TY  - CHAP
A1  - Tillmann, Alexander
A1  - Krömker, Detlef
A1  - Horn, Florian
A1  - Gattinger, Thorsten
A2  - Bergner, Nadine
A2  - Röpke, René
A2  - Schroeder, Ulrik
A2  - Krömker, Detlef
T1  - Analysing & predicting students performance in an introductory computer science course
T2  - Hochschuldidaktik der Informatik HDI 2018 : 8. Fachtagung des GI-Fachbereichs Informatik und Ausbildung/Didaktik der Informatik ; 12.-13. September 2018 an der Goethe-Universität Frankfurt am Main, Commentarii informaticae didacticae (CID) ; 12
N2  - Students of computer science studies enter university education with very different competencies, experience and knowledge. 145 datasets collected of freshmen computer science students by learning management systems in relation to exam outcomes and learning dispositions data (e. g. student dispositions, previous experiences and attitudes measured through self-reported surveys) has been exploited to identify indicators as predictors of academic success and hence make effective interventions to deal with an extremely heterogeneous group of students.
KW  - Learning analytics
KW  - Learning dispositions
KW  - Dispositional learning analytics
KW  - Formative assessment
KW  - Blended learning
KW  - heterogeneity
Y1  - 2018
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/46847
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-468478
UR  - https://publishup.uni-potsdam.de/files/41354/cid12.pdf
SN  - 978-3-86956-435-7
SN  - 3-86956-435-0
SN  - 1868-0844
SN  - 2191-1940
N1  - Dieses Werk ist unter einem Creative Commons Lizenzvertrag lizenziert: Namensnennung 4.0 International. Um die Bedingungen der Lizenz einzusehen, folgen Sie bitte dem Hyperlink: http://creativecommons.org/licenses/by/4.0/
SP  - 29
EP  - 45
PB  - Universitätsverlag Potsdam
CY  - Potsdam
ER  -