Authors:
Nathalie Rzepka
1
;
Katharina Simbeck
1
;
Hans-Georg Müller
2
and
Niels Pinkwart
3
Affiliations:
1
University of Applied Sciences Berlin, Treskowallee 8, 10318 Berlin, Germany
;
2
Department of German Studies, University of Potsdam, Am neuen Palais 10, 14469 Potsdam, Germany
;
3
Department of Computer Science, Humboldt University of Berlin, Unter den Linden 6, 10099 Berlin, Germany
Keyword(s):
Online Controlled Experiments, Adaptive Learning Systems, Digital Learning Environment, Learning System Architecture.
Abstract:
Digital learning platforms are more and more used in blended classroom scenarios in Germany. However, as learning processes are different among students, adaptive learning platforms can offer personalized learning, e.g. by individual feedback and corrections, task sequencing, or recommendations. As digital learning platforms are already used in classroom settings, we propose the transformation of these platforms into adaptive learning environments. To measure the effectiveness and improvements achieved through the adaptions an online-controlled experiment design is created. Our result is a process that consists of the target definition, development of the prediction model, definition of the adaptions, building the experiment architecture, the experimental period, and the hypothesis testing. As an example, we apply this design exemplarily to an online learning platform for German spelling and grammar. In this way, we contribute to the research field by bridging the gap between adaptiv
e learning technology and the process of transformations and experiment designs.
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