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Educational Data Mining

Educational data mining is used to analyze courses of studies and conditions of study success.

For this purpose, anonymized study courses, study plans and module handbooks are analyzed. The aim is to develop a broadly applicable model of study programs for analysis. This should explore conditions for success depending on prerequisites and study design.

By this, current students can be provided with helpful hints for their studies, learning or course planning. Other possible use cases are the improvement of digital teaching or the prevention of dropouts.

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Note on Data Handling for Alumni

  • As part of the collaborative project Digital Mentoring, which is funded by the "Innovation in Higher Education" foundation, in Bochum University of Applied Sciences data of former students are processed anonymously.
  • The used data consists of student and examination data of exmatriculated students with final years 2014 to 2021.
  • The purpose of the data processing is the research of predictive possibilities of study success and dropout by means of automated procedures.

The study directors are responsible for the proper data processing.

Contact person: Basile Tousside | Digital Mentoring, e-mail: basile.tousside(at)

Data Protection Officer: The officially appointed data protection officer at Bochum University is Christina Warsitz. You can reach her as follows: Bochum University of Applied Sciences, Data Protection Officer, Am Hochschulcampus 1, 44801 Bochum, e-mail: christina.warsitz(at) 


  • Tousside, B., Dama, Y. & Frochte, J. (2022). Towards Explainability in Modern Educational Data Mining: A Survey. In: Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. Pages 212-220. DOI, PDF, BibTex