Title :
Metrics for effectiveness of e-learning objects in software engineering education
Author :
Escobar, Alvaro E. ; Reyes, P. ; Van Hilst, Michael
Author_Institution :
Div. of Math, Sci. & Technol., Nova Southeastern Univ., Fort Lauderdale, FL, USA
Abstract :
In this paper we present the rationale and beginning of work on improving e-learning objects through the use of analytics modeled after Google Analytics. Prior work on the use of metrics in e-learning has focused on user satisfaction, and the ranking and selection of learning objects from a set of available choices. This work differs in its focus on the kinds of metrics needed to improve an existing object, or even more specifically to make improvements to specific pages within an object. This work is based on the now well established track record of using Google Analytics for Web site optimization in e-commerce. We discuss adaptations needed to apply similar metrics in the context of e-learning and more specifically e-learning objects.
Keywords :
learning management systems; Google Analytics; Web site optimization; analytics modelling; e-Iearning object improvement; e-commerce; e-learning object effectiveness; software engineering education; Business; Calibration; Current measurement; Electronic learning; Training; World Wide Web; Google Analytics; learning management systems; learning objects;
Conference_Titel :
SOUTHEASTCON 2014, IEEE
Conference_Location :
Lexington, KY
DOI :
10.1109/SECON.2014.6950671