Assessing the Acceptance and Behavioral Intentions Towards ChatGPT among Undergraduate Students
DOI:
https://doi.org/10.24191/jikm.v14i2.3668Keywords:
ChatGPT, UTAUT model, TAM model, artificial intelligence, information managementAbstract
The application of artificial intelligence (AI) in education will grow in the future as technology advances. By looking for a new research setting, the relationship between performance expectancy, effort expectancy, social in-fluence, facilitating conditions and behavioural intention towards ChatGPT of selected undergraduate students in Malaysia is the central theme for this study. This study was conducted throughout Malaysia with a total of 218 valid questionnaires were obtained from selected undergraduate student in Malaysia. Findings of the study show that relationship between performance expectancy, effort expectancy, social influence, facilitating conditions and behavioural intention towards ChatGPT are significant. This research can be extended by more investigations and analysis of the many variables, as well as exploring other potential areas of inquiry.
References
Abdulmunem, R. A. (2023). Artificial intelligence in education. Comparative Research on Diversity in Virtual Learning: Eastern vs. Western Perspectives, January, 241–255. https://doi.org/10.4018/978-1-6684-3595-3.ch012
Alafnan, M. A., & Dishari, S. (2023). ChatGPT as an Educational Tool: Opportunities, Challenges, and Recommendations for Communication, Business Writing, and Composition Courses. Journal of Artificial Intelligence and Technology, 3(2), 60–68. https://doi.org/10.37965/jait.2023.0184
Alazzam, M. B., & Basari, A. S. H. (2015). EHRS acceptance in Jordan hospitals by UTAUT2 model: Preliminary result. Journal of Theoretical and Applied Information Technology, 78(3), 473–482.
Ali, K. A. ., & Buang, M. (2016). Study on Factors that Influence Innovation in Malaysian Public Sector Akademia Baru. Journal of Advanced Research in Business and Management Studies, 4(1), 60–73.
Cahn, B. J. (2017). Chatbot : Architecture , Design & Development.
Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
Cohen, J. (1988). Statistical power analysis for the behavioral sciences.
Colace, F., & De Santo, M. (2018). Chatbot for e-learning: A case of study. International Journal of Mechanical Engineering and Robotics Research, 7(5), 528–533. https://doi.org/10.18178/ijmerr.7.5.528-533
Diamantopoulos, A., & Siguaw, J. A. (2006). Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration. British Journal of Management, 17(4), 263–282.
Dotimineli, A., & Mawardi, M. (2021). Development of STEM Integrated PBL-Based Student Worksheets in Energetic Ma-terials of First-Year Students. Journal of Physics: Conference Series, 1788(1), 1–12. https://doi.org/10.1088/1742-6596/1788/1/012045
Dwivedi, Y. K., Kshetri, N., Hughes, L., & Slade, E. L. (2023). Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71(March). https://doi.org/10.1016/j.ijinfomgt.2023.102642
Falk, R. E., & Miller, N. B. (1992). A primer for solf modelling.
Firat, M. (2023). How Chat GPT Can Transform Autodidactic Experiences and Open Education? Future of Education View project Visual Perception in Educational Design View project. April. https://doi.org/10.31219/osf.io/9ge8m
Foroughi, B., Senali, M. G., Iranmanesh, M., Khanfar, A., Ghobakhloo, M., Annamalai, N., & Naghmeh-Abbaspour, B. (2023). Determinants of Intention to Use ChatGPT for Educational Purposes: Findings from PLS-SEM and fsQCA. International Journal of Human-Computer Interaction, 0(0), 1–20. https://doi.org/10.1080/10447318.2023.2226495
García-peñalvo, F. J. (2023). The perception of Artificial Intelligence in educational contexts after the launch of. 24, 1–9.
Gefen, D., & Straub, D. (2005). A Practical Guide To Factorial Validity Using PLS-Graph: Tutorial And Annotated Example. Communications of the Association for Information Systems. https://doi.org/10.17705/1cais.01605
Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101–107. https://doi.org/10.1093/bi-omet/61.1.101
Goksel, N., & Bozkurt, A. (2023). Artificial Intelligence in Education: Current Insights and Future Perspectives. Handbook of Research on Learning in the Age of Transhumanism, January, 224–236. https://doi.org/10.4018/978-1-5225-8431-5.ch014
Gold, A. H., Malhotra, A., & Segars, A. H. (2015). Knowledge Management: An Organizational Capabilities Perspective. Journal of Management Information Systems, 18(1), 185–214.
Habibi, A., & Muhaimin, M. (2023). ChatGPT in higher education learning: Acceptance and use. Computers and Education: Artificial Intelligence, 5(July), 100190. https://doi.org/10.1016/j.caeai.2023.100190
Hamid, T., & Chhabra, M. (2022). A Review on Artificial Intelligence in Orthopaedics. Proceedings of the 2022 9th Interna-tional Conference on Computing for Sustainable Global Development, INDIACom 2022, 365–369. https://doi.org/10.23919/INDIACom54597.2022.9763178
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. https://doi.org/10.1007/s11747-014-0403-8
Huang, F., Teo, T., & Zhao, X. (2023). Examining factors influencing Chinese ethnic minority English teachers’ technology adoption: an extension of the UTAUT model. Computer Assisted Language Learning, 0(0), 1–23. https://doi.org/10.1080/09588221.2023.2239304
Jarrah, A. M., Wardat, Y., & Fidalgo, P. (2023). Using ChatGPT in academic writing is (not) a form of plagiarism: What does the literature say? Online Journal of Communication and Media Technologies, 13(4). https://doi.org/10.30935/ojcmt/13572
Jiao, W., Wang, W., Xing, J. H., Shi, S., & Tu, Z. (2022). Is ChatGPT A Good Translator? Yes With GPT-4 As The Engine.
Kasneci, E., Sessler, K., & Küchemann, S. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103(March). https://doi.org/10.1016/j.lindif.2023.102274
Kline, R. B. (2015). Principles and practice of structural equation modeling.
Koh, J. (2014). Sense of Virtual Community : A Conceptual Framework and Empirical Sense of Virtual Community : Concep-tual Framework and Empirical Validation. December 2003.
Kok, S.-L., & Siripipatthanakul, S. (2023). Artificial Intelligence (AI) Adoption: The Case of the Malaysian Financial Industry. Advance Knowledge for Executives (AKE), 2(4), 1–15. https://www.researchgate.net/publication/375922633
Lau. (2002). How is AI in Malaysia (2023)? https://thelead.io/artificial-intelligence/how-is-ai-in-malaysia-2023/
Nabiyev, V., Karal, H., Arslan, S., Erumit, L. A. K., & Cebi, A. (2013). An artificial intelligence-based distance education system: Artimat. Turkish Online Journal of Distance Education, 14(2), 81–98.
Pedro, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development Education Sector United Nations Educational, Scientific and Cultural Organization. Minis-terio De Educación, 1–46. https://en.unesco.org/themes/education-policy-
Rahi, S. (2017). Research Design and Methods: A Systematic Review of Research Paradigms, Sampling Issues and Instru-ments Development. International Journal of Economics & Management Sciences, 06(02). https://doi.org/10.4172/2162-6359.1000403
Rahman, A. M., Al Mamun, A., & Islam, A. (2018). Programming challenges of chatbot: Current and future prospective. 5th IEEE Region 10 Humanitarian Technology Conference 2017, R10-HTC 2017, 2018-Janua(March), 75–78. https://doi.org/10.1109/R10-HTC.2017.8288910
Ramayah, T., Cheah, J., Chuah, F., Ting, H., & Memon, M. A. (2018). Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 3.0: An Updated Guide and Practical Guide to Statistical Analysis.
Ranoliya, B. R., Raghuwanshi, N., & Singh, S. (2017). Chatbot for university related FAQs. 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017, 2017-Janua(January), 1525–1530. https://doi.org/10.1109/ICACCI.2017.8126057
Runhaar, H. (2016). Tools for integrating environmental objectives into policy and practice: What works where? Environmen-tal Impact Assessment Review, 59(2015), 1–9. https://doi.org/10.1016/j.eiar.2016.03.003
Sa’at, N. H., Mamat, I., & Nawang, W. M. Z. W. (2017). Pola perubahan sosiobudaya dan mobiliti sosial dalam kalangan komuniti muara di Pantai Timur. Akademika, 87(3), 165–178. http://eprints.unisza.edu.my/5463/
Samsurijan, M. S., & Ebekozien, A. (2023). Artificial intelligence in urban services in Malaysia: a review. PSU Research Review. https://doi.org/10.1108/PRR-07-2021-0034
Sekaran, U., & Bougie, R. (2020). Research Methods For Business A Skill Building Approach (Vol. 8th).
Shadbolt, N. (2022). Species of Artificial Intelligence. 151(2), 28–42.
Shen, K. N., Yu, A. Y., & Khalifa, M. (2010). Knowledge Contribution in Virtual Communities: Accounting for Multiple Dimensions of Social Presence through Social Identity. Behavior & Information Technology. 29, 337–348. https://doi.org/https://doi.org/10.1080/01449290903156622
Shi, X., Du, X., & Song, X. (2023). Research on Miniaturization Trend of ChatGPT Technology Model. Journal of Artificial Intelligence and Technology, 3(3), 95–99. https://doi.org/10.37965/jait.2023.0298
Soper Daniel. (2023). A-priori Sample Size Calculator for Structural Equation Models. In Https://Www.Danielsoper.Com/Stat-calc/Calculator.Aspx?Id=89. https://www.danielsoper.com/statcalc
Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, 36(2), 111–147.
Subramani, M., Jaleel, I., & Mohan, S. K. (2023). Evaluating the performance of ChatGPT in medical physiology university examination of phase I MBBS. Advances in Physiology Education, 47(2), 270–271. https://doi.org/10.1152/ADVAN.00036.2023
Taecharungroj, V. (2023). “What Can ChatGPT Do?” Analyzing Early Reactions to the Innovative AI Chatbot on Twitter. Big Data and Cognitive Computing, 7(1). https://doi.org/10.3390/bdcc7010035
Timms, M. J. (2016). Letting Artificial Intelligence in Education out of the Box: Educational Cobots and Smart Classrooms. International Journal of Artificial Intelligence in Education, 26(2), 701–712. https://doi.org/10.1007/s40593-016-0095-y
Toosi, A., Bottino, A. G., Saboury, B., Siegel, E., & Rahmim, A. (2021). A Brief History of AI: How to Prevent Another Winter (A Critical Review). PET Clinics, 16(4), 449–469. https://doi.org/10.1016/j.cpet.2021.07.001
Viswanath Venkatesh, Tracy Ann Sykes, Ruba Aljafari, M. S. P. (2021). The future is now: calling for a focus on temporal issues in information system research. 121. https://doi.org/https://doi.org/10.1108
Wang, P. (2021). Research on the Application of Artificial Intelligence in the Innovative Development of Visual Communi-cation Design Education. Journal of Physics: Conference Series, 1744(3). https://doi.org/10.1088/1742-6596/1744/3/032196
Wogu, I. A. P., Misra, S., Assibong, P. A., Olu-Owolabi, E. F., Maskeliūnas, R., & Damasevicius, R. (2019). Artificial intel-ligence, smart classrooms and online education in the 21st century: Implications for human development. Journal of Cases on Information Technology, 21(3), 66–79. https://doi.org/10.4018/JCIT.2019070105
Downloads
Published
How to Cite
Issue
Section
License
Copyright of articles that appear in the journal belongs exclusively to Faculty of Information Management, Universiti Teknologi MARA (Publisher). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions or any other reproductions of similar nature.
