Open AccessA Proposed Learner’s Data Model: Integrating Informal Learning and Enhancing Personalization and Interoperability
Author(s) -
Nissrin Nehiri,
Noura Aknin
Publication year - 2021
Publication title -
international journal of emerging technologies in learning/international journal: emerging technologies in learning
Language(s) - English
Resource type - Journals
eISSN - 1868-8799
pISSN - 1863-0383
DOI - 10.3991/ijet.v16i08.19833
Subject(s) - interoperability , personalization , computer science , xml , world wide web , key (lock) , semantic interoperability , knowledge management , multimedia , data science , computer security
A learner profile is key to personalize learning content. Nowadays learners use different applications and tools to learn (Formal and informal types). Indeed, the diversity of profiles, their content, their structure, their operation, and the actors concerned, limits possible interoperability. Hence, the need for a rich and an interoperable learner profile that describes all previous learning achievements or experiences. In this work, after a brief analysis of available standards in this area, an approach is proposed to build an interoperable learner model based on xAPI statements that combine the formal and informal experiences to enhance learning analytic and personalization. Then, we present a tool to transform collected data into our XML model proposed based on the IMS-LIP standard, and in the end, we explore his utility.