Recommendation acceptance in a simple adaptive learning system

Holthaus, Matthias and Pancar, Tansu and Bergamin, Per (2019) Recommendation acceptance in a simple adaptive learning system. In: International Journal on Advances in Intelligent Systems UNSPECIFIED, 24/02 - 28/02, Athen. (In Press)

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In the following article we report the current status of our research on integrating a simple, useful adaptive learning system into a university's standard learning management system. In this context, a corresponding instructional design was implemented for a basic mathematics course with the aim of supporting students in their self-study. A rule-based tool was developed for this purpose. The theoretical basis of the design was the Cognitive Load Theory. Based on the principles of this theory, the load on the working memory of the students during learning was to be optimized by appropriate task difficulties. It was expected that the learning performance would be improved. The first results from one of our preliminary studies focusing on learning progress, activity and previous knowledge of different groups of students showed that students who actively worked with adaptive tasks benefited from the system and achieved a greater learning progress than the comparison groups. In the follow-up to this finding, new research questions have arisen for us on the basis of certain limits of the previous study. All of these questions aim to determine whether the positive learning effects can be attributed to the increase in learning activities alone or to following the recommendations or to the interaction of both. In this paper, we present the next research steps in the sense of a framework in order to find the corresponding answers.

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