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This study aims to investigate Sri Lankan Government university students’ acceptance of Chat Generative Pretrained Transformer (ChatGPT) for educational purposes. Using the unified theory of acceptance and use of technology 2 (UTAUT2) model as the primary theoretical lens, this study incorporated personal innovativeness as both a dependent and moderating variable to understand students’ ChatGPT use behaviour.

This quantitative study used a questionnaire survey to collect data. A total of 500 legitimate undergraduates from 17 government universities in Sri Lanka were selected for this study. Items for the variables were adopted from previously validated instruments. Partial least squares structural equation modelling (PLS-SEM) using SmartPLS 4 was used to investigate latent constructs’ relationships. Furthermore, the variables’ relative relevance was ranked using a two-stage artificial neural network analysis with the SPSS 27 application.

The results of the analysis revealed that eight of the nine proposed hypotheses were confirmed. The most significant determinants of behavioural intention were habit and performance expectancy, closely followed by hedonic motivation and perceived ease of use. Use behaviour was highly influenced by both behavioural intention and personal inventiveness. Though personal innovativeness (PI) was suggested as a moderator, the relationship was not significant.

The research highlights the impact of habit, performance expectancy and perceived ease of use on students’ acceptance of AI applications such as ChatGPT, emphasising the need for efficient implementation techniques, individual variations in technology adoption and continuous support and training to improve students’ proficiency.

This study enhances the comprehension of how undergraduate students adopt ChatGPT in an educational setting. The study emphasises the significance of certain variables in the UTAUT2 model and the importance of PI in influencing the adoption of ChatGPT in educational environments.

The purpose of this study was to investigate the factors that might influence the intention and use behaviour of e-learning systems by students in state universities in Sri Lanka.

The theoretical model for this study was primarily drawn from unified theory of acceptance and Use of Technology 2 (UTAUT2). Exogenous variables included performance expectancy, effort expectancy, social influence, work life quality, hedonic motivation, internet experience and facilitating condition, and their influence on behavioural intention and use behaviour were studied. Instrument was developed using validated items from past literature. Data for this quantitative study were collected from undergraduate and postgraduate students from 15 Sri Lankan state universities by self-administering and Web-form during second quarter of 2018. Structural equation modelling was used to see the insights from the valid data using IBM’s SPSS 25 and AMOS 22.

Results of the confirmatory factor analysis and subsequent evaluation of the structural model confirmed the proposed hypotheses, and it was found that constructs of UTAUT2 have a significant impact on and play an important role in behavioural intention to use and use behaviour of e-learning system by state university students in Sri Lanka.

The adoption of an e-learning system in Sri Lankan state universities is fairly low. Hence, investigation of what determinants might be contributing for adoption is important to enhance the learning experience of students and help them improve their knowledge. This paper contributes by delineating the factors that influence the acceptance and use of e-learning systems by students of state universities in Sri Lanka.

There is a significant decrease in students' attendance in Zoom classes compared to traditional classes. This paper investigates the factors that affect students' attitudes, behavioral intentions and actual use of Zoom for online classes at higher educational institutions (HEIs) in Sri Lanka.

This research uses the technology acceptance model (TAM) as a theoretical model. The data are collected from HEI students via an online survey form. The hypotheses between constructs in the model are tested using partial least squared–structural equation model.

The analysis shows that computer self-efficacy (CSE) affects perceived usefulness (PU) and perceived ease of use (PEU), which affects attitude (ATT) and behavioral intention (BI) and actual use (AU) of Zoom in a chain reaction. Further, PEU affects PU, which, in turn, affects BI. Furthermore, the effect size of PU to BI is larger than ATT to BI.

Students' attendance for Zoom classes mainly depends on CSE, PU and PEU. Therefore, HEIs should promote Zoom with interactive training before teaching online. Further, officials should revise the curriculum in schools to upsurge the CSE of students.

During coronavirus-19, no research was published on students' use of Zoom for online classes in the Sri Lankan context. Moreover, the TAM model has been modified by including CSE as an external variable.