Jul 2026· Journal of Information and Communication Technologies· 0 citations
TL;DR
The results highlight the robustness of the extended UTAUT model, where the two constructs become predictors of behavioural intention to use of ChatGPT, indicating students’ dependency on the perceived reasoning of ChatGPT.
Abstract
The rapid advancement of generative artificial intelligence (AI) tools like ChatGPT is transforming various sectors, including education. Although many are adopting ChatGPT for learning, not all students are embracing it. This is because there are contrasting views regarding its usefulness, ease of use, reliability, and ethical implications. ChatGPT acceptance and usage behaviour have been frequently studied through the Unified Theory of Acceptance and Use of Technology (UTAUT) model. However, it may not completely describe the features of AI. Hence, this paper extends the UTAUT model by incorporating two constructs specifically on AI, namely, Perceived Intelligence and Perceived Anthropomorphism as predictors of the ChatGPT usage behaviour. The study followed a quantitative research design. Purposive sampling was used to collect data from 384 students at a public university in Northern Malaysia. Data was analyzed through Partial Least Squares Structural Equation Modeling. The results showed that all six predictors have significant effects on the Behavioural Intention with 48.3% of variance. Behavioural Intention predicts the actual Use Behaviour with 16.5% of variance. The results highlight the robustness of the extended UTAUT model, where the two constructs become predictors of behavioural intention to use. This indicated students’ dependency on the perceived reasoning of ChatGPT. Based on these predictors, the study has constructed a behavioural model to determine the ChatGPT usage among university students. The findings contribute by demonstrating the validity of the extended UTAUT model. Additionally, practical recommendations are provided to universities, educators, and AI developers for integrating ChatGPT in academic settings.
Artificial Intelligence (AI) technologies are increasingly transforming higher education by providing innovative tools that support students in learning, academic writing, and information processing. Despite the rapid adoption of generative AI tools such as ChatGPT, Grammarly, and QuillBot, the factors influencing undergraduate students’ intention to use these tools for learning remain insufficiently understood. This study aims to examine the determinants of students’ intention to use AI tools based on the Theory of Planned Behaviour (TPB). Specifically, the study investigates the influence of attitude, subjective norms, and perceived behavioural control on students’ behavioural intention to adopt AI technologies in academic contexts. This study adopts a quantitative approach, where data will be collected from approximately 300 undergraduate students from Universiti Teknologi MARA (UiTM), Malaysia, using a structured questionnaire. The measurement items are adapted from established literature and assessed using a five-point Likert scale. The collected data will be analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) through SPSS and SmartPLS software. The proposed framework suggests that students who perceive AI tools as useful and beneficial are more likely to develop positive attitudes toward their use. In addition, social influences from lecturers, peers, and institutions are expected to shape students’ perceptions and acceptance of AI tools. Furthermore, students’ confidence in their digital skills and access to technological resources may enhance their perceived behavioural control, which in turn strengthens their intention to use AI tools. This study contributes to the growing body of knowledge on AI adoption in higher education by applying TPB in the context of generative AI tools. The findings are expected to provide practical insights for universities in developing policies, training programs, and ethical guidelines to promote responsible and effective use of AI in academic learning environments.
Mohd Rozaini Abdul Rahim, W. Hasan, Mastura Roni et al.· International journal of res...· 0 citations
Many students consider statistics one of the difficult subjects to learn throughout their academic period because of many complex theories and statistical analysis methodologies, which can increase anxiety in the learning process. Generative Artificial Intelligence gives birth to ChatGPT, which provides interesting descriptions and allows independent learning. Nevertheless, not enough literature is found regarding the use of ChatGPT in the context of statistics learning, particularly in Indonesia. In this study, we aim to analyze the perceptions of using ChatGPT as a tool in statistics education through Technology Acceptance Model (TAM). A survey with a quantitative approach was conducted with 203 statistics learners (103 females, 100 males) who have already used ChatGPT. To obtain the data, Likert scale questionnaire was used, and PLS-SEM was applied in analyzing data through five constructs of Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Attitude Toward Using (AT), Behavioral Intention (BI), and Actual Use (AU). It was found that all five hypotheses were confirmed, and all relationships between constructs of TAM were positive and significant. Particularly, PEOU significantly affected PU (β = 0.347) and AT (β = 0.255), while AT had the highest impact on BI (β = 0.330). These findings indicate that ChatGPT is perceived as an assisting technological tool for learning statistics, where usability and attitudes of users become very crucial factors.
Siva Nur Samrotissaadah, Kemas Muslim Lhaksmana· Rabit : Jurnal Teknologi dan...· 0 citations
The rapid integration of artificial intelligence (AI) chatbots in higher education has transformed student learning experiences and institutional operations, yet comprehensive measurement tools for assessing student usage patterns remain limited. This study presents the development and psychometric validation of the AI Chatbots Usage Scale, a comprehensive instrument measuring perceptual and attitudinal dimensions of AI chatbot acceptance among higher education students. Using a two-phase methodology, the research employed separate samples for Exploratory Factor Analysis (EFA) (n = 374) and Confirmatory Factor Analysis (CFA) (n = 599) among university students aged 17–23 from the Faculty of Education in Egypt. The initial 25-item scale underwent rigorous expert validation and pilot testing before final administration. EFA revealed a four-factor structure comprising Ease of Use, Perceived Usefulness, Trust, and Accessibility, accounting for 42.48% of total variance. CFA demonstrated excellent model fit indices, with the multidimensional model significantly outperforming a unidimensional alternative. Internal consistency reliability was excellent across all factors, with coefficients ranging from 0.731 to 0.928. The validated scale demonstrates strong theoretical alignment with established technology acceptance frameworks while extending traditional models to accommodate AI-specific considerations. These findings provide researchers and educational institutions with a reliable, theoretically grounded instrument for assessing and optimizing AI chatbot implementation in higher education contexts.
A. Ibrahim, Mohamed Ali Nemt-allah· Scientific Reports· 0 citations
Generative artificial intelligence (AI) tools such as ChatGPT are increasingly integrated into higher education, yet research emphasizes students’ intentions to adopt these tools rather than their actual use. This study examined whether behavioral intention predicts self-reported usage frequency. Using secondary survey data from higher-education participants (N = 751), a three-item behavioral intention composite and a 0–7 usage-frequency index were analyzed using descriptive statistics, Pearson correlation, and simple linear regression. Mean intention was M = 3.35 (SD = 0.91) and mean frequency was M = 3.22 (SD = 2.10). Behavioral intention correlated positively with usage frequency, r = .49, p < .001, and significantly predicted use, B = 1.12, SE = 0.07, β = .49, R² = .239, F (1, 748) = 235.04, p < .001. Findings support TAM and UTAUT while suggesting that institutional supports are needed to translate intention into sustained and responsible AI use in higher education.
Brandon Hester· American Journal of STEM Edu...· 0 citations
The emergence of Artificial Intelligence (AI) tools like ChatGPT is changing the nature of academic writing by providing support in generating ideas, developing content, revision and editing. Although writing with AI offers benefits, little is known about its impact on learners’ writing strategies and motivation. Guided by Self-Determination Theory (SDT), this study examines the relationship between competence, autonomy, and relatedness in academic writing in the context of ChatGPT usage. This quantitative study involved 126 respondents from higher educational institutions. A 43-item Likert-scale questionnaire adapted from Raoofi et al. (2017) and Youssef et al. (2024) was used to collect data. The questionnaire was based on three constructs: autonomy, relatedness, and competence and showed high internal consistency (Cronbach’s α = .937). Data were analysed using descriptive, inferential, and correlation analyses in SPSS. Results show positive perceptions of using ChatGPT in improving academic achievement, critical thinking skills, and the motivation of students. Moreover, participants used metacognitive, cognitive, and effort-regulating writing strategies frequently. ChatGPT is a potential scaffold for supporting learners’ writing development, but it also motivates them by increasing their competence, autonomy, and relatedness.
Julina Munchar, T. A. Buhari, Sharifah Shahnaz Syed Husain et al.· International journal of res...· 0 citations
In recent years, artificial intelligence (AI) technologies have become increasingly prominent in education, with ChatGPT emerging as a notable tool that enhances learning experiences. This study explores teachers’ attitudes towards the adoption of ChatGPT as a learning technology, focusing on its potential benefits, limitations and implications for education. A quantitative approach was employed, involving an online survey targeting university educators. The survey assessed teachers’ perceptions of ChatGPT in higher education and identified barriers to its implementation. The conceptual framework integrates elements from the Technology Acceptance Model, the Unified Theory of Acceptance and Use of Technology and insights from risk perception theory. Data analysis was conducted using Partial Least Squares Structural Equation Modelling with SMART PLS software, ensuring reliability and discriminant validity. Findings indicate that most teachers view ChatGPT as an effective tool for enhancing student motivation, personalised learning and critical thinking. While teaching experience fosters positive perceptions and reduces perceived risks, it does not significantly influence challenges or trust in adoption decisions. Nonetheless, challenges persist, particularly regarding the reliability of information generated by ChatGPT. This study can assist policymakers, educators and technology developers in collaborating to implement practical and ethical AI-enabled tools like ChatGPT. Ultimately, while ChatGPT holds significant potential as an educational technology, its effectiveness hinges on addressing technical and pedagogical challenges.
Latifa Alzahrani· International journal of res...· 0 citations