Problem solving support
This involves assisting learners in solving educational problems through personalised support. Such support uses individual learner characteristics, such as learning styles, to provide appropriate educational materials that supplement understanding of specific concepts. This can be achieved by using adaptive technologies that provide personalised feedback, recommend relevant resources, and support active learning, ensuring that each learner receives instruction suited to their needs and progress.
The adaptive system can achieve this by suggesting previously solved examples and presenting the most relevant ones to the learner. Simulations and feedback mechanisms further allow learners to practise and refine their understanding. Continuous monitoring of learner progress enables the system to personalise learning pathways and provide targeted instructional support.
Additionally, adaptive technologies such has Machine learning (MA) can predict a learner’s way of solving a particular problem and identify the most relevant examples from the learner’s history. These examples are adaptively sorted according to their relevance, so that those most similar to the current problem are presented first, using algorithms such as adaptive sorting techniques
References
- Papanikolaou, K. A., Grigoriadou, M., Magoulas, G. D., & Kornilakis, H. (2002). Towards new forms of knowledge communication: the adaptive dimension of a web-based learning environment. Computers & Education, 39(4), 333-360.