Canadian College Student Attrition for Student Aid Receivers By: Paul J. Madgett University of Ottawa

Policy Reasons Manufacturing disappearing  Strong $CND weak $USD  75% Exports to US Federal Government Policy - Innovation  Increase Highly Skilled People (HQP)  Options 1) increase skilled immigration 2) recognize foreign credentials 3) more financial assistance

Evolution of Colleges Applied Degrees in Ontario and Alberta 150 Community Colleges in Canada  Mostly Public Joining fields dealing with applied research  Skill sets with tech transfer etc. Issues  Student affairs research and infrastructure Lacking

Canadian HE System Universities dominate the system  90+ institutions  Mission creep – college become universities  Prestige issues Community Colleges  colleges  Can/have reached into rural and northern communities  Need more research infrastructure on student attrition

Reason No in depth studies performed  Community Colleges Wanted to verify some theories  Tinto’s  Canada and United States Attrition rate 20%-25%  Next Step Looking at Student Engagement Few Canadian publications on student retention  Mostly institutional

Benefits of retention Public and private benefits  Economic costs  Implicit and Explicit to individual, society etc. Lost of operating funds institution  Approximately 65% funded by government  35% by tuition

What do we know? Some of my earlier studies Other datasets and research  Canadian Millennium Scholarship Foundation  Canadian College Student Financial Survey  Year 2006  99 variables and 7438 respondents Youth in Transition Survey  A few studies

Significant Variables - Canadian College Student Financial Survey Significant Predictors  financial resources and academic background region; highest grade done before starting program; currently attending college FT/PT, delay enrolling in current program because of money, ever had to reduce courses because of lack money; how much money from: academic scholarships, cost of tuition for current year of study; and, how much money in average month: personal expenses.

Student Leavers Reasons# of Students% Insufficient funds % Time conflict with work % Conflict with family/personal % Academic difficulties2129.7% Changed Program % Moved1255.7% No Social Support713.2% Other % No Response50.2% %

Dataset MESA survey of low-income students (cost $5m)  Data collected every year for 3 years Traditional aged Canadian Community College students (18-22)  Not including second degree students Student receiving federal and provincial support  Millennium Scholarship and Provincial counterpart  3717 College students  Variables Based of Stats Canada – YITS

Quantitative Methods Binomial logistic regression Model 1  47 variables Sample Size  3717  0 (attrition), 1 (retention) Final model  8 Significant Variables

Limitations Complexity of the dataset  Two datasets (900+ variables)  respondents Student information Administrative information Specific Sample Lack of details on some of the variables

Goals and Objectives 1. What are the effects of the student’s academic, social background and demographic variables? Are there differences amongst provinces, ethnic background, parental education, high school grades, parental and family perception etc.? 2. What academic factors affect retention, academic programs, time spent in class, perception of learning environment, self- efficacy, grades, etc?

Descriptive Statistics

Objective #1 – background, personal and family perceptions of PSE Found 3 significant variables at 95%  Ethnicity  Dwelling  Average grade of last year of high school

Objective # 2 – College academic Found 5 Significant Variables at 95%  First year PSE grades  Friends for help and support at College  Helps with future plans  Correct Program for me  I Do Well In My Courses Given The Amount Of Time I Dedicate To My Studying.

Conclusion: Further analysis of the variables included Other Statistical Methods need to be applied Some finding are similar to the national study of Madgett and Belanger for University students Further contrast between learning types  Use Kuh’s conceptual model for student learning In the future look at the number of university graduates taken college degrees