Abstract
In this work we address the problem of automatically finding prerequisite relations among learning materials in order to help instructional designers to speed up the course building process. Ours is a data-driven approach, where a (machine) learner is trained to classify predecessor/successor relationships, given two didactic materials in a textual form. As the training set we use the learning materials extracted from Coursera. A first evaluation shows promising results.
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DAJEE can be accessed publicly for research purposes only, following the authors’ approval. Apply for it by filling in the form at http://144.6.235.142/dajee.
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De Medio, C. et al. (2016). Discovering Prerequisite Relationships Among Learning Objects: A Coursera-Driven Approach. In: Chiu, D., Marenzi, I., Nanni, U., Spaniol, M., Temperini, M. (eds) Advances in Web-Based Learning – ICWL 2016. ICWL 2016. Lecture Notes in Computer Science(), vol 10013. Springer, Cham. https://doi.org/10.1007/978-3-319-47440-3_29
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