Collecting Experience Data from Remotely Hosted Learning Applications

The ability to integrate multiple learning applications from different organizations allows sharing resources and reducing costs in the deployment of learning systems. In this sense, Learning Tools Interoperability (LTI) is the main current leading technology for integrating learning applications with platforms like Learning Management Systems (LMS). On the other hand, the integration of learning applications also benefits from data collection, which allows learning systems to implement Learning Analytics (LA) processes. Tin Can API is a specification for learning technology that makes this possible. Both learning technologies, LTI and Tin Can API, are supported by nowadays LMS, either natively or through plugins. However, there is no seamless integration between these two technologies in order to provide learning systems with experience data from remotely hosted learning applications. Our proposal defines a learning system architecture ready to apply advanced LA techniques on experience data collected from remotely hosted learning applications through a seamless integration between LTI and Tin Can API. In order to validate our proposal, we have implemented a LRS proxy plug-in in Moodle that stores learning records in a SCORM Cloud LRS service, and a basic online lab based on Easy JavaScript Simulation (EjsS). Moreover, we have tested our implementation using resources located in three European universities.


Published in:
Online Engineering & Internet Of Things, 22, 170-181
Presented at:
14th International Conference on Remote Engineering and Virtual Instrumentation (REV), New York, NY, Mar 15-17, 2017
Year:
Jan 01 2018
Publisher:
Dordrecht, SPRINGER
ISSN:
2367-3370
2367-3389
ISBN:
978-3-319-64352-6
978-3-319-64351-9
Keywords:
Laboratories:




 Record created 2019-06-18, last modified 2019-08-12


Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)