Abstract
Open Learning Analytics (OLA) is an emerging concept in the field of Learning Analytics (LA). It deals with learning data collected from multiple environments and contexts, analyzed with a wide range of analytics methods to address the requirements of different stakeholders. Due to this diversity in different dimensions of OLA, the LA developers and researchers face numerous challenges while designing solutions for OLA. The Open Learning Analytics Platform (OpenLAP) is a framework that addresses these issues and lays the foundation for an ecosystem of OLA that aims at supporting learning and teaching in fragmented, diverse, and networked learning environments. It follows a user-centric approach to engage end users in flexible definition and dynamic generation of personalized indicators. In this paper, we address a subset of OLA challenges and present the conceptual and implementation details of the analytics framework component of OpenLAP, which follows a flexible architecture that allows the easy integration of new analytics methods and visualization techniques in OpenLAP to support end users in defining indicators based on their needs in order to embed the results into their personal learning environment.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
