3,521
Views
2
CrossRef citations to date
0
Altmetric
Articles

ChatGPT adoption and anxiety: a cross-country analysis utilising the unified theory of acceptance and use of technology (UTAUT)

ORCID Icon, ORCID Icon, ORCID Icon &
Pages 831-846 | Received 04 Oct 2023, Accepted 18 Mar 2024, Published online: 27 Mar 2024

References

  • Abadie, Amelie, Soumyadeb Chowdhury, and Sachin Kumar Mangla. 2024. “A Shared Journey: Experiential Perspective and Empirical Evidence of Virtual Social Robot ChatGPT's Priori Acceptance.” Technological Forecasting and Social Change 201:123202. https://doi.org/10.1016/j.techfore.2023.123202
  • Alavi, Maryam, Dorothy E. Leidner, and Reza Mousavi. 2024. “A Knowledge Management Perspective of Generative Artificial Intelligence.” Journal of the Association for Information Systems 25 (1): 1–12. https://doi.org/10.17705/1jais.00859
  • Ali, Omar, Peter A. Murray, Mujtaba Momin, Yogesh K. Dwivedi, and Tegwen Malik. 2024. “The Effects of Artificial Intelligence Applications in Educational Settings: Challenges and Strategies.” Technological Forecasting and Social Change 199:123076. https://doi.org/10.1016/j.techfore.2023.123076
  • Bin-Nashwan, Saeed Awadh, Mouad Sadallah, and Mohamed Bouteraa. 2023. “Use of ChatGPT in Academia: Academic Integrity Hangs in the Balance.” Technology in Society 75 (November): 102370. https://doi.org/10.1016/j.techsoc.2023.102370
  • Camilleri, M. A. 2024. “Factors Affecting Performance Expectancy and Intentions to use ChatGPT: Using SmartPLS to Advance an Information Technology Acceptance Framework.” Technological Forecasting and Social Change 201:123247. https://doi.org/10.1016/j.techfore.2024.123247
  • Chan, Cecilia Ka Yuk, and Wenjie Hu. 2023. “Students’ Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education.” International Journal of Educational Technology in Higher Education 20 (1): 43. https://doi.org/10.1186/s41239-023-00411-8
  • Cotton, Debby R. E., Peter A. Cotton, and J. Reuben Shipway. 2023. “Chatting and Cheating: Ensuring Academic Integrity in the era of ChatGPT.” Innovations in Education and Teaching International 61 (2): 228–239.
  • Davis, Fred D. 1989. “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology.” MIS Quarterly 13 (3) Management Information Systems Research Center, University of Minnesota: 319–340. https://doi.org/10.2307/249008
  • Department for Business and Trade. 2024. “UK infrastructure – great.gov.uk international.” Accessed 12 March 2024. https://www.great.gov.uk/international/content/investment/why-invest-in-the-uk/uk-infrastructure/.
  • Department for Education. 2023. “Generative Artificial Intelligence (AI) in Education. Education, Training and Skills.” Accessed 24 February 2024. https://www.gov.uk/government/publications/generative-artificial-intelligence-in-education.
  • Dwivedi, Yogesh K., Nir Kshetri, Laurie Hughes, Emma Louise Slade, Anand Jeyaraj, Arpan Kumar Kar, Abdullah M. Baabdullah, et al. 2023. “‘So What If ChatGPT Wrote It?’ Multidisciplinary Perspectives on Opportunities, Challenges and Implications of Generative Conversational AI for Research, Practice and Policy.” International Journal of Information Management 71 (August): 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642.
  • El-Masri, Mazen, and Ali Tarhini. 2017. “Factors Affecting the Adoption of E-learning Systems in Qatar and USA: Extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2).” Educational Technology Research and Development 65 (3): 743–763. https://doi.org/10.1007/s11423-016-9508-8
  • Fornell, Claes, and David F. Larcker. 1981. “Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics.” Journal of Marketing Research 18 (3): 382–388. https://doi.org/10.1177/002224378101800313
  • Foroughi, Behzad, Madugoda Gunaratnege Senali, Mohammad Iranmanesh, Ahmad Khanfar, Morteza Ghobakhloo, Nagaletchimee Annamalai, and Bita Naghmeh-Abbaspour. 2023. “Determinants of Intention to Use ChatGPT for Educational Purposes: Findings from PLS-SEM and fsQCA.” International Journal of Human–Computer Interaction 0 (0) Taylor & Francis: 1–20.
  • Gulati, Anmol, Harish Saini, Sultan Singh, and Vinod Kumar. 2024. “Enhancing Learning Potential: Investigating Marketing Students’ Behavioral Intentions to Adopt ChatGPT.” Marketing Education Review, 1–34. https://doi.org/10.1080/10528008.2023.2300139
  • Hair, Joseph F., David Mary Celsi, J. Ortinau, and Robert P. Bush. 2010. Essentials of Marketing Research. New York: McGraw-Hill.
  • Harman, D. 1967. “A Single Factor Test of Common Method Variance.” Journal of Psychology 35:359–378.
  • Holtzman, Adam L., Deidre B. Pereira, and Anamaria R. Yeung. 2018. “Implementation of Depression and Anxiety Screening in Patients Undergoing Radiotherapy.” BMJ Open Quality 7 (2): e000034.
  • Hu, Li-tze, and Peter M. Bentler. 1999. “Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives.” Structural Equation Modeling: A Multidisciplinary Journal 6 (1): 1–55. https://doi.org/10.1080/10705519909540118
  • Hu, Sailong, Kumar Laxman, and Kerry Lee. 2020. “Exploring Factors Affecting Academics’ Adoption of Emerging Mobile Technologies-an Extended UTAUT Perspective.” Education and Information Technologies 25 (5): 4615–4635. https://doi.org/10.1007/s10639-020-10171-x
  • Jha, Jivesh, and Alok Kumar Yadav. 2022. “How is Artificial Intelligence Changing the World? What Nepal should do to Tap it?” Nepal Live Today, Accessed 12 March 2014. https://www.nepallivetoday.com/2022/02/10/how-is-artificial-intelligence-changing-the-world-what-nepal-should-do-to-tap-it/.
  • Khechine, Hager, and Sawsen Lakhal. 2018. “Technology as a Double-edged Sword: From Behavior Prediction with UTAUT to Students’ Outcomes Considering Personal Characteristics.” Journal of Information Technology Education: Research 17 (April): 63–102. https://doi.org/10.28945/4022
  • Kock, Ned, and Gary Lynn. 2012. “Lateral Collinearity and Misleading Results in Variance-Based SEM: An Illustration and Recommendations.” Journal of the Association for Information Systems 13 (7): 546–580. https://doi.org/10.17705/1jais.00302
  • Korinek, A. 2023. “Generative ai for Economic Research: Use Cases and Implications for Economists.” Journal of Economic Literature 61 (4): 1281–1317. https://doi.org/10.1257/jel.20231736
  • Kumar, Jeya Amantha, and Brandford Bervell. 2019. “Google Classroom for Mobile Learning in Higher Education: Modelling the Initial Perceptions of Students.” Education and Information Technologies 24 (2): 1793–1817. https://doi.org/10.1007/s10639-018-09858-z
  • Kwak, Yeunhee, Yon Hee Seo, and Jung-Won Ahn. 2022. “Nursing Students’ Intent to use AI-based Healthcare Technology: Path Analysis Using the Unified Theory of Acceptance and Use of Technology.” Nurse Education Today 119:105541. https://doi.org/10.1016/j.nedt.2022.105541
  • Lindebaum, D., and P. Fleming. 2023. “Chatgpt Undermines Human Reflexivity, Scientific Responsibility and Responsible Management Research.” British Journal of Management, 1–12.
  • Maican, Catalin Ioan, Ana-Maria Cazan, Radu Constantin Lixandroiu, and Lavinia Dovleac. 2019. “A Study on Academic Staff Personality and Technology Acceptance: The Case of Communication and Collaboration Applications.” Computers & Education 128 (January): 113–131. https://doi.org/10.1016/j.compedu.2018.09.010.
  • Mannuru, Nishith Reddy, Sakib Shahriar, Zoë A. Teel, Ting Wang, Brady D. Lund, Solomon Tijani, Chalermchai Oak Pohboon, et al. 2023. “Artificial Intelligence in Developing Countries: The Impact of Generative Artificial Intelligence (AI) Technologies for Development.” Information Development: 1–19.
  • Martín-García, Antonio Víctor, Fernando Martínez-Abad, and David Reyes-González. 2019. “TAM and Stages of Adoption of Blended Learning in Higher Education by Application of Data Mining Techniques.” British Journal of Educational Technology 50 (5): 2484–2500. https://doi.org/10.1111/bjet.12831
  • Meinhardt-Injac, Bozana, and Carina Skowronek. 2022. “Computer Self-efficacy and Computer Anxiety in Social Work Students: Implications for Social Work Education.” Nordic Social Work Research 12 (3): 392–405. https://doi.org/10.1080/2156857X.2022.2041073.
  • Newton, P. 2016. “Academic Integrity: A Quantitative Study of Confidence and Understanding in Students at the Start of their Higher Education.” Assessment & Evaluation in Higher Education 41 (3): 482–497. https://doi.org/10.1080/02602938.2015.1024199
  • Newton, Philip, and Maira Xiromeriti. 2024. “ChatGPT Performance on Multiple Choice Question Examinations in Higher Education. A Pragmatic Scoping Review.” Assessment & Evaluation in Higher Education 1–18.
  • Nikolopoulou, Kleopatra, Vasilis Gialamas, and Konstantinos Lavidas. 2020. “Acceptance of Mobile Phone by University Students for their Studies: An Investigation Applying UTAUT2 Model.” Education and Information Technologies 25 (5): 4139–4155. https://doi.org/10.1007/s10639-020-10157-9
  • Noy, Shakked, and Whitney Zhang. 2023. “Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence.” Science 381 (6654): 187–192. https://doi.org/10.1126/science.adh2586
  • Perkins, Mike, and Jasper Roe. 2023. “Decoding Academic Integrity Policies: A Corpus Linguistics Investigation of AI and Other Technological Threats.” 1–20.
  • Pham, Thi Bich Thu, Lan Anh Dang, Thi Minh Hue Le, and Thi Hong Le. 2020. “Factors Affecting Teachers’ Behavioral Intention of Using Information Technology in Lecturing-Economic Universities.” Management Science Letters, 2665–2672. https://doi.org/10.5267/j.msl.2020.3.026.
  • Podsakoff, Philip M., Scott B. MacKenzie, and Nathan P. Podsakoff. 2012. “Sources of Method Bias in Social Science Research and Recommendations on How to Control it.” Annual Review of Psychology 63 (1): 539–569. https://doi.org/10.1146/annurev-psych-120710-100452
  • Rogers, Everett M. 2003. Diffusion of Innovations. 5th ed. New York, NY, USA: Free Press.
  • Sabherwal, R., University of Arkansas, and V. Grover. 2024. “The Societal Impacts of Generative Artificial Intelligence: A Balanced Perspective.” Journal of the Association for Information Systems 25 (1): 13–22. https://doi.org/10.17705/1jais.00860
  • Samsudeen, Sabraz Nawaz, and Rusith Mohamed. 2019. “University Students’ Intention to Use e-Learning Systems: A Study of Higher Educational Institutions in Sri Lanka.” Interactive Technology and Smart Education 16 (3): 219–238. https://doi.org/10.1108/ITSE-11-2018-0092
  • Schermelleh-Engel, Karin, Helfried Moosbrugger, and Hans Müller. 2003. “Evaluating the fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-fit Measures.” Methods of Psychological Research Online 8 (2): 23–74.
  • Shelton, Jev, and John P. Hill. 1969. “Effects on Cheating of Achievement Anxiety and Knowledge of Peer Performance.” Developmental Psychology 1:449–455. https://doi.org/10.1037/h0028010
  • Simonson, Michael R., Matthew Maurer, Mary Montag-Torardi, and Mary Whitaker. 1987. “Development of a Standardized Test of Computer Literacy and a Computer Anxiety Index.” Journal of Educational Computing Research 3 (2): 231–247. https://doi.org/10.2190/7CHY-5CM0-4D00-6JCG.
  • Stokel-Walker, C. 2022. “AI Bot ChatGPT Writes Smart Essays — Should Professors Worry?” Nature (December). https://doi.org/10.1038/d41586-022-04397-7.
  • Strzelecki, A. 2023. “To Use or Not to Use ChatGPT in Higher Education? A Study of Students’ Acceptance and Use of Technology.” Interactive Learning Environments 0 (0) Routledge: 1–14. https://doi.org/10.1080/10494820.2023.2209881
  • Strzelecki, A., and S. ElArabawy. 2024. “Investigation of the Moderation Effect of Gender and Study Level on the Acceptance and use of Generative AI by Higher Education Students: Comparative Evidence from Poland and Egypt.” British Journal of Education Technology, 1–22.
  • Šumak, Boštjan, and Andrej Šorgo. 2016. “The Acceptance and Use of Interactive Whiteboards among Teachers: Differences in UTAUT Determinants between Pre- and Post-adopters.” Computers in Human Behavior 64 (November): 602–620.
  • Ursachi, George, Ioana Alexandra Horodnic, and Adriana Zait. 2015. “How Reliable are Measurement Scales? External Factors with Indirect Influence on Reliability Estimators.” Procedia Economics and Finance 20:679–686. https://doi.org/10.1016/S2212-5671(15)00123-9
  • Venkatesh, Viswanath, Michael G. Morris, Gordon B. Davis, and Fred D. Davis. 2003. “User Acceptance of Information Technology: Toward a Unified View.” MIS Quarterly 27 (3): 425–478. https://doi.org/10.2307/30036540
  • Venkatesh, Viswanath, James Y. L. Thong, and Xin Xu. 2012. “Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology.” MIS Quarterly 36 (1): 157–78. https://doi.org/10.2307/41410412
  • Wu, Rong, and Zhonggen Yu. 2024. “Do AI Chatbots Improve Students Learning Outcomes? Evidence from a Meta-analysis.” British Journal of Educational Technology 55 (1): 10–33. https://doi.org/10.1111/bjet.13334
  • Zirar, A. 2023. “Exploring the Impact of Language Models, Such as ChatGPT, on Student Learning and Assessment.” Review of Education 11 (3): e3433. https://doi.org/10.1002/rev3.3433