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Helpful or Harmful? How AI Assistant Intelligence on Online Learning Platforms Shapes Students’ Innovative Behavior for Sustainable Education

Year: 2026

Type: article

Abstract: 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.

Source: Sustainability

DOI: 10.3390/su18179084

Authors: Xinxin Hao, Jiangyu Li, Huan Huang, Bingyu Hao

Institutions: Chengdu University, Sichuan University, Shaanxi Normal University

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $2,896