academic success factors in k-12 education (a quantitative ...prior research • as the gap between...
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Academic Success Factors in K-12 Education (A Quantitative Analysis)Brianna Chew, UC Riverside
Prior Research• As the gap between rich and poor grows, so does the gap between high and low
performing students• Family structures, such as single parent households, influence how students
perform • Encouraging students to read outside of school and participate in the arts effect
reading and math test scores
Problem• The academic achievement gap continues to grow each year• Lower performing students are less likely to attend college• Adults with no college degree tend to not make as much income to support their
family What demographic and socioeconomic
factors affect student success?
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Measuring Academic Success
Literature Review• Students’ academic success can be measured by SAT
results
• 3-hour long, standardized exam is divided into three subjects - math, reading, and writing.
• SAT predicts college readiness and academic achievement equally amongst all ethnicities
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Hypothesis
• Demographic factors may be correlated to SAT scores
Sample & Methods
• Sample size, n=1,070
• Hotspot Analysis• Logistic Regression• Data Visualization
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Tapestry Segmentation
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Top 3 Schools
Monta Vista High SchoolSanta Clara CountyAverage SAT Score: 2043Percent of Students Scored Above 1500: 75.1%
Mission San Jose High SchoolAlameda CountyAverage SAT Score: 2039Percent of Students Scored Above 1500: 79.8%
Saratoga High SchoolSanta Clara CountyAverage SAT Score: 2009Percent of Students Scored Above 1500: 76.8%
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Centennial High SchoolLos Angeles CountyAverage SAT Score: 1079Percent of Students Scored Above 1500: 1.9%
Fremont High SchoolAlameda CountyAverage SAT Score 1080Percent of Students Scored Above 1500: 0.75%
Roosevelt High SchoolFresno CountyAverage SAT Score: 1115Percent of Students Scored Above 1500: 2.7%
Bottom 3 Schools
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Sample 8
Hotspot Analysis 9
Logistic Regression
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Sample Division
Training Set Validation Set749 Schools 321 Schools
n = 1,070
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Demographic and Socioeconomic VariablesHousehold Spending Potential Indexes• Education Annually• Test Prep & Tutoring Services• Health Insurance• Alcoholic Beverages• Online Entertainment/Games• Books• Cable and Satellite TV Services• Pets• Musical Instruments & Accessories• Elementary/HS School Books/Supplies• School Meals• Social/Recreation/Civic Clubs Member Fee
Demographic Variables• Household Size• Husband-wife Families• Multigenerational Households• Population aged 5-17 who speak Spanish/No English• Diversity Index• Single Father Households with Kids• Single Mother Household with Kids
Socioeconomic Variables• Household Income• Households with Income Below
Poverty Level• Education Attainment: Bachelor's
Degree
1-mile radius ring
Businesses• Number of Educational Services
(NAICS)• Number of Occupations:
Education/Library
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Classification Model
Term Estimate Std Error ChiSquare Prob>ChiSqIntercept 4.48566838 0.9880703 20.61 <.0001*
x1 2017 Average Household Size -0.8208772 0.3628465 5.12 0.0237*x2 Online Entertainment/Games:Ind 0.04542688 0.0202414 5.04 0.0248*
x3 Musical Instruments & Acc:Ind -0.0645742 0.032116 4.04 0.0444*x4 2010 Multigenerational HHs -0.0026234 0.0008054 10.61 0.0011*x5 2017 Education: Bachelor's Degree -0.0005044 7.8779e-5 41.00 <.0001*x6 Social/Recreation/Civic Clubs Member Fee:Ind 0.04725331 0.0165337 8.17 0.0043*x7 2010 Husband-wife Fam: Own Kids <18 0.00177097 0.0003402 27.10 <.0001*x8 Educational Services - Businesses (NAICS) 0.03179732 0.0096527 10.85 0.0010*x9 ACS Pop 5-17 speak Span/No English -0.0178355 0.0087682 4.14 0.0419*x10 2017 Diversity Index -0.0817789 0.0119845 46.56 <.0001*
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Confusion Matrix
Accuracy Rate: 84%Misclassification Rate: 16%
Actual Predicted Count
BINARY RESULT 1 0
1 237/286 = 0.83 70/463 = 0.15
0 49/286 = 0.17 393/463 = 0.85
Validation Datan = 321
Training Datan = 749
Actual Predicted Count
BINARY RESULT 1 0
1 97/131 = 0.74 31/190 = 0.16
0 34/131 = 0.26 159/190 = 0.84
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ROC CurveReceiver Operating Characteristics
Validation SetReceiver Operating Characteristics
Training Set
BINARY RESULT Area
1 0.9129
0 0.9129
BINARY RESULT Area
1 0.8907
0 0.890715
SAT Scores vs.
Income
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SAT Scores vs.
Bachelor’s Degrees
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SAT Scores vs.
Educational Businesses
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SAT Scores vs.
Multigenerational Households
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SAT Scores vs.
Diversity Index
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ConclusionVariables that affect SAT scores are:
Multigenerational Households
Husband-Wife Households
Parental Education
Diversity Index
IncomeEducational Businesses
and ServicesSocial/Rec./Club
Membership Fees
Online Entertainment
Games
Musical Instruments
Language Barriers
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My Interpretation
What can we do now?
• Be more proactive about helping students earlier in their academic careers
• Create and fund programs to help students perform better on exams and academics in general, specifically in the lower socioeconomic areas
• Build a stronger connection between college campuses and high schools
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Acknowledgements
Thank you to both my faculty mentors, Professor Asish Satpathy
and Associate Dean Elaine Wong,
from the UCR School of Business for advising me throughout this project.
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