Fiona Deller and Martin Hicks — Spoiler alert: It’s the Ontario Education Number
With Thursday’s unveiling of the 2017 provincial budget, we’re reminded that last year’s budget included an announcement (with great fanfare) of reforms to the Ontario Student Assistance Program, or OSAP. Those reforms were designed to encourage and support more low-income youth to attend postsecondary education, and, as HEQCO has said before, that’s a really great idea!
However, to know if the reforms are working, we need to know more about low-income youth and how they access — or don’t — higher education in Ontario. We will need to measure low-income participation rates over time to see whether the OSAP changes are making a difference.
Statistics Canada recently released a report by Marc Frenette that helps. He mined tax files, Canada’s best source of income information. First, by using data on education tax credits, he created a multi-year sample of 19-year-olds who participated in higher education. Then he captured the students’ family incomes and compared those to the general population’s income distribution. He found that participation rates are on the rise, both globally and for the lowest income quintile of Canadian families.
This is a start. Using education tax credits is probably as good as it gets right now. But like any approach, it has its limitations. Say you want to know where low-income students go to study, what programs they take, and whether they graduate. Or say you want to know what characteristics other than income contribute to higher or lower participation rates, whether interventions as far back as grade school have an impact on participation in higher education 15 years down the road, and what difference accessing OSAP makes. None of these things can be tracked through tax files alone.
But there is a way. There are all manner of administrative data collected within the Ontario school system and within its higher education system that can reveal important stories about where barriers exist and how they can be eliminated, what works and what doesn’t. And if we could link these data together and then link them to the tax data on incomes as Marc Frenette has done, we could multiply our understanding of how and who is helped by OSAP reform, what the resultant impact on participation rates by income is, and what kinds of return on investment individuals and governments can realize.
If only there were some sort of tool that allowed us to track students in Ontario from high school into PSE and link to all these databases. If only there were some way of knowing if an increasing number of low-income students were making it into PSE as a result of OSAP and other policy and program changes.
Of course, if you have been following us, you already know the punchline: it’s the Ontario Education Number. Please, let’s use it. Let the research community look at participation rates, demographic trends, and the implications of policy and program changes. The more open we are with our data, the better a conversation we will be able to have about what works and what doesn’t in supporting our students.
We know there are privacy concerns. They are legitimate but they can be accommodated. The governments of British Columbia and Alberta have managed to find a way. These provinces both use a unique identifier that tracks learners’ educational progress so that governments and policy makers can make decisions that serve students best. Those would be evidence-based decisions, the basis of all effective public policy.
We all want more equitable access for Ontario’s youth. But how on earth will we know how far away we are from reaching that goal and whether anything we are doing is affecting that course unless we know more about Ontario students.
Right now we are just yelling policy and program ideas into a black hole of assumptions and good intentions. Let’s actually shed some light on the process. It would really be remarkably easy.
Fiona Deller is HEQCO’s senior executive director of research and policy. Martin Hicks is HEQCO’s executive director of data and statistics.