Abstract
Learning Analytics (LA) aims to understand and optimize the learning process in the environments in which they occur. It also offers opportunities for teachers to understand students’ behavior and promote the use of effective strategies that allow them to achieve their goals. Most of current solutions proposed in the literature for supporting students’ SRL are based on dashboards. However, if students do not interact with them, it becomes difficult to understand whether they have an impact in their self-regulated behavior. This demonstration, presents Miranda: A Chatbot that acts as a conversational agent to recommend and make suggestions on SRL strategies based on students’ the behavior. The first version of Miranda has been developed for Moodle, but it could be adapted to any other Learning Management System.
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Acknowledgments
This paper was supported by Vicerrectorado de Investigación de la Universidad de Cuenca, the ANR JCJC LASER project (ANR-20-CE38–0004) and Corporación Ecuatoriana para el Desarrollo de la Investigación y la Academia – CEDIA. The authors acknowledge PROF-XXI, which is an Erasmus+ Capacity Building in the Field of Higher Education project funded by the European Commission (609767-EPP-1–2019-1- ES-EPPKA2-CBHE-JP). This publication reflects the views only of the authors and funders cannot be held responsible for any use which may be made of the information.
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Maldonado-Mahauad, J., Pérez-Sanagustín, M., Carvallo-Vega, J., Narvaez, E., Calle, M. (2022). Miranda: A Chatbot for Supporting Self-regulated Learning. In: Hilliger, I., Muñoz-Merino, P.J., De Laet, T., Ortega-Arranz, A., Farrell, T. (eds) Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption. EC-TEL 2022. Lecture Notes in Computer Science, vol 13450. Springer, Cham. https://doi.org/10.1007/978-3-031-16290-9_36
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