Using predictive modelling for identify students at risk of poor university outcomes.

Autor/inn/en	Jia, Pengfei; Maloney, Tim
Titel	Using predictive modelling for identify students at risk of poor university outcomes.
Quelle	In: Higher education, 70 (2015) 1, S. 127-149Infoseite zur Zeitschrift PDF als Volltext Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; gedruckt; Zeitschriftenaufsatz
ISSN	0018-1560; 1573-174X
DOI	10.1007/s10734-014-9829-7
Schlagwörter	Lehre; Studium; Studiendauer; Studienerfolg; Studienverhalten; Studentenschaft; Student; Ausland; Neuseeland
Abstract	Predictive modelling is used to identify students at risk of failing their first-year courses and not returning to university in the second year. Our aim is twofold. Firstly, we want to understand the factors that lead to poor first-year experiences at university. Secondly, we want to develop simple, low-cost tools that would allow universities to identify and intervene on vulnerable students when they first arrive on campus. This is why we base our analysis on administrative data routinely collected as part of the enrollment process from a New Zealand university. We assess the 'target effectiveness' of our model from a number of perspectives. This approach is found to be substantially more predictive than a previously developed risk tool at this university. For example, observations from validation samples in the top decile of risk scores account for nearly 28 % of first-year course non-completions and 22 % of second-year student non-retentions at this university. (HRK / Abstract übernomen)
Erfasst von	Hochschulrektorenkonferenz, Bonn
Update	2016/1