Conference on the First Year Experience San Francisco, Ca

1. The Equity Scorecard for the First College Year:Addressing Race-BasedDisparities in Student Outcomes Conference on the First Year Experience San Francisco, Ca Dr. Elsa Macias – Director of Research and Development Center for Urban Education, University of Southern California Dr. Greg Lampe – Interim Provost and Vice Chancellor University of Wisconsin Colleges Gregg Nettesheim – Institutional Researcher University of Wisconsin Colleges

2. The Equity Scorecard (EqS) • Tool for self-assessment of institutional performance • Data-informed discussion • Collective learning is evidence-based • Equity mindedness vs deficit thinking

3. Learning Goals of the EqS • Awareness of race-based inequities in educational outcomes; • Interpret disparities in academic outcomes through the lens of equity; • Inequities in outcomes is a problem of institutional performance:requires communal responsibility and action.

4. Why EqS in the First Year? • Fall term new freshman • Part-time (< 12 credits) • Under-prepared (graduated from high school in bottom half of class) • Traditional Age (< 22) • Non-white She has a 1 in 10 chance of returning next fall

5. The Equity Scorecard for the First College Year • A collaborative initiative • With support from the University of Wisconsin System

6. Institutional Change in the Equity Scorecard Project • Organizations change through individuals • who engage in organizational learning • and enable institutions to bring about equitable educational outcomes.

7. Access Measure Baseline Improvement Target Equity Retention and Persistence Equity in Educational Outcomes Institutional Receptivity Measure Measure Baseline Improvement Target Equity Baseline Improvement Target Equity Excellence Measure Baseline Improvement Target Equity The EqS Framework

8. The Eqs Evidence Team • Appointed by the President and senior leadership of each participating institution • Access to resources • Teams have support at all levels • Include a diverse group of campus members • Must include Institutional Researcher

9. How Does EqS Work?The Evidence Team as Practitioner-Researchers • Using only existing data: Disaggregate by race/ethnicity Pose questions about the data Observe inequities Collaborative Reflection on findings Gather more data and information Set goals to achieve equity

10. Engaging the EqS Process?The Importance of Cognitive Frames Guide our beliefs, actions, and sense making: • how we teach • our beliefs and assumptions about the way students learn • the ways in which we connect and interact with students • the assumptions we make about students based on race/ethnicity

11. The Cognitive Frames of Practitioner-Researchers Guide collaborative research: • What questions will be asked • What information will be collected • What gets noticed • What goes unnoticed

12. Cognitive Frames and EqS • Diversity • Focus on representation of differences in the student body (e.g., gender, race, ethnicity, sexual orientation, religion, etc.) • Emphasizes “access” and “representation” rather than “success” and “outcomes” • Deficit • Students are responsible for inequities in student outcomes • Programs that attempt to “fix” the student

13. Cognitive Frames and EqS • Equity • Awareness of inequities in educational outcomes • Inequities: result of history of exclusion, discrimination, “educational apartheid” • Unit of analysis: institution, not the student • Changing institutions, developing institutional responsibility • The benchmark for equity is white students

14. Data Gaps In Educational Outcomes Solutions (Best Practices) Data versus Inquiry The Data Paradigm: The Inquiry Paradigm: Evaluation of Implemented Solutions Informed Discussion Leads to Possible Solutions Data Gaps Inquiry into the Causes

15. The Data ParadigmA Comparative Example Data Gaps Solution Student Outcomes in Math Courses Black Students Experience Unequal Outcomes in Math Courses Create a Learning Community (Students’ Learning Problem)

16. The Data ParadigmA Comparative UW Colleges Example The Data Reveals Gaps D, F, W, I Rates by Course – Fall 2000 – Spring 2007 Create Learning Communities with Math 105 and Freshman Seminar Solution

17. The Inquiry ParadigmA Comparative Example Data Gaps Inquiry Solution • Math faculty members • use tools to identify • causes of inequities: • LASSI • Student Interviews • Cultural Audit • Study of Instructional • Practices • (Practitioners’ Learning • Problem) Solution addresses identified Cause/s Student Outcomes in Math Courses Black Students experience unequal outcomes in Math Courses Evaluation of Implemented Solution Evaluation

18. The Inquiry ParadigmA Comparative UW Colleges Example The Data Reveals Gaps D, F, W, I Rates by Course – Fall 2000 – Spring 2007 Inquiry Solution Evaluation of Implemented Solution (test again for gaps) • Faculty members seek causes of inequities: • Student Interviews • Curricular Review • Study of Instructional • Practices Changes to curriculum and instruction Evaluation

19. Questioning Your Knowledge and Assumptions “New students from the top half of their high school class are retained at a higher rate than those from the bottom half.” Retention to a 2nd Year Full-Time Traditional Age Students

20. EqS Indicators and the First Year Experience (FYE) Access • Students of color who apply, are admitted, and enroll • Students of color in majors, undeclared • Distribution of financial aid: balance of loans and scholarships

21. EqS Indicators and the FYE Access The UW Colleges High School Equity Enrollment Model

22. EqS Indicators and the FYE Retention and Persistence • Term-to-term and year-to-year retention rates of first-time students • Six-year graduation rates of first-time undergrad students • Success rates in gatekeeper courses: • Class drops, withdrawals, incompletes

23. EqS Indicators and the FYE Retention The UW Colleges Full-Time Retention Model • Create the same model for part-time students

24. EqS Indicators and the FYE Retention • Linking Retention to Student Success D, F, W, I Rates for Introductory History Courses - DFWI Rate exceeds 30%

25. EqS Indicators and the FYE Excellence • Academic performance (GPA): • Distribution in courses and majors • Excellence at degree completion • Study abroad • Dean’s Honor Roll • Student leadership activities

26. EqS Indicators and the FYE Excellence UW Colleges Students With a Cumulative GPA of 3.0 or Higher {enrolled 2 or more terms} {Non-Admissible indicatesstudent was not admissible at any other UW institution} • Linking Excellence to a mission of access

27. EqS Indicators and the FYE Institutional Receptivity • Faculty & staff of color • Hiring rates for faculty/staff applicants of color • Courses taught by faculty of color

28. EqS Indicators and the FYE Institutional Receptivity in the UW Colleges Interracial tensions in the classroom Scale:(1-Extremely), 2, 3, (4-Moderately),5, 6, (7-Not at all, NA) Tensions – To what degree is interracial tension in the classroom present at this college/university? Scale(1) Extremely, (2),(3),(4) Moderately,(5),(6),(7) Not at all, NA Source – Climate Survey – Educational Benchmarking, Inc. - Fall 2006

29. Outcomes and Actions • Institutional data is routinely disaggregated by race/ethnicity • Established equity benchmarks are regularly monitored • Equity is integrated into institutional processes: • strategic planning • leadership evaluation • curricular review • budget development • Equity is linked to delivery of the institutional mission

30. DATA vs KNOWLEDGE • Data [the Scorecard] alone will not bring about transformation of campuses. • The SENSEMAKING activities—the dialogue about the data—are a fundamental lever of organizational change. • The act of analyzing the data is itself the intervention tool – a catalyst for change

31. To Contact Us Elsa Macias eemacias@usc.edu Greg Lampe greg.lampe@uwc.edu Gregg Nettesheim gregg.nettesheim@uwc.edu