Towards informed policy decisions: assessing student perceptions and intentions to use ChatGPT for academic performance in higher education

Artificial Intelligence holds vast potential in academia, yet concerns arise regarding its usage. This study examines students' perceptions and intentions to use ChatGPT through the signalling and elaboration likelihood model, which offers valuable insights into the transmission and procession of information. Two adoption approaches are considered: the peripheral route involves the utilization of simple cues requiring less cognitive effort, such as credibility, content quality, and critical mass, while the central route requires a person to critically evaluate the information rooted in perceived usefulness and technical advantages. Critical reasoning and digital efficacy are examined as moderating variables. Using convenience sampling, data from 694 respondents are collected via WeChat and www.wjx.cn in China. Structural Equation Modeling reveals a significant positive impact of perceived usefulness, technical advantages, credibility, content quality, and critical mass on student perceptions and intentions to use ChatGPT for academic performance. The findings inform policymakers and educators on AI tool integration in higher education, stressing the importance of understanding student perceptions and intentions. ChatGPT's perceived benefits and challenges underscore its influence on student performance and educational practices. This study advocates for ethical guidelines and support systems to address AI integration concerns, emphasizing critical reasoning and digital proficiency as pivotal factors.