Understanding the Scope and Problems of Artificial Intelligence and Assisted Learning in Higher Education
DOI:
https://doi.org/10.5281/zenodo.13637234Keywords:
ai, ai in education, assisted learningAbstract
Learning is a dynamic experience. We need to create learning experiences that assist all kinds of learners. Human beings have different patterns of learning. Assisted learning helps in decentralizing the learning experience in a more individualistic approach. Artificial Intelligence has helped in automating many tasks of administrative nature, evaluation and has even helped personalize learning, countering the problems of teacher exhaustion. Not just efficient grading use of AI through educational chatbots and applications can help in helping students get a 24/7 mentoring option which in a real-world scenario might be difficult for human teachers to cater to. With technology has come ease of global accessibility and insights that are backed by data. But it also brings along with it an enhanced scenario of digital divide, technological hurdle and inequality. The paper through case studies tries to analyze the scopes and problems of using Artificial Intelligence in Assisted Learning in Higher Education.
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References
key policy ideas to integrate AI in education effectively. (2024, July 16). World Economic Forum. Available at: https://www.weforum.org/agenda/2024/04/prepare-future-policy-ideas-ai-in-education/.
AI & emerging technologies group | Ministry of electronics and information technology, Government of India. (n.d.). https://www.meity.gov.in/emerging-technologies-division#:~:text=The%20Government%20of%20India%20launched,India%27s%20AI%20startups%20and%20researchers.
Aithal, P.S., & Aithal, S. (2020). Implementation strategies of higher education part of national education policy 2020 of India towards achieving its objectives. International Journal of Management, Technology, and Social Sciences (IJMTS), 5(2), 283-325.
Alam, A., & Mohanty, A. (2022). Business models, business strategies, and innovations in EdTech companies: Integration of learning analytics and artificial intelligence in higher education. in IEEE 6th Conference on Information and Communication Technology (CICT), pp. 1-6. IEEE.
Bhatnagar, A.K., Khanna, U., & Rana, A. (2021). Digital learning ecosystem at Indian higher education system. The Journal of Contemporary Issues in Business and Government, 27(2), 4360-4375.
Bigscal. (2023). https://www.bigscal.com/wp-content/uploads/2024/03/Top-Benefits-of-Artificial-Intelligence-In-Education-Sector_1.webp.
Chaka, C. (2023). Fourth industrial revolution—A review of applications, prospects, and challenges for artificial intelligence, robotics and blockchain in higher education. Research and Practice in Technology Enhanced Learning, 18, 002-002.
Cloudfront. (2023). https://d3lkc3n5th01x7.cloudfront.net/wp-content/uploads/2023/04/24222707/ai-in-education-2-1.png.
Commonsense. (2023). https://www.commonsense.org/sites/default/files/png/2018-08/game-review-dreambox-learning-math.png.
Dhawan, S., & Batra, G., 2020. Artificial intelligence in higher education: Promises, perils, and perspective. Expanding Knowledge Horizon. OJAS, 11, 11-22.
Dwivedi, V.J., & Joshi, Y.C. (2020). Leadership pivotal to productivity enhancement for 21st-century Indian higher education system. International Journal of Higher Education, 9(2), 126-143.
Ghnemat, R., Shaout, A., & Abrar, M. (2022). Higher education transformation for artificial intelligence revolution: Transformation framework. Int. J. Emerg. Technol. Learn., 17(19), 224-241.
Hamilton, I. (2024, June 6). Artificial intelligence in Education: Teachers’ opinions on AI in the classroom. Forbes Advisor. Available at: https://www.forbes.com/advisor/education/it-and-tech/artificial-intelligence-in-school/.
Holloway, J., & Lewis, S. (2022). Governing teachers through datafication: Physical–virtual hybridity and language interoperability in teacher accountability. Big Data & Society, 9(2), 20539517221137553.
Jindal, A., & Bansal, M. (2020). Knowledge and education about artificial intelligence among medical students from teaching institutions of India: a brief survey. Med Ed Publish, 9, 200.
Kashive, N., Powale, L., & Kashive, K. (2020). Understanding user perception toward artificial intelligence (AI) enabled e-learning. The International Journal of Information and Learning Technology, 38(1), 1-19.
Key components of developing AI literacy at your institution. (2024, January 16). www.elsevier.com. https://www.elsevier.com/connect/key-components-of-developing-ai-literacy-at-your-institution.
Longnecker, J. (2021). Teacher practices with adaptive math technology: Sitting in the driver’s seat of a self-driving car.
Morgan, B., Hogan, M., Hampton, A.J., Lippert, A., & Graesser, A.C. (2020). The need for personalized learning and the potential of intelligent tutoring systems. in Handbook of Learning from Multiple Representations and Perspectives, pp. 495-512. Routledge.
Mousavinasab, E., Zarifsanaiey, N., R. Niakan Kalhori, S., Rakhshan, M., Keikha, L., & Ghazi Saeedi, M. (2021). Intelligent tutoring systems: A systematic review of characteristics, applications, and evaluation methods. Interactive Learning Environments, 29(1), 142-163.
Nagaraj, B.K., Kalaivani, A., Begum, S., Akila, S., & Sachdev, H.K. (2023). The emerging role of artificial intelligence in stem higher education: A critical review. International Research Journal of Multidisciplinary Technovation, 5(5), 1-19.
Nextplatform. (2023). https://www.nextplatform.com/wp-content/uploads/2019/02/ibm-watson-history.jpg.
Paek, S., & Kim, N. (2021). Analysis of worldwide research trends on the impact of artificial intelligence in education. Sustainability, 13(14), 7941.
Panditrao, M.M., & Panditrao, M.M. (2020). National education policy 2020: What is in it for a student, a parent, a teacher, or us, as a Higher Education Institution/University?. Adesh University Journal of Medical Sciences & Research, 2(2), 70-79.
Rahman, A. (2022). Mapping the efficacy of artificial intelligence-based online proctored examination (OPE) in higher education during COVID-19: Evidence from Assam, India. International Journal of Learning, Teaching and Educational Research, 21(9), 76-94.
Rajeshwari, M., & Krishna Prasad, K. (2020). IBM watson industry cognitive education methods. International Journal of Case Studies in Business, IT, and Education (IJCSBE), 4(1), 38-50.
Roy, R., Babakerkhell, M.D., Mukherjee, S., Pal, D., & Funilkul, S. (2022). Evaluating the intention for the adoption of artificial intelligence-based robots in the university to educate the students. IEEE Access, 10, 125666-125678.
Saravanakumar, A.R., & Padmini Devi, K.R. (2020). Indian higher education: Issues and opportunities. Journal of Critical Reviews, 7(2), 542-545.
Sethi, K., Chauhan, S., & Jaiswal, V. (2021). Artificial Intelligence in higher education: First attempt. in Impact of AI Technologies on Teaching, Learning, and Research in Higher Education, pp. 1-29. IGI Global.
Su, J., Zhong, Y., & Ng, D.T.K. (2022). A meta-review of literature on educational approaches for teaching AI at the K-12 levels in the Asia-Pacific region. Computers and Education: Artificial Intelligence, 3, 100065.
Tyagi, A.K., Aswathy, S.U., & Abraham, A. (2020). Integrating blockchain technology and artificial intelligence: Synergies perspectives challenges and research directions. Journal of Information Assurance and Security, 15(5), 1554.
Wang, T., Lund, B.D., Marengo, A., Pagano, A., Mannuru, N.R., Teel, Z.A., & Pange, J. (2023). Exploring the potential impact of artificial intelligence (AI) on international students in higher education: Generative AI, chatbots, analytics, and international student success. Applied Sciences, 13(11), 6716.
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Copyright (c) 2024 Dr. Amartya Saha
This work is licensed under a Creative Commons Attribution 4.0 International License.
