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.
DE MEDIO, C., Gasparetti, F., Limongelli, C., Lombardi, M., Marani, A., Sciarrone, F., et al. (2016). Discovering Prerequisite Relationships Among Learning Objects: A Coursera-Driven Approach. In Advances in Web-Based Learning – ICWL 2016 (pp.261-265) [10.1007/978-3-319-47440-3_29].
Discovering Prerequisite Relationships Among Learning Objects: A Coursera-Driven Approach
DE MEDIO, CARLO;GASPARETTI, FABIO;LIMONGELLI, Carla;SCIARRONE, FILIPPO;
2016-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
