What Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AI
#AI chatbots #Technology Acceptance Model #Student adoption #Perceived usefulness #Perceived enjoyment #Trust in AI #Conversational AI
📌 Key Takeaways
- Perceived usefulness is the strongest predictor of students' intention to use conversational AI
- Perceived ease of use affects behavioral intention indirectly through perceived usefulness
- Trust and subjective norms significantly influence perceptions of usefulness
- Perceived enjoyment has both direct and indirect effects on usage intentions
📖 Full Retelling
Researchers Griffin Pitts and Sanaz Motamedi published a study on February 24, 2026, through arXiv that investigates what drives students' adoption of AI chatbots for learning purposes, examining the factors that influence their acceptance of conversational AI technology in educational contexts. The study builds upon the Technology Acceptance Model (TAM) to understand how students perceive and adopt conversational AI tools, extending it with additional factors such as trust, perceived enjoyment, and subjective norms to capture social and affective influences on AI adoption. Using partial least squares structural equation modeling, the researchers found that perceived usefulness remains the strongest predictor of students' intention to use conversational AI for learning tasks. The research revealed that perceived ease of use does not exert a significant direct effect on behavioral intention once other factors are considered, instead operating indirectly through perceived usefulness. The study also discovered that trust and subjective norms significantly influence perceptions of usefulness, while perceived enjoyment has both direct and indirect effects on usage intentions, suggesting that adoption decisions for conversational AI systems are influenced less by effort-related considerations and more by confidence in system outputs, affective engagement, and social context.
🏷️ Themes
Technology Acceptance, Educational Technology, Human-Computer Interaction
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Original Source
--> Computer Science > Human-Computer Interaction arXiv:2602.20547 [Submitted on 24 Feb 2026] Title: What Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AI Authors: Griffin Pitts , Sanaz Motamedi View a PDF of the paper titled What Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AI, by Griffin Pitts and 1 other authors View PDF HTML Abstract: Conversational AI tools have been rapidly adopted by students and are becoming part of their learning routines. To understand what drives this adoption, we draw on the Technology Acceptance Model and examine how perceived usefulness and perceived ease of use relate to students' behavioral intention to use conversational AI that generates responses for learning tasks. We extend TAM by incorporating trust, perceived enjoyment, and subjective norms as additional factors that capture social and affective influences and uncertainty around AI outputs. Using partial least squares structural equation modeling, we find perceived usefulness remains the strongest predictor of students' intention to use conversational AI. However, perceived ease of use does not exert a significant direct effect on behavioral intention once other factors are considered, operating instead indirectly through perceived usefulness. Trust and subjective norms significantly influence perceptions of usefulness, while perceived enjoyment exerts both a direct and indirect effect on usage intentions. These findings suggest that adoption decisions for conversational AI systems are influenced less by effort-related considerations and more by confidence in system outputs, affective engagement, and social context. Future research is needed to further examine how these acceptance relationships generalize across different conversational systems and usage contexts. Subjects: Human-Computer Interaction (cs.HC) ; Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Emerging Technologies (cs.ET) ACM classes:...
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