A Study on the Faculty Perception Regarding the Use of Artificial Intelligence inCommerce Education
DOI:
https://doi.org/10.69996/ijari.2024007Keywords:
Artificial Intelligence, Commerce Education, Faculty PerceptionAbstract
This study explores faculty perceptions regarding the integration of Artificial Intelligence (AI)
in commerce education. The main goals of the research are to understand faculty attitudes
towards AI in commerce education, assess the current level of AI adoption in commerce
curriculums, and explore faculty perspectives on the impact of AI on student engagement and
analytical skills development. A cross-sectional survey design was employed, with 400
commerce faculty members participating. Convenience sampling was used to select
participants. The survey included closed-ended questions to gather quantitative data on faculty
perceptions of AI in commerce education. Significant differences in perceptions of AI,
adoption of AI tools, and impact on student performance were found across demographic
variables. Age and years of experience influenced faculty perceptions and behaviors regarding
AI integration in commerce education. Faculty perceptions of AI vary significantly across
demographic variables, highlighting the need for targeted approaches to promote AI adoption
and support faculty in utilizing AI tools effectively. These findings underscore the importance
of considering diverse perspectives in the implementation of AI in commerce education to
enhance teaching and learning outcomes.
References
[1] Venkatesh, Morris, Davis, & Davis, “User acceptance of information technology: Toward a unified view,” MIS Quarterly, 27(3), 2003, 425–478.
[2] W. M. H. K. Bandara and S. G. M. S. D. Senanayaka, "Use of Artificial Intelligence in Education: A Systematic Review," 2024 International Research Conference on Smart Computing and Systems Engineering (SCSE), Colombo, Sri Lanka, 2024, 1-5
[3] T. K. Chiu, Q. Xia, X. Zhou, C. S. Chai and M. Cheng, "Systematic literature review on opportunities challenges and future research recommendations of artificial intelligence in education", Comput. Educ. Artif. Intell., 4, 2023, 100118.
[4] B. Williamson and R. Eynon, "Historical threads missing links and future directions in AI in education", Learn. Media Technol., 45(3), 2020, 223-235.
[5] D. Weragama and J. Reye, "Analysing student programs in the PHP intelligent tutoring system," Int. J. Artif. Intell. Educ., 24, 2014, 162-188.
[6] I. M. Krishna, C. S. N. Avinash, R. Jaganadham, A. J. L. Durga, Y. Madhulika and K. Rakesh, "The Impact of Artificial Intelligence Effect on e-Commerce: A Framework for Key Research Areas," 2023 IEEE International Conference on ICT in Business Industry & Government (ICTBIG), Indore, India, 2023, 1-6.
[7] C. Wang, S.F. Ahmad, A.Y.B.A. Ayassrah, E.M. Awwad, M. Irshad, Y.A. Ali, et al., "An empirical evaluation of technology acceptance model for Artificial Intelligence in E-commerce", Heliyon, 9(8), 2023.
[8] A.A. Vărzaru and C.G. Bocean, "A two-stage SEM– artificial neural network analysis of mobile commerce and its drivers," Journal of Theoretical and Applied Electronic Commerce Research, 16(6), 2021, 2304- 2318.
[9] A. Güneyli, N.S. Burgul, S. Dericioğlu, N. Cenkova and H. Güneralp, “Exploring Teacher Awareness of Artificial Intelligence in Education: A Case Study from Northern Cyprus,” European Journal of Investigation in Health, Psychology and Education, 14(8), 2024, 2358- 2376.
[10]C. Surugiu, G. Catalin and S. Marius-Razvan, “Artificial Intelligence in Business Education: Benefits and Tools,” Amfiteatru Economic, 26(65), 2024, 241-258.
[11]Marc Sollosy and Marjorie McInerney, “Artificial intelligence and business education: What should be taught,” The International Journal of Management Education, 20(3), 2022, 100720
[12]R.E. Bawack, S.F. Wamba, K.D.A.Carillo and S. Akter, “Artificial intelligence in E-Commerce: a bibliometric study and literature review,” Electron Mark., 32(1), 2022, 297-338.
[13]Z. Zheng and B. Padmanabhan, “Selectively acquiring customer information: A new data acquisition problem and an active learning-based solution,” Management Science, 52(5), 2006, 697–712.
[14]X. Ye, L. Dong and D. Ma, “Loan evaluation in P2P lending based on Random Forest optimized by genetic algorithm with profit score,” Electronic Commerce Research and Applications, 32, 2018, 23–36.
[15]L.T. Khrais, “Role of Artificial Intelligence in Shaping Consumer Demand in E-Commerce,” Future Internet, 12(12), 2020, 226.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 International Journal of Advance Research and Innovation(IJARI, 2347-3258)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Fringe Global Scientific Press publishes all the papers under a Creative Commons Attribution-Non-Commercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/) license. Authors have the liberty to replicate and distribute their work. Authors have the ability to use either the whole or a portion of their piece in compilations or other publications that include their own work. Please see the licensing terms for more information on reusing the work.