Gender Differences in Perceived Enjoyment and AI Learning Anxiety in Human-Ai Interactions: An Affordance Theory Perspective

Drawn from Gibson's Affordance Theory, this study explored young generations' attitudes toward perceived enjoyment and perceived anxiety in human-AI interactions. Particularly, we examined gender differences among Generation Z after interacting with generative AI (GenAI) chatbots for travel planning. A sample of 195 participants (107 males, 88 females) participated in this study to interact with GenAI chatbots for about 20 minutes and then completed an online survey immediately. The findings indicated that no significant gender differences emerged in perceived affordance and perceived enjoyment. However, a gender gap was found in AI learning anxiety, with females reporting significantly higher anxiety levels than males. Interestingly, young females may feel more anxious while also experience greater enjoyment in interacting with AI chatbots. These results indicated the dual role of psychological factors can simultaneously hinder and facilitate the use of AI chatbots. This study extends Gibson's Affordance Theory to the domain of AI chatbots, demonstrating how perceived action possibilities influence emotional responses in human-AI interactions. Future research should continue to explore the complex interplay between user emotions and demographic factors in different age and educational level groups.