Personalised Technology-enhanced Learning Environments

In our research on personalised technology-enhanced learning environments we are addressing three main research objectives. First, we investigate the use of diagnostic assessments for the detection of a learner's knowledge gaps or skill gaps. Based on knowledge graphs and learning paths our personalised learning environment then suggests the right learning content based on a learner's current knowledge and experience. Further, we aim for automatic content adaptation based on a learner's individual constraints and preferences to ensure maximal accessibility.

 

 

In order to model the complex domain-specific knowledge, we opted to use the resource-selector-link (RSL) hypermedia metamodel. Instead of simply suggesting different exercises based on a learner's proficiency, we might adapt the exercises based on the RSL model's concept of structural links and their use for adaptive document structures.

Related Publications

Status: Ongoing

Start Date: 01-08-2021

Related Research Topics