Modelling Students at Risk
AbstractUsing a sample of several hundred students we model progression in a first-year econometrics course. Our primary interest is in determining the usefulness of these models in the identification of 'students at risk'. This interest highlights the need to distinguish between students who drop the course and those who complete but who ultimately fail. Such models allow identification and quantification of the factors that are most important in determining student progression and thus make them a potentially useful aid in educational decision making. Our main findings are that Tertiary Entrance Rank (TER), mathematical aptitude, being female and attendance in tutorials are all good predictors of success but amongst these factors only attendance is significant in discriminating between students who fail and those who discontinue. Also, there are differences across degree programs and, in particular, students in Combined Law are very likely to pass but, if they are at risk, they are much more likely to discontinue than to fail. Copyright Blackwell Publishing Ltd/University of Adelaide and Flinders University of South Australia 2004.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Wiley Blackwell in its journal Australian Economic Papers.
Volume (Year): 43 (2004)
Issue (Month): 2 (06)
Contact details of provider:
Web page: http://www.blackwellpublishing.com/journal.asp?ref=0004-900X
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Prowse, Victoria, 2012.
"Modeling employment dynamics with state dependence and unobserved heterogeneity,"
38038, University Library of Munich, Germany, revised 10 Apr 2012.
- Victoria Prowse, 2012. "Modeling Employment Dynamics With State Dependence and Unobserved Heterogeneity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 411-431, April.
- Victoria Prowse, 2007. "Modeling Employment Dynamics with State Dependence and Unobserved Heterogeneity," Economics Series Working Papers 337, University of Oxford, Department of Economics.
- Prowse, Victoria L., 2010. "Modeling Employment Dynamics with State Dependence and Unobserved Heterogeneity," IZA Discussion Papers 4889, Institute for the Study of Labor (IZA).
- Hong il Yoo, 2012. "A new condition for pooling states in multinomial logit," Discussion Papers 2012-48, School of Economics, The University of New South Wales.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.