Date
Publisher
arXiv
Artificial Intelligence (AI) is transforming higher education, but its benefits can vary depending on where, how, and how often it supports learning. While prior research emphasizes cognitive and academic outcomes, this study examines how AI chatbots support the psychological needs and motivational states of engineering students. A survey of college engineering students (n = 206) examined perceived effects of AI chatbots on autonomy, relatedness, and relief from competence frustration. Structural equation modeling with latent interaction effects examined how baseline autonomy, competence frustration, relatedness, and personal agency contributed to perceived AI outcomes. Results indicate that students perceived that AI provided the greatest benefits as relief from competence frustration, smaller benefits for autonomy, and the weakest benefits for relatedness. Baseline motivational states mattered more than demographic factors, and inattention moderated how baseline competence frustration and autonomy related to perceived AI-related benefits. These results offer insights into formulating design principles for engineering-specific AI-based tools.
Study at a glance
- Question: How does AI chatbot use relate to engineering students' psychological needs and attention challenges?
- Setting and data: Large public research university in the United States, late May to early June 2025, 206 undergraduate engineering students who use AI chatbots.
- Method: Survey analyzed using factor analysis and structural equation modeling (SEM) with latent interactions.
Why it matters
While research highlights cognitive outcomes of educational AI, evidence on psychological and motivational needs remains sparse, particularly for engineering students and learners with attention challenges.
Key findings
- Students perceived that AI chatbots provided the greatest benefit as relief from competence frustration, moderate benefits for autonomy, and the weakest benefits for relatedness.
- Baseline psychological needs and personal agency shaped perceived AI benefits more strongly than demographics, with higher baseline autonomy and competence frustration predicting greater relief from frustration.
- Higher inattention was associated with greater perceived relief from competence frustration, but it weakened the positive associations of baseline competence frustration and autonomy with AI benefits.
Summary drafted with AI from the full paper and may contain errors. See the full paper for details.
What is the application?
Who is the user?
Who age?
Why use AI?
Study design
