Navigationsweiche Anfang

Navigationsweiche Ende

Select language

News


  • For news in pictures click the ­home button. For older news go to the archive. [more]
go to Archive ->

Early identification of dropout risks

Topic:

Early identification of dropout risks from university and the effectiveness of interventions

 

Principal Investigators:

Kerstin Schneider, Simon Görtz

 

Staff:

Johannes Berens (contact person), Simon Oster

 

Duration: 2017-2020

 

Publications:

Berens, J., Schneider, K., Görtz, S., Oster, S., Burghoff, J. (2019): Early Detection of Students at Risk - Predicting Student Dropouts Using Administrative Student Data from German Universities and Machine Learning Methods. In: Journal of Educational Data Mining, 11(3), 1-41. https://doi.org/10.5281/zenodo.3594771

Schneider, K., Berens, J., Burghoff, J. (2019): Drohende Studienabbrüche durch Frühwarnsysteme erkennen: Welche Informationen sind relevant?. In: Zeitschrift für Erziehungswissenschaften, 221121-1146. DOI: 10.1007/s11618-019-00912-1

Berens, J., Schneider, K. (2019): Drohender Studienabbruch: Wie gut sind Frühwarnsysteme? In: Qualität in der Wissenschaft (QiW), 3+4/19, 102-108. ISSN 1860-3041

Berens, J., Schneider, K., Görtz, S., Oster, S., Burghoff, J. (2018): Early Detection of Students at Risk - Predicting Student Dropouts Using Administrative Student Data and Machine Learning Methods. CESifo Working Papers, 7259. [download from RePEc]

 

Funded by: