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This article aims to draw a conceptual model that integrates the view from the entrepreneurial event model with entrepreneurial education and prior self-employment experience. The model tests the role of entrepreneurial education on the formation of intentions to become an entrepreneur and examines whether prior self-employed experiences moderate the route from entrepreneurial education, entrepreneurial perceived feasibility (PF) and perceived desirability (PD) into the entrepreneurial intention (EI).

The authors operated on a sample of 389 master's students by applying Cronbach's alpha, exploratory factor analysis, confirmatory factor analysis and structural equation modelling to illustrate the links between constructs.

The study found that entrepreneurial education is positively correlated with PF, PD, and intention to enter entrepreneurial activities. PD is determined as a partial mediator in the entrepreneurial education–intention link and full mediator in PF and EI. Moreover, the study revealed that prior self-employed experiences serve as a positive moderator in the path from entrepreneurial education and PD to EI.

The study offers several recommendations based on research findings so as to nurture and promote entrepreneurial activities among master's students.

The current research provides novel insights about the relationship between entrepreneurial education and intentions to become an entrepreneur over and about the central antecedents in the entrepreneurial event model and moderation effects of prior self-employed experiences.

Although previous research has acknowledged the significance of comprehending the initial acceptance and adoption of ChatGPT in educational contexts, there has been relatively little focus on the user’s intention to continue using ChatGPT or its continued usage. Therefore, the current study aims to investigate the students’ continuance intentions to use ChatGPT for learning by adopting the stimulus–organism–response (SOR) model.

This study has employed the SOR model to investigate how UTAUT factors (such as performance expectancy, facilitating conditions, effort expectancy and social influence) influence the cognitive responses of students (e.g. trust in ChatGPT and attitude towards ChatGPT), subsequently shaping their behavioral outcomes (e.g. the intention to continue using ChatGPT for study). A sample of 392 higher students in Vietnam and the PLS-SEM method was employed to investigate students’ continuance intention to use ChatGPT for learning.

This study reveals that students’ continuance intention to use ChatGPT for learning was directly affected by their attitude toward ChatGPT and trust in ChatGPT. Meanwhile, their attitude toward ChatGPT was built on effort expectancy, social influence, and facilitating conditions and trust in ChatGPT was developed from effort expectancy and social influence.

By extending the analysis beyond initial acceptance, this research provides valuable insights into the factors that influence the sustained utilization of ChatGPT in an educational environment.