examine how AI literacy, attitudes, interests, and usage contribute to students’ confidence in understanding and using AI technologies.

Key findings reveal that positive attitudes towards AI and frequent AI use significantly increase students’ interest in AI. This interest and a baseline level of AI literacy directly enhances students’ self-efficacy or belief in their ability to effectively use and learn about AI. Surprisingly, negative attitudes towards AI had minimal impact on AI interest, suggesting that positive factors play a more critical role in fostering engagement.

Student Group Profiles 

The study also identified three distinct student groups:

• AI Advocates (48%): High interest, positive attitudes, frequent use, and confidence in AI.
• Cautious Critics (21%): Low literacy, low interest, and high skepticism about AI’s role and safety.
• Pragmatic Observers (31%): Moderate interest and balanced perspectives on AI.

Discipline and Gender profiles

The authors highlight that the distribution of disciplines and gender among the groups reveals important insights. For example, Cautious Critics are predominantly from Arts and Humanities and Social Sciences, while AI Advocates are primarily from Engineering and Technology. Additionally, the male dominance among AI Advocates and the female majority among Cautious Critics suggest the need for more inclusive AI education programs.

Key Takeaways for Educators and Learners

The authors recommend differentiated educational strategies, e.g., for AI Advocates. Advanced courses emphasizing ethics and societal impacts are key. Cautious Critics benefit from relatable, accessible content to address their skepticism, while Pragmatic Observers need motivating materials to deepen their engagement.

Summing up, this study highlights that fostering AI self-efficacy requires more than just technical knowledge. Positive attitudes, interest, and hands-on experiences with AI are crucial for developing confidence. Educators are encouraged to design inclusive programs tailored to these diverse groups, ensuring all students are prepared for an AI-driven world. This study underscores the importance of aligning AI education with students’ different cognitive, emotional, and behavioral profiles for better learning outcomes.

References

• Bewersdorff, A., Hornberger, M., Nerdel, C., & Schiff, D. (2024). AI Advocates and Cautious Critics: How AI attitudes, AI interest, use of AI, and AI literacy build university students’ AI self-efficacy. Computers and Education: Artificial Intelligence. https://doi.org/10.1016/j.caeai.2024.100340