Analisis Pengaplikasian Model Utaut pada Penggunaan Chatbot Kecerdasan Buatan dalam Mengukur Efikasi Diri & Capaian Akademik Mahasiswa Akuntansi
Keywords:
UTAUT, Chatbot, Application, Accounting StudentsAbstract
The aim to be achieved in this research is to analyze and explain the direct and indirect influence between the variables Performance Expectations, Effort Expectations, Social Influence, Supporting Conditions, Self-Efficacy and Academic Achievement. The population used was students of the Accounting Department of the Samarinda State Polytechnic, whose data was collected through sampling using purposive sampling techniques and data was obtained from 756 respondents. Data is processed through the PLS model using WarpPLS 8.0 software. The results of the research show that: the variables Performance Expectations, Business Expectations, Social Influence, Supporting Conditions have a positive and significant effect on the variables of self-efficacy, academic achievement, and academic variables through the self-efficacy variable. The conclusion of the 13 hypotheses proposed in this research is that there are 13 hypotheses that have a significant positive effect on self-efficacy and academic achievement.
References
Albayati, H. (2024). Investigating undergraduate students’ perceptions and awareness of using ChatGPT as a regular assistance tool: A user acceptance perspective study. Computers and Education: Artificial Intelligence, 6. https://doi.org/10.1016/j.caeai.2024.100203
Budhathoki, T., Zirar, A., Njoya, E. T., & Timsina, A. (2024). ChatGPT adoption and anxiety: a cross-country analysis utilising the unified theory of acceptance and use of technology (UTAUT). Studies in Higher Education, 1–16. https://doi.org/10.1080/03075079.2024.2333937
Cervantes, S. (2023). Creating Likert-scale visualizations: An approach using Stata and Tableau. 2023 Stata Conference, 15.
Chiu, T. K. F. (2024). Future research recommendations for transforming higher education with generative AI. Computers and Education: Artificial Intelligence, 6. https://doi.org/10.1016/j.caeai.2023.100197
Cooper, G. (2023). Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence. Journal of Science Education and Technology, 32(3), 444–452. https://doi.org/10.1007/s10956-023-10039-y
Crawford, J., Cowling, M., & Allen, K. A. (2023). Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial intelligence (AI). Journal of University Teaching and Learning Practice, 20(3). https://doi.org/10.53761/1.20.3.02
Doroudi, S. (2024). On the paradigms of learning analytics: Machine learning meets epistemology. Computers and Education: Artificial Intelligence, 6. https://doi.org/10.1016/j.caeai.2023.100192
Einarsson, H., Lund, S. H., & Jónsdóttir, A. H. (2024). Application of ChatGPT for automated problem reframing across academic domains. Computers and Education: Artificial Intelligence, 6. https://doi.org/10.1016/j.caeai.2023.100194
Essel, H. B., Vlachopoulos, D., Essuman, A. B., & Amankwa, J. O. (2024). ChatGPT effects on cognitive skills of undergraduate students: Receiving instant responses from AI-based conversational large language models (LLMs). Computers and Education: Artificial Intelligence, 6. https://doi.org/10.1016/j.caeai.2023.100198
Gao, R., Merzdorf, H. E., Anwar, S., Hipwell, M. C., & Srinivasa, A. R. (2024). Automatic assessment of text-based responses in post-secondary education: A systematic review. In Computers and Education: Artificial Intelligence (Vol. 6). Elsevier B.V. https://doi.org/10.1016/j.caeai.2024.100206
Grabińska, B., Andrzejewski, M., & Grabiński, K. (2021). The students’ and graduates’ perception of the potential usefulness of Artificial Intelligence (AI) in the academic curricula of Finance and Accounting Courses. E-Mentor, 92(5), 16–25. https://doi.org/10.15219/em92.1544
Kelly, S., Kaye, S. A., & Oviedo-Trespalacios, O. (2023a). What factors contribute to the acceptance of artificial intelligence? A systematic review. Telematics and Informatics, 77. https://doi.org/10.1016/j.tele.2022.101925
Kuligowski, J., Pérez-Rubio, Á., Moreno-Torres, M., Soluyanova, P., Pérez-Rojas, J., Rienda, I., Pérez-Guaita, D., Pareja, E., Trullenque-Juan, R., & Castell, J. V. (2024a). Cluster-Partial Least Squares (c-PLS) regression analysis: Application to miRNA and metabolomic data. Analytica Chimica Acta, 1286, 342052.
Liana, L. (2009). Penggunaan MRA dengan SPSS untuk menguji pengaruh variabel moderating terhadap hubungan antara variabel independen dan variabel dependen. Dinamik, 14(2).
Lim, Z. W., Pushpanathan, K., Yew, S. M. E., Lai, Y., Sun, C. H., Lam, J. S. H., Chen, D. Z., Goh, J. H. L., Tan, M. C. J., Sheng, B., Cheng, C. Y., Koh, V. T. C., & Tham, Y. C. (2023). Benchmarking large language models’ performances for myopia care: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and Google Bard. EBioMedicine, 95. https://doi.org/10.1016/j.ebiom.2023.104770
Lo, C. K. (2023a). What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature. In Education Sciences (Vol. 13, Issue 4). MDPI. https://doi.org/10.3390/educsci13040410
Moindjié, I.-A., Dabo-Niang, S., & Preda, C. (2024). Classification of multivariate functional data on different domains with Partial Least Squares approaches. Statistics and Computing, 34(1), 5.
Musyaffi, A. M., Baxtishodovich, B. S., Afriadi, B., Hafeez, M., Adha, M. A., & Wibowo, S. N. (2024a). New Challenges of Learning Accounting With Artificial Intelligence: The Role of Innovation and Trust in Technology. European Journal of Educational Research, 13(1), 183–195. https://doi.org/10.12973/eu-jer.13.1.183
Stokel-Walker, C. (2022a). AI bot ChatGPT writes smart essays-should academics worry? Nature.
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. https://doi.org/10.1080/10494820.2023.2209881
Suhartanto, D., Brien, A., Primiana, I., Wibisono, N., & Triyuni, N. N. (2020). Tourist loyalty in creative tourism: the role of experience quality, value, satisfaction, and motivation. Current Issues in Tourism, 23(7), 867–879.
Sullivan, M., Kelly, A., & McLaughlan, P. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning and Teaching, 6(1), 31–40. https://doi.org/10.37074/jalt.2023.6.1.17
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023a). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10(1). https://doi.org/10.1186/s40561-023-00237-x
Van Dis, E. A. M., Bollen, J., Van Rooij, R., Zuidema, W., & Bockting, C. L. (2023). ChatGPT: five priorities for research.
Wood, D. A., Achhpilia, M. P., Adams, M. T., Aghazadeh, S., Akinyele, K., Akpan, M., Allee, K. D., Allen, A. M., Almer, E. D., & Ames, D. (2023). The ChatGPT artificial intelligence chatbot: How well does it answer accounting assessment questions? Issues in Accounting Education, 38(4), 81–108.
Yussaivi, A., Suhartanto, D., & Syarief, M. E. (2020). An Analysis of the Determining Factors of Mobile Banking Adoption in Islamic Banks. IOP Conference Series: Materials Science and Engineering, 879(1), 012174.
Zalukhu, H., Prastiyanto, K. W. D., Ramadhan, I., & Ramadhan, N. R. (2024). Penggunaan Machine Learning dalam Startup dengan Pemanfaatan Smart Pls. Jurnal MENTARI: Manajemen, Pendidikan Dan Teknologi Informasi, 2(2), 111–122.
Ziemba, Maruszewska E, & Grabara D. (2023). Acceptance of ChatGPT among Accounting and Finance Higher Education Students. https://ssrn.com/abstract=4650693
Downloads
Published
How to Cite
Conference Proceedings Volume
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
