Open Source Learning Management Service for flexible and stronger teaching oriented to students interests and higher motivation of the teaching innovations

The University of Hildesheim understands itself in view of social changes and global challenges as a “cosmopolitan place of learning” for the people with different skills and potentials. With this background, the university is a modern form of the old European idea of ​​the community of teachers and students - universitas magistrorum et scholarium. This includes, continuously realigning the courses and learning opportunities at the university to meet socio-political expectations and challenges of modern higher education. In recent years, the University of Hildesheim has the educational concept of a diversity-oriented teaching with numerous opportunities for support and advice which can be seen from the heterogeneity among its students.

Digitization should never be a mere digital representation of existing processes and structures, but always as an opportunity to establish new approaches and principles. This project, in cooperation with Software Systems Engineering (SSE) and Information Systems and Enterprise Modelling (ISUM) departments from University of Hildesheim, aims at developing an open source learning management service that provides digital support to improve learning of the students at the University of Hildesheim. This platform helps in enhancing the various teaching and learning activities such as: enabling composition of working groups in an event, submitting software program related assignments, developing concept maps for the seminars, collaborative literature analysis and so on.

But as important as such a basic competence in the field of data science, a data literacy, is, so little do most employees currently feel prepared. In a study by Qlik2 among 5500 employees and managers of various organizations from five European countries, only 17% consider themselves data competent, in Germany only 14%.

Our group, Information Systems and Machine Learning Lab, works on integrating the digital feedback received from the students and recommender systems to provide individually tailored recommendations to further the teaching and learning paths. The example use cases are: sequencing the tasks (assignments for example), selection of possible contents (tasks, atomic learning units etc.) from an existing pool to motivate further self-study and so on.

The planned developments will help in flexible and stronger teaching oriented to student interests. As a result, dropout rates due to typical organizational problems are reduced, but there will also be a higher motivation of the teaching innovations.