The Learner-Model-Server (LMS for short) is a central software component for the VoLL-KI ecosystem.
Here, the competency mappings of the learners are calculated, altered, and stored (pseudonymized and protected from external access).
This information is then used elsewhere to generate and make available learning materials that are tailored to individual learners and particularly useful to them (such as Guided Tours).
The actual model we use for the goals, progress, and success of learners is based on Bloom’s learning taxonomy, adapted as in Fuller et al.
In particular, this model distinguishes between two categories of skills: skills for knowledge interpretation and skills for knowledge production.
For a single topic, such as a specific definition, the competencies of individual learners as well as all learners as a group are distinguished and studied closely.
Someone who can accurately reproduce a definition may not necessarily be able to use it in an application context or provide their own examples.
Therefore, we also want to capture these differences in our model in order to offer learners the best possible, tailored support.
The most important data on which we base this modeling are, of course, inputs from the learners themselves.
However, it is not realistic to regularly test or question all learners on every competency for every topic, so other relationships are also taken into account.
For example, the competency distribution of learners in a topic can influence the model of the distribution in a related topic.
Similarly, the distribution of other comparable learners could also be relevant.
We hope to be able to research and determine which configuration of this system will produce the best results for learners and educators during this project.