Exploring the Role of Generative AI in Enhancing Mobile Learning Adoption: A Case Study with Notion

Abstract

The rapid advancement of Generative Artificial Intelligence (GenAI) offers new opportunities for enhancing mobile learning adoption, particularly through platforms like Notion. However, adoption remains inconsistent among university students. This study examines the factors influencing the adoption of Notion enhanced with GenAI functionalities, using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Data were collected from 90 university students and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that Performance Expectancy (PE) is the most significant predictor of Behavioral Intention (BI), highlighting the importance of AI-driven features such as automated content generation and personalized learning recommendations. In contrast, Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC) do not significantly influence adoption, suggesting that digital familiarity reduces perceived barriers. The study extends the UTAUT model to the context of AI-enhanced mobile learning tools. It recommends emphasizing productivity-enhancing features and intuitive AI automation to increase adoption. Future research should explore longitudinal effects, cross-cultural differences, and additional motivational drivers.

Classification JEL : I21 ; O33 ; C88

Paper type : Empirical Research