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2021 | OriginalPaper | Chapter

Intelligent Mentoring Bots in Learning Management Systems

Concepts, Realizations and Evaluations

Authors : Alexander Tobias Neumann, Peter de Lange, Ralf Klamma, Norbert Pengel, Tamar Arndt

Published in: Learning Technologies and Systems

Publisher: Springer International Publishing

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Abstract

Mentoring students in online courses is an essential task to keep students on track. Often, they ask simple questions or have repetitive issues. However, due to a high resource demand, this task is difficult to achieve on a massive scale. Digitizing mentoring processes has a high potential to fill this resource gap. In this paper, we present the concept, implementation and evaluation of intelligent mentoring bots. These bots are implemented as chatbots that can be integrated into learning management systems. With these bots, we enable 24/7 mentoring support for students. Students can ask Frequently Asked Questions (FAQs) regarding their general studies or about one of their current classes. Further, we integrate external learning applications with the bots to provide personalized feedback to students. The realization of the chatbots is based on Natural Language Understanding (NLU) to identify the respective intent of the student. We apply those chatbots as an additional offer in university courses and evaluate them in this context. We see the potential of bots as a scalable solution for mentoring in online courses.

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Metadata
Title
Intelligent Mentoring Bots in Learning Management Systems
Authors
Alexander Tobias Neumann
Peter de Lange
Ralf Klamma
Norbert Pengel
Tamar Arndt
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-66906-5_1

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