Research Center for Learning Analytics and Digital Education

 

Speaker: Prof. Dr. Christoph Meinel, Dr. Thomas Staubitz

 

The term learning analytics refers to the collection, aggregation, analysis, and evaluation of data about learners and their digitally supported learning contexts. This form of data analysis is motivated by technical, pedagogical, political and economic considerations. The evaluation of learner data makes it possible to assess the effectiveness of digital learning formats and methods in order to better understand and optimize the learning process as a whole. Digital education enables personalized support for learners, which the German University of Digital Science can use directly to improve its offerings.
In recent years, various forms of digital learning have emerged that can be categorized as lifelong learning. MOOCs – Massive Open Online Courses – have been particularly successful. These are offered by renowned universities worldwide on various platforms. The trend is to bundle such courses into packages in order to obtain so-called micro-credentials or micro-degrees. As a native digital university, the German University of Digital Science is predestined to analyze different digital learning opportunities in a comprehensive way, to research quality criteria for good teaching and to set scientifically based quality standards.

The Research Center Learning Analytics and Digital Education will address these challenges, especially in the following areas:

1. Learning analytics for improving (digital) teaching
2. Use of AI methods in teaching, assistance systems
3. Online examination formats, online support
4. Competency-based formats, project-based learning, teamwork
5. Game-based learning, support of the learning process through playful elements
6. Automatically assessable tasks, programming, math
7. Learning on mobile devices
8. Establishing international quality standards

The research center Learning Analytics and Digital Education involves professors and researchers from different disciplines (computer science, AI, distributed systems, statistics, pedagogy, didactics, sociology, law) and companies in an interdisciplinary way with other research centers of the German University of Digital Science. In addition, collaboration with other universities and industry through research partnerships or external Ph.D. students is planned. Due to the overall digital character of the German University of Digital Science, doctoral and master students are not bound to a specific location. Through regular communication with supervisors and active (weekly) participation in the Research School of the Research Center, students and doctoral candidates learn to interact and learn from each other. Topics for master’s theses and doctoral dissertations are derived from the research foci and projects.