Joana Heil, Chair of Learning, Design and Technology: Online Assessment & Assessment Analytics (May 2025)

Joana is a PhD student at the Chair of Learning, Design and Technology since 2021. After a bachelor’s degree in educational science/education management at the Albert-Ludwigs-Universität Freiburg, she completed her master's degree in cognitive science at the University of Osnabrück with a focus on artificial intelligence and computational linguistics.

What is your current research topic?

My current research topic is Online Assessment, with a specific focus on Higher Education and Assessment Analytics.

For those who have not yet delved deeply into the topic of Data Science: How would you explain to a child what you are working on?

Learning is not something we do once, but a process that spans over time. We are trying to help teachers and students to understand what happens in this process and what they can do to reach their goal.

Everyone talks about Data Science – how would you describe the importance of the topic for yourself in three words?

Knowledge Discovery, Structure and Prediction

What points of contact with Data Science does your work have? Which methods do you already use, and which would be interesting for you in the future?

In educational technology, we use data science for analysis of psychometrical research through methods of quantitative data analysis or exploratory approaches such as clustering. Furthermore, the practical application of Data Science in educational are manifold. Examples are Large Language Models such as BERT for automated essay grading, methods such as Decision Trees for learner classification or social network analysis for collaborative learning. In the future, a stronger connection between pedagogy and Data Science would be very beneficial.

How high is the value of Data Science for your work? Would your research even be possible without Data Science?

Research shows us that Data Science can play a significant role in adapting and modelling learning experiences for students. It improves and speeds up processes, if applied thoughtfully, and therefore allows for valuable research as well as complex data analysis. Our research would be possible to some degree but would be on a different scale.

What development opportunities do you see for the topic of Data Science in relation to your field?

Empirical evidence highlights the need for data literate teachers as well as students considering the application of Data Science in Education. More education and intuitive solutions on a broad scale would definitely help our field to grow and apply. Considering the research and praxis, local, pedagogically valid and data-security conform solutions will be highly beneficial.

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