A collaborative algorithmic problem-based learning environment using learners' learning styles

Abstract

All the algorithmic courses taught in the first year of computer science at our university are face-to-face, our research aims to present the improvements that online adaptive training can bring to the learning style of learners. In particular in terms of learners' subjective satisfaction and learning speed and performance.The objective of this research is to find the contribution that problembased learning can make to the learner's learning style within a social network.The technique proposed in this paper aims to personalize learning by applying Felder-Silverman's model of learning styles and intelligent technologies, for example, such as ontology and data mining methods to improve the quality and sustainability of learning. The PBL process does not focus on problem solving with a defined solution, but takes into consideration the improvement of other attractive abilities and qualities. This will include learning, improved collaboration and group communication.