Harnessing the Power of Artificial Intelligence for Adaptive Learning Systems: A Systematic Review

Автор: Muhammad Jawad Mustfa, Sidra Ashiq

Журнал: International Journal of Education and Management Engineering @ijeme

Статья в выпуске: 5 vol.14, 2024 года.

Бесплатный доступ

This research paper delves into the transformative potential of Adaptive Learning Systems (ALS) in revolutionizing education through the integration of Artificial Intelligence (AI). With traditional educational approaches often failing to accommodate individual learning needs, the answer to this problem is adaptive learning system which focuses on personalized content delivery, instructional methods, and assessments. Through case studies spanning various educational contexts, including various countries, higher education, and diverse cultures, we have evaluated the effectiveness of different ALS techniques in terms of different educational needs and requirements. By reviewing these techniques in terms of their features, capabilities and functionalities, we have tried to figure out, how does the use of AI in adaptive learning systems contribute to personalized learning experiences for students. The paper also highlights the key challenges and limitations associated with the integration of AI in ALS. It addresses issues like data protection, analyzes the ALS principles and investigates the ethical consideration which arises during implementation of AI in adaptive learning systems. Furthermore, it underscores the pivotal role educators’ play in collaborating with AI systems to create a balanced learning environment. By providing insights into future directions, such as advancements in personalization techniques and lifelong learning, this paper contributes to understanding the complex interplay between AI and personalized education. Ultimately, the research advocates for the widespread integration of ALS as a transformative approach that has the potential to redefine education and cater to the diverse needs of learners in the digital age.

Еще

Adaptive Learning Systems, Personalized Education, Artificial Intelligence, Knowledge Measurement, Learning Process

Короткий адрес: https://sciup.org/15019482

IDR: 15019482   |   DOI: 10.5815/ijeme.2024.05.02

Список литературы Harnessing the Power of Artificial Intelligence for Adaptive Learning Systems: A Systematic Review

  • Bostrom, N. and Yudkowsky, E., 2018. The ethics of artificial intelligence. In Artificial intelligence safety and security (pp. 57-69). Chapman and Hall/CRC.
  • Nilsson, N.J., 1998. Artificial intelligence: a new synthesis. Morgan Kaufmann.
  • Chen, L., Chen, P. and Lin, Z., 2020. Artificial intelligence in education: A review. Ieee Access, 8, pp.75264-75278.
  • Skinner, B.F., 1958. Teaching Machines: From the experimental study of learning come devices which arrange optimal conditions for self-instruction. Science, 128(3330), pp.969-977.
  • Hussain, M.I., Shamim, M., Ravi Sankar, A.V., Kumar, M., Samanta, K. and Sakhare, D.T., 2022. The Effect Of The Artificial Intelligence On Learning Quality & Practices In Higher Education. Journal of Positive School Psychology, pp.1002-1009.
  • El Miedany, Y. and El Miedany, Y., 2019. Flipped learning. Rheumatology Teaching: The Art and Science of Medical Education, pp.285-303.
  • Weber-Lewerenz, B., 2021. Corporate digital responsibility (CDR) in construction engineering—ethical guidelines for the application of digital transformation and artificial intelligence (AI) in user practice. SN Applied Sciences, 3, pp.1-25.
  • Kinshuk, Chen, N.S., Cheng, I.L. and Chew, S.W., 2016. Evolution is not enough: Revolutionizing current learning environments to smart learning environments. International Journal of Artificial Intelligence in Education, 26, pp.561-581.
  • Collins, A. and Halverson, R., 2018. Rethinking education in the age of technology: The digital revolution and schooling in America. Teachers College Press.
  • Yarbrough, J.R., 2018. Adapting Adult Learning Theory to Support Innovative, Advanced, Online Learning-WVMD Model. Research in Higher Education Journal, 35.
  • Abbas, N., Ali, I., Manzoor, R., Hussain, T. and Hussaini, M.H.A., 2023. Role of Artificial Intelligence Tools in Enhancing Students' Educational Performance at Higher Levels. Journal of Artificial Intelligence, Machine Learning and Neural Network (JAIMLNN) ISSN: 2799-1172, 3(05), pp.36-49.
  • Miseliunaite, B., Kliziene, I. and Cibulskas, G., 2022. Can holistic education solve the world’s problems: A systematic literature review. Sustainability, 14(15), p.9737.
  • Alamri, H.A., Watson, S. and Watson, W., 2021. Learning technology models that support personalization within blended learning environments in higher education. TechTrends, 65, pp.62-78.
  • Fung, C.Y., Su, S.I., Perry, E.J. and Garcia, M.B., 2022. Development of a socioeconomic inclusive assessment framework for online learning in higher education. In Socioeconomic inclusion during an era of online education (pp. 23-46). IGI Global.
  • Hassan, J., Devi, A. and Ray, B., 2022. Virtual Laboratories in tertiary education: Case study analysis by learning theories. Education Sciences, 12(8), p.554.
  • Soslau, E., Gallo-Fox, J. and Scantlebury, K., 2019. The promises and realities of implementing a coteaching model of student teaching. Journal of Teacher Education, 70(3), pp.265-279.
  • El-Sabagh, H.A., 2021. Adaptive e-learning environment based on learning styles and its impact on development students' engagement. International Journal of Educational Technology in Higher Education, 18(1), pp.1-24.
  • Asigigan, S.İ. and Samur, Y., 2021. The Effect of Gamified STEM Practices on Students' Intrinsic Motivation, Critical Thinking Disposition Levels, and Perception of Problem-Solving Skills. International Journal of Education in Mathematics, Science and Technology, 9(2), pp.332-352.
  • Pendy, B., 2023. From Traditional to Tech-Infused: The Evolution of Education. BULLET: Jurnal Multidisiplin Ilmu, 2(3), pp.767-777.
  • Vadivel, B., Namaziandost, E. and Saeedian, A., 2021, November. Progress in English language teaching through continuous professional development—teachers’ self-awareness, perception, and feedback. In Frontiers in Education (Vol. 6, p. 757285). Frontiers.
  • Gregg, A., Yu, J., Resig, J., Johnson, L., Park, E. and Stuczynski, P., 2021. Promising educational technology meets complex system: A 6-year case study of an adaptive learning project from initial exploration through the end of a pilot. Journal of Formative Design in Learning, 5, pp.62-77.
  • Dorfman, J., 2022. Theory and practice of technology-based music instruction. Oxford University Press.
  • McCalla, G., 2023. 2. The history of artificial intelligence in education–the first quarter century. Handbook of Artificial Intelligence in Education, p.10.
  • Gardner, J., O'Leary, M. and Yuan, L., 2021. Artificial intelligence in educational assessment:‘Breakthrough? Or buncombe and ballyhoo?’. Journal of Computer Assisted Learning, 37(5), pp.1207-1216.
  • Maghsudi, S., Lan, A., Xu, J. and van Der Schaar, M., 2021. Personalized education in the artificial intelligence era: what to expect next. IEEE Signal Processing Magazine, 38(3), pp.37-50.
  • Kabudi, T., 2023. Towards Designing AI-Enabled Adaptive Learning Systems.
  • Munshi, A., Biswas, G., Baker, R., Ocumpaugh, J., Hutt, S. and Paquette, L., 2023. Analysing adaptive scaffolds that help students develop self‐regulated learning behaviours. Journal of Computer Assisted Learning, 39(2), pp.351-368.
  • Javed, A.R., Saadia, A., Mughal, H., Gadekallu, T.R., Rizwan, M., Maddikunta, P.K.R., Mahmud, M., Liyanage, M. and Hussain, A., 2023. Artificial Intelligence for Cognitive Health Assessment: State-of-the-Art, Open Challenges and Future Directions. Cognitive Computation, pp.1-46.
  • Mhlongo, S., Mbatha, K., Ramatsetse, B. and Dlamini, R., 2023. Challenges, opportunities, and prospects of adopting and using smart digital technologies in learning environments: An iterative review. Heliyon.
  • Tinoca, L., Piedade, J., Santos, S., Pedro, A. and Gomes, S., 2022. Design-based research in the educational field: a systematic literature review. Education Sciences, 12(6), p.410.
  • MATHEWS-PETT, A.M.E.L.I.A., Gods and Robots: Myths, Machines, and Ancient Dreams of Technology. By Adrienne Mayor (Princeton and Oxford: Princeton University Press, 2018. Pp. xvi+ 275, acknowl-edgements, introduction, illustrations, photographs, glos-sary, notes, bibliography, index. $29.95 hardbound.).
  • Pham, S.T., 2022. The distinctions of Heideggerian phenomenological research method. Qualitative Research Journal, 22(2), pp.261-273.
  • Neumann, A.T., Arndt, T., Köbis, L., Meissner, R., Martin, A., de Lange, P., Pengel, N., Klamma, R. and Wollersheim, H.W., 2021. Chatbots as a tool to scale mentoring processes: Individually supporting self-study in higher education. Frontiers in artificial intelligence, 4, p.668220.
  • Ustun, A.B., Zhang, K., Karaoğlan-Yilmaz, F.G. and Yilmaz, R., 2022. Learning analytics based feedback and recommendations in flipped classrooms: an experimental study in higher education. Journal of Research on Technology in Education, pp.1-17.
  • Sapci, A.H. and Sapci, H.A., 2020. Artificial intelligence education and tools for medical and health informatics students: systematic review. JMIR Medical Education, 6(1), p.e19285.
  • Wang, S., Christensen, C., Xu, Y., Cui, W., Tong, R. and Shear, L., 2020. Measuring chinese middle school students’ motivation using the reduced instructional materials motivation survey (RIMMS): a validation study in the adaptive learning setting. Frontiers in psychology, 11, p.1803.
  • Hayward, D.V., Mousavi, A., Carbonaro, M., Montgomery, A.P. and Dunn, W., 2022. Exploring preservice teachers engagement with live models of universal design for learning and blended learning course delivery. Journal of Special Education Technology, 37(1), pp.112-123.
  • Alam, A., 2022. Investigating sustainable education and positive psychology interventions in schools towards achievement of sustainable happiness and wellbeing for 21st century pedagogy and curriculum. ECS Transactions, 107(1), p.19481.
  • Malinka, K., Peresíni, M., Firc, A., Hujnak, O. and Janus, F., 2023, June. On the educational impact of ChatGPT: Is Artificial Intelligence ready to obtain a university degree?. In Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1 (pp. 47-53).
  • Pu, S., Ahmad, N.A., Khambari, M.N.M., Yap, N.K. and Ahrari, S., 2021. Improvement of Pre-Service Teachers' Practical Knowledge and Motivation about Artificial Intelligence through a Service-learning-based Module in Guizhou, China: A Quasi-Experimental Study. Asian Journal of University Education, 17(3), pp.203-219.
  • Gerogiannis, V., Tsoni, E., Born, C. and Omiros, I., 2020, January. Prioritizing Software Features based on Stakeholders Satisfaction/Dissatisfaction and their Hesitation. In 4th International Conference on Algorithms, Computing and Systems (ICACS 2020).
  • Baidoo-Anu, D. and Owusu Ansah, L., 2023. Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Available at SSRN 4337484.
  • Ouyang, F. and Jiao, P., 2021. Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, p.100020.
  • Wang, H., Liu, Y., Han, Z. and Wu, J., 2020, June. Extension of media literacy from the perspective of artificial intelligence and implementation strategies of artificial intelligence courses in junior high schools. In 2020 International Conference on Artificial Intelligence and Education (ICAIE) (pp. 63-66). IEEE.
  • He, Z. and Niu, X., 2021, November. Applying Artificial Intelligence to Primary and Secondary School Physical Education. In 2021 2nd International Conference on Information Science and Education (ICISE-IE) (pp. 1577-1581). IEEE.
  • Chen, J., Zhan, X., Wang, Y. and Huang, X., 2021, June. Medical Robots based on Artificial Intelligence in the Medical Education. In 2021 2nd International Conference on Artificial Intelligence and Education (ICAIE) (pp. 1-4). IEEE.
  • Kabudi, T., Pappas, I. and Olsen, D.H., 2021. AI-enabled adaptive learning systems: A systematic mapping of the literature. Computers and Education: Artificial Intelligence, 2, p.100017.
Еще
Статья научная