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December 13, 2010

Shifting the Retention Rates to Retention Risk

Mark Conrad and Kate Morris, York University

Authors:

Mark Conrad and Kate Morris, York University

Full Research Report:

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Research Summary:

Early identification of dropout risks could improve postsecondary retention rates

The dropout rate in Ontario’s colleges and universities could be reduced by identifying students early in their postsecondary career who might be at risk – long before they actually leave.

A recent study conducted by two researchers at York University for the Higher Education Quality Council of Ontario (HEQCO) proposes a new method to measure student retention at postsecondary institutions. Shifting from Retention Rates to Retention Risk: An Alternative Approach for Managing Institutional Student Retention Performance is based on a pilot project at York where researchers Mark Conrad and Kate Morris undertook a prospectiveanalysis of retention risks rather than a retrospective analysis of retention rates.

Project description
Essentially a forecast that estimates the risk of events that have not yet occurred, the authors created a statistical model based on a series of risk factors that can contribute to a student dropping out. They then applied this model to a set of current and former York students to determine whether the predicted outcomes matched actual outcomes. Using their new methodology, they were able to correctly identify slightly more than 90 per cent of first-year drop-outs and almost 25 per cent of upper-year drop-outs.

Findings
The authors say that their approach could be applied to students at the beginning of their postsecondary career, and produce an accurate estimate of the actual dropout risk posed by each individual student. Institutions would then have the opportunity to intervene well before astudent leaves the institution. Among potential risk factors, according to the study: students who are attending part time,  are not attending postsecondary institutions on scholarships or bursaries, have lower high school grades and/or have not declared a major.

Accurately assessing patterns in retention rates has been problematic, say the authors, in part because existing methods fail to take into account institutional variation and divergent student backgrounds. They note that social, economic, cultural and academic background significantly influence degree completion.

They propose using historical data at individual institutions to develop a more specialized or tailored estimate of the probability of a student dropping out at some point in the future. If the issues associated with dropping out become better.

However, the authors also acknowledge that additional research is necessary to implement their approach more widely as there remains a gap between available data and what is required to produce precise risk estimates. They suggest using interviews and focus groups to further inform institutional understanding of who drops out of postsecondary programs and why. If a prospective, retention-risk-based approach is used, they argue, institutions can both reduce dropout rates and better evaluate their retention programs.​​