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This page is basically not written. For now I have just 3 things to say.
My older notes giving some perspective on retention are here.
As those notes say, the single biggest name to look for in the literature is Tinto. For the UK, the second biggest name to look for is Mantz Yorke. E.g.
A paper worth looking at, from a statistician's viewpoint (rather than from
Tinto's or from the education literature's viewpoint) is:
Smith J. & R. A. Naylor (2001) "Dropping out of university: a statistical analysis of the probability of withdrawal of UK university students" Journal of the Royal Statistical Society (Series A) vol.164 pp.389-405
It is interesting for at least these reasons: it is UK data, it is a re-analysis of government data, it looks at the independent contributions of many factors to dropout. It shows that the patterns of male and female dropout are substantially different. It has a substantiated argument about why league tables comparing university dropout rates are largely meaningless. But all the many factors they analyse account together for only about 10% of the variance, so most of it could be susceptible to improvement -- or could just be beyond control.
Even then, it will be like interviewing people about their divorces: everyone will have a story, but it is a story they can live with, scarcely a dispassionate account. Rationalisation by each student, particularly dropouts, may mean that what they say about causes is not useful. They will be very likely to describe cause as external factors (the classic Social Psychology attribution error?). So for this, should attend only to data on external factors, and get it equally for persisters. In fact the Brown and Harris method of collecting descriptions of external factors for all, and getting a panel of experts to rate their seriousness "blindly", may be essential.
Similarly for "internal" and all "ask them" measures of attitude, Tinto integration etc.: we should ask all students before as well as after external events, and before exam results, and before dropouts. I.e. do prospective studies.
The other approach is "experimental": intefere, and report what actions actually change dropout, regardless of what participants report. This gets round the important issue of self-interest in reporting dropouts, which is a significant life event. Studies reporting this kind of evidence are mentioned in this page. This yields the "best" evidence in the sense of the most believable as far as it goes. Drawbacks are that it is limited to testing the interventions that have occurred to researchers (and there's no guarantee they guess good ones to try), and interventions that are cheap enough to be easy to get done. Thus the effect of single phone calls, and short written passages have been tested (with surprisingly powerful results); but there have been no studies of systematically varying the induction procedures of whole institutions.
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