Dataset for: Generative AI as a Driver for Critical Thinking: Integrating Information Quality, Self-Efficacy, and Learning Motivation in Indonesian Higher Education

The implementation of Generative Artificial Intelligence (GenAI) in higher education has drastically transformed learning methods, yet the impact of GenAI usage on critical thinking abilities via students' internal psychological influences still requires more in-depth investigation. This study aims to analyze the influence of information quality and habit on critical thinking, with the mediating roles of use of GenAI, self-efficacy, and learning motivation. This research was conducted using a quantitative approach and purposive sampling technique, involving 421 active students from various levels of higher education in Indonesia. Data analysis was performed using SmartPLS 4 software and utilized the Partial Least Squares Structural Equation Modeling (PLS-SEM) method to test model validity and hypotheses. The results of this study indicate that information quality and habit exert a significant influence on GenAI usage. Furthermore, the use of GenAI is proven to be a strong factor in enhancing self-efficacy and learning motivation, while also contributing significantly to the improvement of students' critical thinking abilities. It can be concluded from these research results that the use of GenAI supported by quality information does not result in passive dependence, but rather functions as a catalyst that enhances self-efficacy and academic motivation, thereby encouraging the development of higher-order thinking processes in academic activities.