JCERJournal of Contemporary Educational Research2208-84662208-8474Bio-Byword Scientific Publishing Pty. Ltd.10.26689/jcer.v8i2.6081ArticleArtificial Intelligence-Enhanced Learning: A New Paradigm in the “Business Data Analysis and Application” Coursehttps://artdesignp.com/journal/JCER/8/2/10.26689/jcer.v8i2.6081WuSuhan2024822024-02-25This paper explores the transformative impact of generative artificial intelligence (AI) on the “Business Data Analysis and Application” course in the post-2023 era, marking a significant paradigm shift in educational methodologies. It investigates how generative AI reshapes teaching and learning dynamics, enhancing the processing of complex data sets and nurturing critical thinking skills. The study highlights the role of AI in fostering dynamic, personalized, and adaptive learning experiences, addressing the evolving pedagogical needs of the business sector. Key challenges, including equitable access, academic integrity, and ethical considerations such as data privacy and algorithmic bias, are thoroughly examined. The research reveals that the integration of generative AI aligns with current professional demands, equipping students with cutting-edge AI tools, and tailoring learning to individual needs through real-time feedback mechanisms. The study concludes that the incorporation of generative AI into this course signifies a substantial evolution in educational approaches, offering profound implications for student learning and professional development.

Lim WM, Gunasekara A, Pallant JL, et al., 2023, Generative AI and the Future of Education: Ragnarök or Reformation? A Paradoxical Perspective from Management Educators. The International Journal of Management Education, 21(2): 100790.

Nah FFH, Zheng R, Cai J, et al., 2023, Generative AI and ChatGPT: Applications, Challenges, and AI-Human Collaboration. Journal of Information Technology Case and Application Research, 2023(3): 277–304.

García-Peñalvo FJ, Vázquez-Ingelmo A, 2023, What Do We Mean by GenAI? A Systematic Mapping of the Evolution, Trends, and Techniques Involved in Generative AI. International Journal of Interactive Multimedia and Artificial Intelligence, 2023: 1–10.

Michel-Villarreal R, Vilalta-Perdomo E, Salinas-Navarro DE, et al., 2023, Challenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT. Education Sciences, 13(9): 856.

Salah M, Al Halbusi H, Abdelfattah F, 2023, May the Force of Text Data Analysis Be with You: Unleashing the Power of Generative AI for Social Psychology Research. Computers in Human Behavior: Artificial Humans, 1(2): 100006.

Chiu TK, 2023, The Impact of Generative AI (GenAI) on Practices, Policies and Research Direction in Education: A Case of ChatGPT and Midjourney. Interactive Learning Environments, 2023: 1–17.

Chen L, Chen P, Lin Z, 2020, Artificial Intelligence in Education: A Review. IEEE Access, 2020(8): 75264–75278.

Paek S, Kim N, 2021, Analysis of Worldwide Research Trends on the Impact of Artificial Intelligence in Education. Sustainability, 13(14): 7941.

Quy VK, Thanh BT, Chehri A, et al., 2023, AI and Digital Transformation in Higher Education: Vision and Approach of a Specific University in Vietnam. Sustainability, 15(14): 11093.

Nedelkoski S, Bogatinovski J, Mandapati AK, et al., 2020, Multi-Source Distributed System Data for AI-Powered Analytics. Service-Oriented and Cloud Computing: 8th IFIP WG 2.14 European Conference, ESOCC 2020, September 28–30, 2020, Proceedings 8. Heraklion, Crete, Greece, 161–176.

Rodriguez CO, 2012, MOOCs and the AI-Stanford Like Courses: Two Successful and Distinct Course Formats for Massive Open Online Courses. European Journal of Open, Distance and E-Learning, 2012(15).

Schleiss J, Laupichler MC, Raupach T, et al., 2023, AI Course Design Planning Framework: Developing Domain- Specific AI Education Courses. Education Sciences, 13(9): 954.

Dogan ME, Goru Dogan T, Bozkurt A, 2023, The Use of Artificial Intelligence (AI) in Online Learning and Distance Education Processes: A Systematic Review of Empirical Studies. Applied Sciences, 13(5): 3056.

Ouyang F, Zheng L, Jiao P, 2022, Artificial Intelligence in Online Higher Education: A Systematic Review of Empirical Research from 2011 to 2020. Education and Information Technologies, 27(6): 7893–7925.

Leddo J, Garg K, 2021, Comparing the Effectiveness of AI-Powered Educational Software to Human Teachers. International Journal of Social Science and Economic Research, 6(3): 953–963.

Zheng L, Niu J, Zhong L, et al., 2023, The Effectiveness of Artificial Intelligence on Learning Achievement and Learning Perception: A Meta-Analysis. Interactive Learning Environments, 31(9): 5650–5664.

Maranguni? N, Grani? A, 2015, Technology Acceptance Model: A Literature Review from 1986 to 2013. Universal Access in the Information Society, 2015(14): 81–95.

Chocarro R, Cortiñas M, Marcos-Matás G, 2023, Teachers’ Attitudes Towards Chatbots in Education: A Technology Acceptance Model Approach Considering the Effect of Social Language, Bot Proactiveness, and Users’ Characteristics. Educational Studies, 49(2): 295–313.

Li K, 2023, Determinants of College Students’ Actual Use of AI-Based Systems: An Extension of the Technology Acceptance Model. Sustainability, 15(6): 5221.

Yi S, 2023, Effects of the Artificial Intelligence Convergence General Education Course Using No-Code Data Analysis Tools on College Students’ Data Literacy. EdMedia + Innovate Learning, Vienna, Austria, 1099–1104.

Zheng Y, 2019, A Course on Applied AI and Data Science: Recommender Systems. Proceedings of the 20th Annual SIG Conference on Information Technology Education, 43–48.

Ahmad K, Iqbal W, El-Hassan A, et al., 2023, Data-Driven Artificial Intelligence in Education: A Comprehensive Review. IEEE Transactions on Learning Technologies, 2023(17): 12–31.

Fitria TN, 2021, Artificial Intelligence (AI) In Education: Using AI Tools for Teaching and Learning Process. Prosiding Seminar Nasional & Call for Paper STIE AAS, 4(1): 134–147.