Transfer Pathways among Ontario Colleges and Universities

Authors
D. Zarifa
Y. Sano
C. Hillier
Reference Number
2021-03
Date
Status
Abstract

The Regional Dimensions of Transfer in Ontario: A Brief Introduction to the Zarifa et al. Reports

by Roger Pizarro Milian, ONCAT
 
Researchers have repeatedly found that geography shapes educational decision-making. All other things being equal, students who live closer to colleges and universities[1], or specific educational/training programs[2], are more likely to enroll in them. This phenomenon is known as “distance deterrence” within academic circles. In Ontario, this dynamic leads to significant regional disparities both north/south and rural/urban in educational attainment and skills development.[3] This, in turn, generates impediments for the economic development of northern and rural regions, with employers often struggling to find the requisite human capital to grow their enterprises.
 
Despite the well-known impact of geography on student decision-making, as well as its effects on “downstream” labour market processes (e.g., human capital scarcity), there’s been little effort to examine the intersections of geography and transfer in Ontario. There are a few reasons to expect regional variance in the likelihood of students transferring across Ontario:
 
  1. Unequal Distance Deterrence. There’s greater geographical dispersion of colleges and universities across the vast provincial north.[4] A student residing in the Greater Toronto Area has many local college and university options should they wish to transfer. A move from Ryerson to OCAD, or George Brown to the University of Toronto, entails only a relatively minor adjustment to a student’s TTC ride. However, for northern students, transferring may require a residential move to a community many hours away, from North Bay to Sault St. Marie or Timmins. This added distance could serve as a strong deterrent to transferring, forcing students to complete their programs in the same college or university they started in, or to drop out altogether.
     
  2. Socio-Economic Effects. It is well-known that educational attainment in northern and rural communities typically lags behind southern/urban regions a disparity exacerbated by the constant rural-brain drain that has been discussed in many empirical studies (e.g., Hillier et al., 2020). Beyond its impact on local economies, this disparity means that northern students and their families may not possess as much experience with (or knowledge of) technical PSE processes[5], including transfer. They may also lack the ability to effectively navigate the many bureaucratic structures (e.g., advising offices) in place to make such information accessible. This could prevent them from executing successful transitions into programs or schools that are better aligned with their interests.
Research on regional patterns in transfer has not progressed in Ontario in recent years primarily due to the absence of a data source that can support such analysis. As mentioned in other ONCAT reports (e.g., Davies & Pizarro Milian, 2020), popular national datasets do not support more detailed analyses of student mobility within specific provinces for various reasons. However, the recent development of Statistics Canada’s Education and Labour Market Longitudinal Linkage Platform (ELMLP), and improvements in the quality of the Postsecondary Students Information System (PSIS) within Ontario, has provided an opportunity to perform such type of research within our province.
 
Last spring, ONCAT engaged Dr. David Zarifa, Canada Research Chair in Life Course Transitions in Northern and Rural Communities at Nipissing University, and his team (Dr. Yuji Sano and Dr. Cathlene Hillier) to utilize the PSIS and available linkages to the T1 Family File through the ELMLP for the purposes of examining regional differences in transfer activity. After much hard work, and numerous unexpected delays with the closure of Statistics Research Data Centers due to COVID-19, the initial results of this work are finally being released through a set of research reports:
 
  • Transfer Pathways among Ontario Colleges and Universities: The Magnitude of Post-secondary Transfer Pathways among Ontario Colleges and Universities
  • Transfer Pathways among Ontario Colleges and Universities: Northern and Southern Differences in Students Who Transfer
  • Transfer Pathways among Ontario Colleges and Universities: Characteristics of Students Who Transfer Across and Within Regions
Through this initial brief, we provide a high-level overview of the findings of these three reports, and invite readers to dive into the full documents for additional details if they are so inclined.
 
The first report begins by providing an overview of student mobility across the province, capturing the magnitude of flows across seven pathways through our PSE system within students’ first two years of study, including both direct entry and persistence within college and universities, intra- (e.g., C-to-C, U-to-U) and inter-sectoral movements (e.g., C-to-U, U-to-C), as well as “swirl.” Nearly eight percent of all students in Ontario’s postsecondary system moved across or within sectors within two years of starting their programs. The report then goes on to statistically model the likelihood a student will travel each pathway using multivariate techniques. Dr. Zarifa’s work here finds that, compared to counterparts from southern Ontario, students from northern Ontario are more likely to engage in university-to-university transfer. However, they are less likely to engage in college-to-university or college-to-college transfer. These patterns remain even after controlling for an array of other factors, such as age, sex, parental income, registration status (FT/PT), field of study, family composition and size, and year of enrollment.
 
The second report is differentiated from the first in that it separately models the correlates of transfer pathways for students who begin their PSE at northern and southern colleges and universities. This allows us to observe various differences in what factors predict transfer among these different populations. With respect to gender, for example, it finds that females in the southern part of the province are more prone to traveling four (U-to-U, C-to-U, C-to-C, and swirl) of the five available transfer routes. However, in the provincial north, it is males who exhibit greater odds of taking all five transfer pathways. Notable consistencies are also found, with students in both regions with lower parental income being more likely to travel various transfer pathways (C-to-U, C-to-C, swirl). These, along with other age and program-based differences, illustrate the complex web of factors that promote transfer behaviour across geographical regions.
 
The third report brings regional migration into the mix, examining the correlates of transferring within or across provincial regions, relative to remaining at one institution. This, of course, is an issue of great interest to various stakeholders given that out-transfer from northern colleges and universities (north to south) serves as a potential mechanism through which talent could be drained from the region. Descriptive statistics from this report show that transferring out of the region is far more common among northern students, with southern students primarily transferring within region. In terms of predictors, it is found that older southern students are more prone to transferring across regions, while in Northern Ontario, it is younger students who are more likely to transfer across regions. Notable differences are also identified between part-time and full-time students. In the south, part-time students are more likely to transfer both within the region and across the region. Meanwhile, in Northern Ontario, part-time students are only significantly more likely to transfer across regions. In each region studied, college students are also more likely to transfer within and across regions. An array of program/discipline effects are also identified.
 
For us at ONCAT, this is the first time that we have been presented with systematic knowledge about the regional dimensions of transfer in Ontario. Indeed, we must confess we are unaware of any other regional analysis of this type done in other provinces using the PSIS. The produced findings, though certainly eye-opening, are raising far more questions among our team than they are answering. In particular, given ONCAT’s mandate to promote and fund articulation, we wonder: do observed patterns mirror the availability of articulated pathways across our PSE system? Perhaps students are simply traveling “paths of least resistance” when it comes to making switches across institutions. Linking available ONTransfer.ca data on articulated pathways and course equivalencies between Ontario colleges and universities could allow for an analysis of this topic. This work could help us to understand the influence of structured pathways on student mobility, especially for pathways established during the last decade. More broadly, we also wonder about the causal mechanisms behind observed trends. Are students adjusting their educational pathways after obtaining more knowledge of the available labour market opportunities in their region? This is a question that we could get at through more in-depth qualitative analysis of the decision-making processes of transfer students. Or, perhaps, we could derive this information from highly-targeted surveying of recent transfer students.
 
We look forward to the many conversations that these reports will spark across our sectors, among administrators, researchers and practitioners alike. As always, ONCAT remains receptive to research proposals that build on or complement existing reports.
 

[1] For Canadian research on this topic, see Frenette (2004; 2006), Newbold & Brown (2015) and Zarifa, Hango & Pizarro Milian (2018). For European work, see Spiess & Wrohlich (2010), Gibbons & Vignoles, (2012), and Sa, Florax, & Rietveld (2004).
 
[2] For Canadian work on this topic, see Hango, Zarifa, & Pizarro Milian (2019). International work can be found here (Bertrand-Cloodt et al., 2010; Suhonen, 2014).
 
[3] See Zarifa, Seward & Pizarro Milian (2019).
 
[4] For a more detailed discussion of this, see Pizarro Milian, Zarifa & Seward (2020).
 
 
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