Abstract—Supporting user friendly intelligible and
comprehensive explanations in context-based, adaptive systems
is a big challenge. They are important for a personalized system
to support user acceptance and user trust. In cases, where
privacy laws like the General Data Protection Regulation
(GDPR) are affected, it’s even more challenging. GDPR e. g.
demands explanations of data usages, i. e. explanations where
and for what purpose personal data is being processed.
Currently, users cannot retrace the usage and the storage of
their personal data in context-based adaptive collaboration
environments. We address the aforementioned problem by
developing a context-based adaptive platform linked to an
adaptive personalized learning environment (APLE) to support
learners with intelligible, comprehensible explanations of
system processes.
Index Terms—Comprehensibility, context-based adaptive
systems, context modelling, GDPR, intelligibility, ontology,
personal explanations, privacy law.
The authors are with the FernUniversität in Hagen, Faculty of
Mathematics and Computer Science, 58084 Hagen, Germany (e-mail:
mandy.goram@fernuni-hagen.de, dirk.veiel@fernuni-hagen.de).
Cite: Mandy Goram and Dirk Veiel, "A Context Model for Intelligible Explanations in Adaptive Personalized Learning Environments," International Journal of Information and Education Technology vol. 10, no. 5, pp. 351-355, 2020.
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).