Huan Huang

Dr. Huan Huang


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
4 September 2026 in Sustainability
Verified
Journal Article
Open access
PDF file
XHXinxin Hao
Xinxin Hao
JLJiangyu Li
Jiangyu Li
HHHuan Huang
Huan Huang
郝秉郝 秉钰
郝 秉钰
Against the backdrop of sustainable education and the digital transformation of higher education, AI assistants on online learning platforms have become important tools for facilitating students’ access to learning resources, providing immediate feedback, and supporting self-directed learning, thereby creating new opportunities for more effective and sustainable learning experiences. However, the psychological mechanisms linking AI assistant intelligence to students’ innovative behavior remain unclear. Based on Social Cognitive Theory (SCT), this study examines how AI assistant intelligence on online learning platforms relates to higher education students’ innovative behavior through academic self-efficacy and academic procrastination and further explores the moderating role of AI literacy. Using a two-phase time-lagged design, the study collected data through online questionnaires from students at Chinese universities, yielding a final matched sample of 503 students. The findings show that AI assistant intelligence is positively associated with both academic self-efficacy and academic procrastination, but it has no significant direct effect on innovative behavior. Importantly, these two mediators operate in opposing directions: academic self-efficacy transmits a positive indirect effect, whereas academic procrastination transmits a negative indirect effect on innovative behavior. In addition, AI literacy strengthens the positive relationship between AI assistant intelligence and academic self-efficacy while weakening its positive relationship with academic procrastination. These findings reveal the dual psychological pathways through which AI assistant intelligence shapes students’ innovative behavior, extend Social Cognitive Theory in intelligent learning environments, and offer practical implications for leveraging AI-assisted learning to foster students’ innovative capacity and inform the sustainable integration of AI in higher education.