Abstract
This paper presents the design of a learning analytics dashboard, utilizing learning traces that emerge from conversational MOOC activities. These chat-based activities encourage students to collaborate in dyads, with the support of a conversational agent, in order to answer open-ended questions, set by the course instructor. Taking into account the dynamic and context-sensitive nature of the agent-based support provided during this kind of online activities, we aspire to share a series of variables, metrics and use cases, which can be valuable for practitioners and researchers looking forward to initiate the development of a learning analytics dashboard that encompasses aspects of both peer-to-peer and human-to-bot conversational interactions.
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Acknowledgements
This research has been funded by the Erasmus+ Programme of the European Commission (project No 588438-EPP-1-2017-1-EL-EPPKA-KA). This document reflects the views only of the authors. The Education, Audiovisual and Culture Executive Agency and the European Commission cannot be held responsible for any use which may be made of the information contained therein.
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Tegos, S., Tsiatsos, T., Psathas, G., Demetriadis, S. (2021). Towards a Learning Analytics Dashboard for Collaborative Conversational Agent Activities in MOOCs. In: Auer, M.E., Tsiatsos, T. (eds) Internet of Things, Infrastructures and Mobile Applications. IMCL 2019. Advances in Intelligent Systems and Computing, vol 1192. Springer, Cham. https://doi.org/10.1007/978-3-030-49932-7_65
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