Transforming behavioral intention and academic performance: ChatGPT-4.0 insights through SEM,ANN,and cIPMA analysis

Abstract

This research paper has determined the impact of the new version, ChatGPT-4.0, on students’ performance in higher education as the technological world changes rapidly. We focused on essential variance predictors: information quality, system quality, service quality, and students’ behavioral intentions. ChatGPT-4.0 has significantly influenced students’ satisfaction, attitude, and academic performance, mainly in Pakistan, due to relevance, completeness, pleasure, and assurance support. Data were collected using questionnaires, with the participation of 1019 university students in Islamabad, Pakistan. We used partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) methods. The findings of the PLS-SEM and ANN methods showed that all factors had been corrected. Additional analyses, such as Necessary Condition Analysis (NCA) and Combined Importance Performance Map Analysis (cIPMA) were conducted to prioritize intervention areas. This article applies the Technology Acceptance Model and Information System Success Model to studying how factors work in applying ChatGPT-4.0 and add to the lifting of these models in this mechanism. Being the first study to adopt this approach, it is pretty comprehensive and gives insights that extend these models to a new set. ChatGPT-4.0 acts more as a tool in the intervention of education; therefore, it gives support more individually and interactively. The educator gives feedback and helps the user become a successful self-directed learner, therefore defining and attaining students’ educational goals.