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Increasing Student Transition and Success:

Increasing Student Transition and Success:. Cal-PASS California Partnership for Achieving Student Success. A Matter of Misalignment. According to a recent report issued by the Stanford University Bridge Project:

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Increasing Student Transition and Success:

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  1. Increasing Student Transition and Success: Cal-PASS California Partnership for Achieving Student Success

  2. A Matter of Misalignment • According to a recent report issued by the Stanford University Bridge Project: • “…the coursework between high school and college is not connected; students graduate from high school under one set of standards and, three months later, are required to meet a whole new set of standards in college.”

  3. Troubling Indicators • - High HS drop-out rate • Up to 50% in large urban districts • - Poor transition rates from HS to college • - Significant remediation needs in higher education • Over 70% in Community Colleges • Almost 50% in California State Universities • Over 30% in University of California

  4. What is Cal-PASS? • Publicly funded initiative • Links primary, secondary and post-secondary institutions on a regional basis • Tracks students from one segment to the next • Engages faculty across segments in instructional conversations • Includes over 3,000 K-12 schools, community colleges, and universities throughout California

  5. Cal-PASS Principles • Collaboration • Discovery • Continuity/Alignment • Innovation • Evaluation • Expansion

  6. Making Cal-PASS Work: Intersegmental Professional Learning Councils • English • Mathematics • Counseling • EL • Tech Prep • Science

  7. Relation between last math passed at Alpha High School and first math attempted at Beta College Red = attempted class in college lower than that already passed in high school Gold = attempted class in college equal to that already passed in high school Green = attempted class in college higher than that already passed in high school

  8. Relation between last math passed at Alpha High School and success in first math attempted at Beta College Red = attempted class in college lower than that already passed in high school Gold = attempted class in college equal to that already passed in high school Green = attempted class in college higher than that already passed in high school

  9. Relationship between sequence in which math courses were taken in high school and the level of the first math class attempted at a local community college Red = attempted class in college lower than that already passed in high school Gold = attempted class in college equal to that already passed in high school Green = attempted class in college higher than that already passed in high school

  10. Success* in First Community College Math Course after Successfully Completing High School Math by Senior Math Status

  11. Relationship between the last English class passed at Alpha High School and the first English class attempted at Beta College

  12. Success in a Community College Biology Course by Highest Level of English Completed in High School

  13. Misclassification Rate = 35%

  14. Transition pathways from last community college math at nearby feeder colleges to first math at the local CSU campus (STEM = Science, technology, engineering, math)

  15. Exploratory Analysis on Science, Technology, Engineering, and Math (STEM) Pathways from Community College to University • Use classification and regression tree (CART) to predict degree based upon: • Highest level math completed at community college • Number of classes passed and units earned at a CC in • Biology, • Chemistry, • Physics, • Mathematics • Financial aid, time at CC, time at university, time to degree, zip code • Whether student had same major in first and last university term • Ethnicity, gender, age, disability status

  16. Using CART to Predict Degree • Highest level math completed at community college (available for n=2,764) correctly predicted 49% of balanced sample compared to 33% with random guess • Using all variables correctly predicted 76% of balanced sample compared to 33% with random guess • Using all variables correctly predicted 90% of total sample compared to 88% for guessing “other” for all degrees

  17. Model using CART on balanced sample • Last Math <= 7 • Units Bio <= 7.500 • Units Health <= 0.750 • Chem courses <= 0.500  Other Degree (1,019; 0.755) • Chem courses > 0.500 • Last math <= 6  Health Degree (154; 0.442) • Last math >= 7  STEM Degree (52; 0.538) • Units Health > 0.750 • Time between CC and Univ <= -1.875  STEM Degree (50; 0.46) • Time between CC and Univ > -1.875  Health Degree (126; 0.833) • Units Bio > 7.500 • Time to degree <= 1.562  STEM Degree (37; 0.892) • Time to degree > 1.562  Health Degree (687; 0.846) • Last Math >= 8 • Health courses <= 0.500  STEM Degree (634; 0.852) • Health courses > 0.500  Health Degree (60; 0.5)

  18. How to Contact Us • Terrence Willett • Director of Research • twillett@calpass.org • (831) 277-2690 • Nathan Pellegrin • Research Analyst • npellegrin@calpass.org • (619) 933-3973 • Eden Dahlstrom • Assistant Director of Regional Collaboration/Research Analyst • edahlstrom@calpass.org • (530) 204-7129 • www.calpass.org

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