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The LAPS Project: Using Machine Learning Techniques for Early Student Support

  • Mathias HinkelmannEmail author
  • Tobias Jordine
Chapter

Abstract

This chapter introduces the LAPS project, which is able to analyze progressions of former students and to make statements on possible risks for currently enrolled students by using machine learning techniques. It is also possible to get information about courses, lectures, and student cohorts. The project does not only include a web-based software, it also consists of a student consultation process which respects students’ self-responsibility, individuality, confidentiality, and anonymity. This chapter provides insights how the project is technically developed at the Hochschule der Medien, Stuttgart, Germany, and how it can be used in consultation situations.

Keywords

Early student support Machine learning Risk calculation Student consultation process Privacy 

Notes

Acknowledgments

The LAPS team likes to thank the developers of S-Beat,2 namely, Dominik Herbst, Niclas Steigelmann, and Annkristin Stratmann, which served as the technical foundation for the feasibility study. Additionally, we like to thank the authors of the “Softwaregestützte Studienverlaufsanalyse zur frühzeitigen gezielten Studienberatung” article, namely, Prof. Dr. Johannes Maucher and Prof. Dr. Tobias Seidl, which served as a foundation for this book chapter. Finally, we like to thank the “Digital Innovations for Smart Teaching—Better Learning” promotional program for allowing us to further improve the project.

References

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science and MediaHochschule der MedienStuttgartGermany

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