Aug 2026· International Journal of Technology and Emerging Research· Vol 2, pp. 34-47· 0 citations· 56 references
TL;DR
Education institutions should focus on developing chatbot system programs with high efficiency, elegance and academic aptness while promoting their usage through institutional initiatives alongside peer influence, to increase student acceptance and intent to engage.
Abstract
Chatbots powered by artificial intelligence are becoming a part of higher education, supplementing teaching and learning as well as student services. Nevertheless, there is only limited evidence regarding the factors influencing students’ intention to use these technologies in the Indian higher education context. The influence of performance expectancy, effort expectancy, social influence and perceived trust on students’ intention to adopt artificial intelligence-based chatbot. This study adopted a quantitative research design using a self-administered, structured questionnaire administered to students of Pondicherry University. For data analysis, 477 valid responses were analyzed through IBM SPSS Statistics and SmartPLS after screening. The results demonstrate that performance expectancy was the strongest predictor of chatbot adoption intention, suggesting students are likely to adopt chatbots when they see obvious academic and learning gains. Social influence, perceived trust, and perceived intelligence also significantly and positively impact adoption intention, whereas effort expectancy does not significantly affect students' behavioral intention, implying that ease of use may be less important for digitally literate learners. This study recommends that educational institutions should focus on developing chatbot system programs with high efficiency, elegance and academic aptness while promoting their usage through institutional initiatives alongside peer influence. Combining the factors of the Technology Acceptance Model with artificial intelligence-specific features provides this study with a holistic view and practical advice to increase student acceptance and intent to engage.
Keywords: students; Chatbots; trust; adoption intention
This study explores teachers’ attitudes towards the adoption of ChatGPT as a learning technology, focusing on its potential benefits, limitations and implications for education and can assist policymakers, educators and technology developers in collaborating to implement practical and ethical AI-enabled tools like ChatGPT.
Latifa Alzahrani· International journal of res...· 0 citations
AI chatbots are becoming essential within contemporary education, significantly influencing student engagement and learning processes. They provide personalized support by delivering instant resources designed for individual learning styles and needs, enabling students to study subjects at their own pace. Therefore, this study seeks to investigate the impact of AI chatbots on self-reliance, their role in enhancing educational outcomes, and the factors influencing their adoption. A random sample of 384 questionnaires was collected from students enrolled in Jordanian universities. Data were collected through an online survey conducted from June to September 2025. The study's hypotheses were tested using SPSS for regression analyses of sub-hypotheses and PLS-SEM for the primary hypotheses. The results reveal that various dimensions of AI chatbots positively impact both self-reliance and the adoption of these tools, both individually and collectively, suggesting that their effective implementation can enhance learning outcomes and student engagement in educational settings. These results emphasize the significance of AI chatbots in fostering self-reliance and their adoption. The study advises integrating AI tools into the educational process while maintaining a balance with traditional teaching methods, as this approach can enhance learning outcomes and ensure that students benefit from both innovative and established educational strategies.
Unknown authors· International Journal of Dat...· 0 citations
To examine the effects of performance expectancy, effort expectancy, social influence, and facilitating conditions on university students’ behavioural intention to use and actual use of ChatGPT in higher education, while assessing the moderating role of ethical awareness. Methods: The proposed study adopts a quantitative cross-sectional survey design. Data will be collected from university students and analysed using structural equation modelling. Guided by the Unified Theory of Acceptance and Use of Technology, the model evaluates the technological, social, institutional, and ethical factors influencing students’ adoption and use of ChatGPT. Results: The proposed model suggests that students’ behavioural intention and actual use of ChatGPT are influenced by its perceived usefulness, ease of use, social influence, and the availability of institutional and technological support. Ethical awareness is expected to moderate these relationships because ChatGPT use may raise concerns related to academic integrity, plagiarism, overreliance, privacy, fairness, and reduced critical thinking. Conclusion: The study contributes to the literature by integrating technology acceptance with responsible AI use in higher education. It provides a framework for examining ChatGPT adoption patterns, students’ motivations for using the technology, and its implications for academic integrity, while offering practical guidance for universities, educators, and policymakers in developing AI literacy programmes and responsible-use policies.
Naga Thevan Mano Karan, Muhammad Hassan Arshad, Saralah Devi Mariamdaran Chethiyar et al.· Journal of Psychology &...· 0 citations
Universities increasingly have access to artificial intelligence, but access alone says little about whether these tools become part of everyday academic work. This article examines behavioural intention as the link between university teachers' and administrators' evaluations of AI and their subsequent use of it. It brings the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Theory of Planned Behavior into conversation with research on AI literacy, perceived risk and organisational support. Performance expectancy, effort expectancy, social influence, AI literacy and risk perceptions are expected to shape intention, while facilitating conditions affect both intention and the likelihood that intended use becomes sustained practice. The article distinguishes between two possible consequences of adoption: changes in teaching quality and changes in management efficiency. Neither consequence can be inferred from usage alone; each depends on the task, the quality of human review and the institutional arrangements surrounding the tool. Against the policy and organisational background of Shenyang, the article sets out propositions and measurement priorities for a later empirical study. Its main contribution is to clarify the sequence from appraisal to intention, from intention to use, and from use to educational or administrative outcomes.
Nan-Nan Hu, N. Noordin, Wong Siew Ping· Global Media and Social Scie...· 0 citations
The rapid adoption of generative artificial intelligence tools, particularly ChatGPT, is transforming teaching and learning in higher education. This study proposes an explainable artificial intelligence (XAI) framework that integrates the Unified Theory of Acceptance and Use of Technology (UTAUT2), machine learning, and explainability techniques to examine students’ intentions to use ChatGPT in academic contexts. Survey data were analyzed using Ordinary Least Squares regression, Random Forest, SHAP, Necessary Condition Analysis (NCA), Importance–Performance Map Analysis (IPMA), and K-Means clustering. The results indicate that Habit, Performance Expectancy, Hedonic Motivation, Social Influence, and Facilitating Conditions significantly influence behavioral intention, explaining 67.6% of the variance. Habit emerged as the strongest predictor, whereas Price Value had negligible influence. XAI analyses revealed that Effort Expectancy acts as a necessary condition for high adoption levels despite its limited direct effect. Four distinct student profiles were identified, highlighting heterogeneous patterns of AI integration and informing strategies for responsible and effective educational adoption. These findings provide evidence-based guidance for integrating AI literacy, responsible AI practices, and pedagogically meaningful ChatGPT use in higher education curricula.
The results show that AI self-efficacy, perceived usefulness, and relative advantage have significant positive effects on lecturers’ intention to use AI, and institutional support plays a pivotal moderating role, strengthening the relationship between intention to use AI and actual adoption behaviour.
A.M. Al-Darabseh, S. F. Padlee, Siti Nur et al.· Journal of Intelligent Decis...· 0 citations
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