When teachers are surfing the Web to search suitable learning material for their courses it would be very important that web resources were characterized to restrict the scope of the search. Hence, it arises the need of finding characterizing properties for learning materials. This paper proposes an initial reflection on this issue. We exploit the huge potential of the MOOC, in particular Coursera, to discover new educational information that might characterize material of MOOCs. This goal is achieved by means of data mining techniques. Two types of features about resources have been discovered: teaching context and resource attributes. The resulting knowledge can be very helpful for a more accurate recommendation of resources to the particular teaching context of an instructor, as well as improving the creation and arrangement of learning activities.

De Medio, C., Gasparetti, F., Limongelli, C., Lombardi, M., Marani, A., Sciarrone, F., et al. (2017). Towards a characterization of educational material: An analysis of coursera resources. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.547-557). Springer Verlag [10.1007/978-3-319-52836-6_58].

Towards a characterization of educational material: An analysis of coursera resources

De Medio, Carlo;Gasparetti, Fabio;Limongelli, Carla;Lombardi, Matteo;Marani, Alessandro;Sciarrone, Filippo;Temperini, Marco
2017-01-01

Abstract

When teachers are surfing the Web to search suitable learning material for their courses it would be very important that web resources were characterized to restrict the scope of the search. Hence, it arises the need of finding characterizing properties for learning materials. This paper proposes an initial reflection on this issue. We exploit the huge potential of the MOOC, in particular Coursera, to discover new educational information that might characterize material of MOOCs. This goal is achieved by means of data mining techniques. Two types of features about resources have been discovered: teaching context and resource attributes. The resulting knowledge can be very helpful for a more accurate recommendation of resources to the particular teaching context of an instructor, as well as improving the creation and arrangement of learning activities.
2017
9783319528359
De Medio, C., Gasparetti, F., Limongelli, C., Lombardi, M., Marani, A., Sciarrone, F., et al. (2017). Towards a characterization of educational material: An analysis of coursera resources. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp.547-557). Springer Verlag [10.1007/978-3-319-52836-6_58].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/326029
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