# Emerging Drivers of Adoption of Generative AI Technology in Education: A Review
## The Three-Tier Framework for GenAI Technology Adoption in Education  
* Empirical Evidence  
[PERSON] et al. [47] found that job replacement anxiety notably reduces Behavioral Intention (BI) to adopt GenAI, as users fear that the technology may replace their current or future job roles. [PERSON] et al. [50] reported that GenAI anxiety significantly diminishes users' intentions to adopt the technology, particularly by negatively affecting performance expectancy and effort expectancy. Similarly, [PERSON] et al. [62] demonstrated that AI anxiety leads to a lower perception of the technology's usefulness and a reduced likelihood of adoption. These findings underscore that anxiety can create substantial barriers to GenAI adoption, highlighting the imperative of addressing these concerns for successful implementation and engagement with the technology. * Rationale  
Anxiety is an emerging predictor of GenAI adoption, as concerns about job displacement, ethical dilemmas, privacy risks, and the misuse of data can significantly deter users from adopting the technology. These anxieties often undermine trust, reduce perceived usefulness, and heighten resistance, especially in contexts where users are unfamiliar with or skeptical of AI technologies. Fears about GenAI can create substantial barriers to adoption, hindering its integration into workflows and educational practices. As GenAI continues to evolve and become more widespread, these concerns are likely to intensify, making it an increasingly critical factor in shaping adoption decisions. Addressing these anxieties through transparent communication, clear ethical guidelines, and trust-building measures will be necessary for mitigating fears and fostering a more positive outlook toward GenAI adoption, particularly in educational settings where such concerns are often amplified. * Definition
* Hydfulness or Hedonic Motivation refers to the degree to which users perceive using GenAI as enjoyable, fun, or intrinsically satisfying. This factor highlights the enjoyment and creative fulfilment that users derive from interacting with GenAI technologies, which can enhance the overall user experience beyond practical or utilitarian outcomes. * Empirical Evidence
* [PERSON] et al. [45] found that Hedonic Motivation significantly predicts Behavioral Intention (BI), emphasizing that the enjoyment users experience while engaging with GenAI plays a crucial role in their decision to adopt the technology. Similarly, [PERSON] et al. [46] identified perceived playfulness as a top predictor of BI, further reinforcing the idea that the intrinsic satisfaction users derive from interacting with GenAI enhances their likelihood of continued use. [PERSON] et al. [32] also highlighted that hedonic motivation strongly influences BI. These studies consistently emphasize that the fun and creative aspects of interacting with GenAI are major factors in fostering user engagement, which is fundamental for adoption and long-term integration. * Rationale  
Playfulness or hedonic motivation is an emerging predictor of GenAI adoption, as the enjoyment, creativity, and intrinsic satisfaction users derive from interacting with the technology significantly enhance their BI and likelihood of continued use. Studies suggest that when GenAI is perceived as fun and engaging, users are more inclined to incorporate it into their routines, leading to deeper and more sustained engagement. In educational contexts, hedonic motivation plays a particularly important role by stimulating creativity and exploration, which are vital for dynamic and innovative learning experiences. While playfulness alone may not be sufficient for widespread adoption, it supports ongoing user engagement and fosters a more positive attitude toward GenAI. This makes hedonic motivation an essential, though emerging, factor that strengthens adoption by making interactions both enjoyable and rewarding.