ARTIFICIAL INTELLIGENCE AND STRESS REDUCTION AMONG ACCOUNTING EDUCATION STUDENTS IN TERTIARY INSTITUTIONS IN AKWA IBOM STATE
Abstract
The study examined Artificial Intelligence and Stress Reduction among Accounting Education students in Tertiary Institutions in Akwa Ibom State. It adopted a survey research design to investigate the magnitude of Stress Reduction (SR) and Artificial Intelligence (AI), and Academic performance (AP) and Artificial intelligence (AI) among accounting education students in tertiary institutions. A structured questionnaire in English was designed by the researchers and used as a relevant instrument for primary data collection using a 4-point ranking scale of Strongly Agree (SA) 4; Agree (A) 3; Disagree (D) 2; Strongly Disagree (SD) 1. A two-stage cluster sampling was used, where a simple random sample of clusters is selected and then a simple random sample is selected from the units in each sampled cluster. The sampling technique used in the first stage of the sampling was a Taro Yamane formula, which was used to determine the reliable sample size from population size of 700. Two hundred and fifty-five (255) Questionnaires were distributed and Two hundred and forty-one (241) were retrieved, a 95% retrieval. The model specification used for these analyses was Regression and Correlation. The mechanism used for this research was trustworthy, the researchers through their expertise ensured that the instrument measured what it was actually constructed to measure in the course of the study. Every item in the instrument was critically securitized and screened. Two hypotheses were tested: there is no significant effect of Artificial Intelligence on Stress Reduction among Accounting Education students of Tertiary Institutions in Akwa Ibom State; and there is no significant effect of Artificial Intelligence on Academic Performance among Accounting Education students in Tertiary Institutions in Akwa Ibom State. From the findings of the analyses, it is concluded that Artificial Intelligence (AI) has a positive effect on Stress Reduction (SR) and Academic Performance (AP).References
Akgun, S., and Greenhow, C. (2021). Artificial Intelligence in Education: Addressing Ethical Challenges in K-12 Settings. AI and Ethics, 1-10.
Alam, A. (2021). Possibilities and Apprehensions in the Landscape of Artificial Intelligence in Education. In 2021 International Conference on Computational Intelligence and Computing Applications (ICCICA), 1-8. IEEE.
Asha, N. E. J., Islam, E. U., and Khan, R., (2021) “Low-Cost Heart Rate Sensor and Mental Stress Detection Using Machine Learning”, International Journal of Innovative Technology and Exploring Engineering, 10(8) 574-577.
Asuquo, E. E. and Ukoima, E. F. (2016). Adequacy of office technology facility for skill development of business education students in University, South–South, Nigeria. Journal of Research and Development in Education, 6 (1): 112 – 121.
Chen, L., Chen, P., and Lin, Z. (2020). Artificial Intelligence in Education: A Review. Ieee Access, 8, 75264-75278.
Chen, X., Zou, D., Xie, H., Cheng, G., and Liu, C. (2022). Two Decades of Artificial Intelligence in Education: Contributors, Collaborations, Research Topics, Challenges, and Future Directions. Educational Technology and Society, 25(1), 28-47.
Cheng, X., Su, L., Luo, X., Benitez, J., and Cai, S. (2022). The Good, the Bad, and the Ugly: Impact of Analytics and Artificial Intelligence-Enabled Personal Information Collection on Privacy and Participation in Ridesharing. European Journal of Information Systems, 31(3), 339-363.
Dong, Y., Hou, J., Zhang, N., and Zhang, M. (2020). Research on How Human Intelligence, Consciousness, and Cognitive Computing Affect the Development of Artificial Intelligence. Complexity, 2020, 1680845, 1-10.
Gupta, S. K., Ashwin, T. S., and Guddeti, R. M. R. (2019). Students’ affective content analysis in smart classroom environment using deep learning techniques. Multimedia Tools and Applications, 78(18), 25321–25348. https://doi.org/10.1007/s11042-019-7651-z
Hashim, H. (2018). Application of Technology in the Digital Era Education. International Journal of Research in Counseling and Education, 2(1), 1-5.
Hwang, G. J. (2014). Definition, Framework and Research Issues of Smart Learning Environments - A Context-Aware Ubiquitous Learning Perspective. Smart Learning Environments, 1(1), No.4, pp. 1-14.
Hwang, G. J., Xie, H., Wah, B. W., and Gašević, D. (2020). Vision, Challenges, Roles and Research Issues of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 100001.
Li, J., Cheng, H., Guo, H., and Qiu, S. (2018). Survey on Artificial Intelligence for Vehicles. Automotive Innovation, 1(1), 2-14.
Limna, P. (2022). Artificial Intelligence (AI) in the Hospitality Industry: A Review Article. International Journal of Computing Sciences Research, 6.
Limna, P., Siripipatthanakul, S., and Phayaphrom, B. (2021). The Role of Big Data Analytics in Influencing Artificial Intelligence (AI) Adoption for Coffee Shops in Krabi, Thailand. International Journal of Behavioral Analytics, 1(2), 1-17.
Makridakis, S. (2017). The Forthcoming Artificial Intelligence (AI) Revolution: It’s Impact on Society and Firms. Futures, 90, 46-60.
Mitchell, M. (2019). Artificial Intelligence: A Guide for Thinking Humans. Penguin UK.
Owoc, M. L., Sawicka, A., and Weichbroth, P. (2019). Artificial Intelligence Technologies in Education: Benefits, Challenges and Strategies of Implementation. IFIP International Workshop on Artificial Intelligence for Knowledge Management, 37-58.
Pandiaraj M., Siva A. M., Sindhu M. M., Shekhar H., Ajeet K., Ravikumar S. and S. P. Thipperudra swamy, (2022) “Artificial Intelligence (AI) and Internet of Medical Things (IoMT) Assisted Biomedical Systems for Intelligent Healthcare”, National Library of Medicenr, Biosensors (Basel),12(8): 562.
Pranjal K., Siddhartha C. and Lalit K. A., (2023) “Artificial Intelligence in Healthcare: Review, Ethics, Trust Challenges and Future Research Directions”, ACM Digital Library, doi.org/10.1016/j.engappai.2023.105894, vol. 120, Issue C.
Rahmatullah, A. S., Mulyasa, E., Syahrani, S., Pongpalilu, F., and Putri, R. E. (2022). Digital Era 4.0: The Contribution to Education and Student Psychology. Linguistics and Culture Review, 6, 89-107.
Roll, I., and Wylie, R. (2016). Evolution and Revolution in Artificial Intelligence in Education. International Journal of Artificial Intelligence in Education, 26(2), 582.
Shabbir, J., and Anwer, T. (2018). Artificial Intelligence and Its Role in Near Future. arXiv preprint arXiv:1804.01396.
World Health Organization weekly epidemiological update on COVID-19 (2021), edition 46, URL:https://www.who.int/publications/m/item/weekly-epidemiological-update-on-covid-19-29-june-2021.
Yufeia, L., Salehb, S., Jiahuic, H., and Syed, S. M. (2020). Review of the Application of Artificial Intelligence in Education. Integration (Amsterdam), 12(8), 1-15.
Yasin H., Koorosh M., Bahram T., Khalil A., Mohammad G., (2022). “Stress Detection Using PPG Signal and Combined Deep CNN-MLP Network”, Stress Detection Using PPG Signal and Combined Deep CNN-MLP Network. IEEE Transactions on Biomedical Engineering, 70(2), 589-599.
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