In the past, the term â€œpersistenceâ€ was used somewhat interchangeably with â€œretentionâ€ to describe the fact of students remaining in a course of studies from one year to the next, typically at a single institution and sometimes within a particular program. Over the last few years, however, persistence has shifted in meaning to refer to the ability of students to continue their PSE studies and ultimately graduate, regardless of switches between programs or institutions or even temporary absences from PSE altogether. There is a growing recognition in Ontario and across Canada that this system-wide perspective on persistence will help government and institutions manage a highly functional, well-integrated PSE system, one in which students can avail themselves of numerous alternative educational opportunities and pathways to success.
It would be a mistake, however, to assume that these system-wide concerns are the primary arena in which PSE outcomes ought to be managed. Indeed, the concept of persistence as a process whereby students overcome obstacles is of note only in the context of the presence of initial decisions to leave and not return to a particular institution. The central aim of any university ought to be to improve its own retention of students. Indeed, a sustained focus on improving in situ retention outcomes is a vital component of an overall strategy for achieving high system-wide persistence rates. It is in the best interests of government and universities to develop the means by which retention practice efficacy can be reliably assessed, compared amongst institutions and used within institutions to actively improve retention rates.
Unfortunately, two common approaches used to calculate retention rates â€“ the raw rate approach and the natural rate approach â€“ are seriously flawed and cannot be recommended for use by Ontario PSE institutions as tools for managing retention practices.
The raw rate approach is transparently inadequate. The crux of the problem with raw rates is that they are essentially outcome measures unadjusted for variation in inputs. An institution that is in a position to admit students who are highly prepared academically, financially and culturally for university life at that particular institution can expect to be rewarded with relatively high outcome rates, and this without having to innovate or invest much in retention practices. Evaluating retention practice efficacy on the basis of raw rates favours institutions that are able to offload potential retention risks during the admissions process.
Another common approach used to calculate retention rates is to calculate the differences between raw rates and â€œexpectedâ€ or â€œnaturalâ€ rates and then to base evaluations and comparisons on these differences. Natural institutional rates are averages of the estimated probabilities of an event occurring (e.g., being retained after one year, graduating within four years) for each member of a cohort of students at an institution. One key feature of the statistical models upon which the probability estimates are based is the fact that they are system-wide models, pooling data across all institutions in the study and delivering a single set of model coefficients that is applied to all institutions. Another key feature is the fact that probability estimates are based on predictor variables that usually include only pre-entry characteristics of students and sometimes include environmental characteristics such as institution size, the field of study and whether the school primarily serves urban commuters. An institution with a raw rate that exceeds its natural rate is deemed to be performing well at
2 â€“Shifting from Retention Rates to Retention Risk: An Alternative Approach for Managing Institutional Student Retention Performance retaining students, whereas an institution with a raw rate that is lower than its natural rate is evaluated as performing poorly. This approach has been implemented in the United States but not in Canada.
Three interpretation problems are ingrained in the natural rate approach that impede its meaningful application: normative interpretations given to natural rates are unwarranted; attributions of causation â€“ to students in the case of natural rates and to institutions in the case of differences between natural and raw rates â€“ are also unwarranted and potentially misleading; and a single set of system-wide coefficients is not likely to provide useful characterizations of the realities in play at individual institutions. A large and growing body of research embeds retention processes within the local context of individual institutions and indeed individual students. As research findings accumulate, there is a deeper and growing appreciation of the fact that the PSE system is not homogeneous in terms of the magnitude or direction of relationships between factors influencing retention event occurrence and the actual occurrence of those events. Rather, processes generating retention events operate locally and with considerable variation in form and intensity amongst locales, so system-wide characterizations do not give meaningful summaries of local conditions. The natural rate approach looks like a more sophisticated, finely tuned analysis, but its looks are deceiving.
An alternative to the raw and natural rate approaches is to move away from retrospective analyses of retention rates in favour of prospective analyses of retention risks. According to this approach, institutions use historical data to develop statistical models of retention risk at the individual student level. These models are then employed to estimate for each student in a currently enrolled cohort the â€œriskâ€ (expressed as a probability) of continuing with their studies beyond a certain length of time.