Towards a characterization of educational material: An analysis of coursera resources
Author(s)
De Medio, Carlo
Gasparetti, Fabio
Limongelli, Carla
Lombardi, Matteo
Marani, Alessandro
Sciarrone, Filippo
Temperini, Marco
Year published
2017
Metadata
Show full item recordAbstract
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 ...
View more >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.
View less >
View more >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.
View less >
Journal Title
Lecture Notes in Computer Science
Volume
10108
Subject
Information and Computing Sciences not elsewhere classified