The document discusses an intervention called edu Intervention that aims to raise high school graduation rates by identifying students most at risk of leaving school early. It does this by using data from the National Center for Education Statistics tracking over 26,000 attributes of 30,000 students to determine factors correlated with leaving, such as poor grades, disliking school, and leaving to work. A logistic regression is used to calculate probabilities of students leaving school based on identifiable factors like absences, math scores, number of schools attended, suspensions, and skipping class. The model is validated as being highly effective at identifying at-risk students.

1. edu Intervention
Raising Graduate Rates Through Targeted Interventions
Kevin Mercurio
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2. High school completion is important, but still elusive
for some students
• 7% of students in American high schools leave without completing each year.
• Many excellent high school completion programs exist, but which students get this
opportunity?
• edu Intervention solves the selection problem by identifying which students are
most at risk.
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3. How can we identify at-risk students?
• The National Center for Education Statistics has multi-year, detailed studies of students
• Tracks ~2600 features of 30,000 students and their schools
• Students often describe their reasons for leaving as:
• Poor grades
• Dislike of school environment
• Leaving to work
• Determine which documented features are correlated with leaving school and address them
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4. How can we identify at-risk students?
Math Quintile Scores
Completes School
Does not Complete
1 2 3 4 5
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5. How can we identify at-risk students?
Number of Schools Attended
Completes School
Does not Complete
1 2 3 4
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6. Logistic Regression is Powerful and Clear
• A probability to leave school is
calculated using a logistic
regression, selecting
features that are identifiable
to administrators
birth year
absences
regression coefficients
math score
total schools
friend drops
suspensions
skipping class
• urban/rural, family size, race,
tardiness, and lack of homework
are all less important
• validation: 5-fold, mean area
under RoC curve is 0.93
soc. economic
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7. About me
Kevin Mercurio
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8. Thank you!
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9. Web backup
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10. Web backup
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11. Web backup
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