Abstract
SIgBLE is a general framework devoted to providing adaptable feedback for the three kinds of actors involved in a blended-learning process: teachers, students, and learning environments. Its general objectives are to automatically detect visible signs of failure or success among data coming from the actors’ interactions and provide relevant feedback adapted to each situation and target actor. This paper focuses on SIgBLE’s general structure and main analysis process. In addition, it presents SIgMa, a specific implementation oriented toward the teacher in the context of the MAgAdI environment, along with some evaluation results.
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Martín, M., Álvarez, A., Fernández-Castro, I., Urretavizcaya, M. (2011). Adapted Feedback Supported by Interactions of Blended-Learning Actors: A Proposal. In: Biswas, G., Bull, S., Kay, J., Mitrovic, A. (eds) Artificial Intelligence in Education. AIED 2011. Lecture Notes in Computer Science(), vol 6738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21869-9_28
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DOI: https://doi.org/10.1007/978-3-642-21869-9_28
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