Title
Visual learning analytics techniques applied in software engineering subjects
Abstract
The technology applied to educational contexts, and specially the learning platforms, provides students and teachers with a set of tools and spaces to carry out the learning processes. Information related to the participation and interaction of these stakeholders with their peers and with the platform is recorded. It would be useful to exploit this information in order to make decisions. However this is a complex activity mainly because of the huge quantity of information stored. This work presents a visual learning analytics system that makes possible the exploitation of that information. The system includes several tools that help to analyze users' interaction attending to different dimensions, such as: when interaction is carried out, which are more important contents for users, how they interact with others, etc. This system has been tested with the subject information recorded during five academic years. From this analysis it is possible to show that visual learning analytics may help to improve educational practices.
Year
DOI
Venue
2014
10.1109/FIE.2014.7044486
FIE
Keywords
Field
DocType
computer science education,data visualisation,learning management systems,software engineering,educational context,software engineering subject,visual learning analytics,data mining,lms,learning analytics,visual analytics,data visualization,semantics
Data science,Speech analytics,Software analytics,Web analytics,Computer science,Visual analytics,Semantic analytics,Cultural analytics,Visual learning,Analytics
Conference
ISSN
Citations 
PageRank 
0190-5848
5
0.45
References 
Authors
22
6