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 datadriven 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.
CITATION STYLE
De Medio, C., Gasparetti, F., Limongelli, C., Lombardi, M., Marani, A., Sciarrone, F., & Temperini, M. (2016). Discovering prerequisite relationships among learning objects: A coursera-driven approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10013 LNCS, pp. 261–265). Springer Verlag. https://doi.org/10.1007/978-3-319-47440-3_29
Mendeley helps you to discover research relevant for your work.