Enrolment and Portable Classrooms in Ontario Schools

 _{Principal Investigator} 

 _{Gus Riveros, PhD} 

 _{Research Assistants} 

 _{Sonia Zhou, Tina Liu, Diego Sornoza-Parrales, Nyasha Nyereyemhuka, Richard Oppong-Bosomah} 

Inputs-Based Perspective: A condition or situation that makes it possible to receive quality education. Equal access to educational resources including pre-conditions of learning E.g. facilities, resources, policies, programmes, structures, etc.

Outcomes-Based Perspective: The Coleman report (1966) showed that socio economic disparities have an effect on educational outcomes (e.g. achievement). ‘Opportunity’ must be understood in terms of the conditions or situations that affect the outcomes of education.

Educational opportunity is “productive” since early educational opportunities, are linked to future educational opportunities. e.g. opportunities to gain early literacy are connected to more complex learning opportunities in the future.

The chi square analysis established that there was a statistically significant relationship between school board size and school utilization rate. The Phi value of 0.2 (Φ = 0.26) shows a moderately strong relationship between school board size and school utilization rate.

The Chi Square test shows a statistically significant relationship between Utilization Rate and Portable use. X ²  (4, N = 1870) = 219.76, p = < .000  (<2.2e-16). This finding confirms the association between UR and portables suggesting that schools boards use portables as a response to high UR.

The Chi Square test shows a statistically significant relationship between Portable use and percentage of students in Low Income households. X ²  (4, N = 1432) = 16.079, p = < .00291. There seems to be an association between:

1. Schools that have more than 24% students living in low income households and schools with 1-5 portables
2. Schools with fewer than 13% students in low income households and schools that have between 6 and 11 portables
3. Schools that have between 13% and 24% low income students and schools that have more than 11 portables.
4. Also, the residuals indicate negative relations between low income and portable use in some categories. This could be explored in more detail with regression models.

Spatial clustering could offer statistically-supported indication that these variables are localized in specific geographic areas. Once evidence of spatial clustering is obtained, the next step is to explore these patterns through spatial analysis.

We wanted to confirm if there is a statistically significant relationship between Use of Portables, Low Income and Utilization Rates. A multiple regression model (Ordinary Least Squares) was used.

The overall regression was statistically significant at Adj. R2 = 0.34 p = < .000 (2.2e-16)

The predictor Low Income is significant at p = < .000 (1.22e-06)

Predictor Portables is significant at p = < .000 (2e-16)

It should be noted that the coefficient for Low Income is negative, which suggests that schools with higher levels of low income students tend to have lower utilization rates. This could be interpreted as a sign of declining enrolment in schools that serve a higher number of low income students.

While additional analysis is required to examine the residuals for the existence of other patterns, we believe this is a promising model.

Portables have become a generalized response to overcrowding issues in Ontario schools

Despite their temporary nature, they tend to stay for long periods of time

High utilization rates and use of portables seem more pronounced in urban areas, probably due to rapid urban development and suburbanization

There is a statistically significant relation between use of portables, income, and utilization rates

The next steps will include examining other variables in the dataset and mobilize findings with relevant stakeholders.