Authors:
Eleni Ilkou
and
Beat Signer
Affiliation:
Web & Information Systems Engineering Lab, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
Keyword(s):
Knowledge Graphs, Learning Paths, e-Learning, Smart Education, Smart Learning, Educational Application, Assessment Classification, Personalised Teaching Assistant Tool, Mathematics Education.
Abstract:
In our position paper on a technology-enhanced smart learning environment, we propose the innovative combination of a knowledge graph representing what one has to learn and a learning path defining in which order things are going to be learned. In this way, we aim to identify students’ weak spots or knowledge gaps in order to individually assist them in reaching their goals. Based on the performance of different learning paths, one might further identify the characteristics of a learning system that leads to successful students. In addition, by studying assessments and the different ways a particular problem can be solved, new methods for a multi-dimensional classification of assessments can be developed. The theoretical findings on learning paths in combination with the classification of assessments will inform the design and development of a smart learning environment. By combining a knowledge graph with different learning paths and the corresponding practical assessments we enable
the creation of a smart learning tool. While the proposed approach can be applied to different educational domains and should lead to more effective learning environments fostering deep learning in schools as well as in professional settings, in this paper we focus on the domain of mathematics in primary and high schools as the main use case.
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