Adaptive learning
Adaptive learning is an innovative approach to learning that uses computer algorithms to coordinate the learning program to the student. It does so by customizing resources and tasks to suit the needs of an individual (Midgley, 2014). It often starts by participants trying out one method of training to see if it works well for them. Next, algorithms change the educational material based on students reactions and responses to assignments and exercises. The adaptive learning mechanisms are based on the knowledge from scientific fields such as artificial intelligence, psychology and neuroscience (Dawid, 2011).
One of the main inspirations for the development of adaptive learning systems was the fact that studying on a bigger than local scale cannot easily be custom - fitted to students by using traditional methods. Adaptive learning main advantage is that it makes the student more of a collaborator in the learning experience than just a passive receiver of data. Although adaptive learning is mainly used in educational fields it can also be helpful in business courses. Adaptive learning tools are usually in the form of computer or internet applications (Yang et al., 2013).
Main applications of adaptive learning
There is three main applications:
- Learning management system - A lot of corporations use so called learning management systems (LMS). Learning management system is an software program that is used for the handling of the documents, reports and tasks involved in the educational courses and programs, often adopted by large companies.
- Distance learning - Distance learning is a very useful tool, but it presents some challenges for education. Adaptive learning is perfect for distance learning and class teamwork. In the beginnings of distance learning, provided tools were able to give students simple automated feedback on their performance. Nowadays, adaptive learning systems can, in a way, substitute teachers. Adaptive learning programs are able to give personalized feedback and suggestions that are well suited for individual students (Truong, 2016).
- Group collaboration - adaptive learning can be used to help promote group interaction and teamwork. Modern adaptive learning systems are able to automatically link users with similar interests and similar online behaviour that was being analyzed by the program. With this method people are easily able to start work together, because of the lack of unnecessary conflicts (Wang & Wu, 2011).
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References
- Aguilera, N. E., Fernandez, G., & Fitz-Gerald, G. (2002). Addressing different cognitive levels for on-line learning, In Ascilite (pp. 39-46).
- Dawid, H. (2011). Adaptive learning by genetic algorithms: Analytical results and applications to economic models, Springer Science & Business Media.
- Gaudioso, E., & Boticario, J. G. (2003). Towards web-based adaptive learning communities, In Proceedings of the 11th International Conference on Artificial Intelligence in Education (AIED’2003). Sidney, Australia.
- Lin, F., Graf, S., & McGreal, R. (2004). Adaptive and Intelligent Web-Based Educational Systems, Guest Editorial Preface.
- Midgley, C. (Ed.). (2014). Goals, Goal Structures, and Patterns of Adaptive Learning, Routledge.
- Truong, H. M. (2016). Integrating learning styles and adaptive e-learning system: Current developments, problems and opportunities, Computers in human behavior, 55, 1185-1193.
- Wang, S. L., & Wu, C. Y. (2011). Application of context-aware and personalized recommendation to implement an adaptive ubiquitous learning system, Expert Systems with applications, 38(9), 10831-10838.
- Yang, T. C., Hwang, G. J., & Yang, S. J. H. (2013). Development of an adaptive learning system with multiple perspectives based on students' learning styles and cognitive styles, Journal of Educational Technology & Society, 16(4), 185-200.
Author: Katarzyna Atłas