Massive Open Online Courses (MOOCs) are among the most popular online learning systems, with courses characterized by a very large number of attendees. Monitoring the students' learning process in a MOOC can be hard for the teacher, due to sheer numbers. Moreover, MOOC platforms produce large amounts of data related to the dynamics of the students community, which, if well used, can contribute to improving the educational offer. Here we present a web-based system, allowing the teacher to simulate a MOOC class of students, and experiment with it, by applying a pedagogic strategy based on Peer Assessment. The simulated students (peers) are supposed to produce answers to a question, and assessments of some other peers' answers, according to the models used to define the simulated class. Using our system the teacher can observe the dynamics of the simulated MOOC, based on a modified version of the K-NN algorithm, in line with the Teaching Analytics discipline. A first trial of the system produced promising results, showing its usefulness to support Teaching Analytics.
A Web-based System to Support Teaching Analytics in a MOOC's Simulation Environment
Sciarrone F.;
2020-01-01
Abstract
Massive Open Online Courses (MOOCs) are among the most popular online learning systems, with courses characterized by a very large number of attendees. Monitoring the students' learning process in a MOOC can be hard for the teacher, due to sheer numbers. Moreover, MOOC platforms produce large amounts of data related to the dynamics of the students community, which, if well used, can contribute to improving the educational offer. Here we present a web-based system, allowing the teacher to simulate a MOOC class of students, and experiment with it, by applying a pedagogic strategy based on Peer Assessment. The simulated students (peers) are supposed to produce answers to a question, and assessments of some other peers' answers, according to the models used to define the simulated class. Using our system the teacher can observe the dynamics of the simulated MOOC, based on a modified version of the K-NN algorithm, in line with the Teaching Analytics discipline. A first trial of the system produced promising results, showing its usefulness to support Teaching Analytics.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
