Exploring the impact of generative AI-based technologies on learning performance through self-efficacy, fairness & ethics, creativity, and trust in higher education

Artificial Intelligence (AI) technologies have rapidly transformed the education sector and affect student learning performance, particularly in China, a burgeoning educational landscape. The development of generative artificial intelligence (AI) based technologies, such as chatbots and large language models (LLMs) like ChatGPT, has completely changed the educational environment by providing individualized and engaging programs. This study brings forward a model and hypothesis based on social cognitive theory and appropriate research. This investigation centers on how generative AI-based technologies influence students’ learning performance in higher education (HE) institutions and the function of self-efficacy, fairness & ethics, creativity, and trust in promoting these connections. Data is collected from 362 students at Chinese universities using purposive sampling. The proposed structural model was evaluated using partial least squares–structural equation modeling (PLS-SEM). The findings reveal that generative AI technologies such as LLM models exemplified by ChatGPT and chatbots significantly influence students’ learning performance through self-efficacy, fairness & ethics, and creativity. Furthermore, trust significantly moderates the relationship between fairness & ethics, creativity, and learning performance but negatively moderates the relationship between self-efficacy and learning performance. This study supports the new explanatory potential of social cognitive theory in technological practices. Additionally, this research suggests using generative AI technologies to enhance students’ digital learning and boost academic achievement.