1. Chancellor’s Office Data Resources for Student Success October 7, 2015
Ryan Fuller, Research Specialist, Research, Analysis and Accountability, California Community Colleges Chancellor’s Office   Tom Leigh, Research Specialist, Research, Analysis and Accountability, California Community Colleges Chancellor’s Office

2. Datamart http://datamart.cccco.edu/

4. What’s in Datamart
Student Counts/Enrollments (by gender, age, ethnicity)
Headcount
Enrollment Status
FTES
Unit load
Education status
Citizenship status
Distance Education

5. What’s in Datamart Outcomes Retention/Success
Awards (degree/certificates)
Grade distribution
Basic Skills completion
Earnings (salary surfer)
Student Success Scorecard metrics
Transfers (public & private)

6. What’s in Datamart Courses Credit & Non-credit sections
Basic Skills sections
Course details
Academic Calendar

7. What’s in Datamart Student Services Financial Aid Matriculation
Special Population data (Foster Youth, First Generation etc.)
DSPS
CalWorks
EOPS
Assessment types

8. What’s in Datamart
Faculty & Staff
Demographic reports

9. Disproportionate Impact
Disproportionate impact occurs when “the percentage of persons from a particular racial, ethnic, gender, age or disability group who are directed to a particular service or placement based on an assessment instrument, method, or procedure is significantly different from the representation of that group in the population of persons being assessed, and that discrepancy is not justified by empirical evidence demonstrating that the assessment instrument, method or procedure is a valid and reliable predictor of performance in the relevant educational setting.” [Title 5 Section 55502(d)]

10. 80 % Rule Gap Analysis Proportionality
Measuring Disproportionate Impact:
80 % Rule
Gap Analysis
Proportionality
Outlined in detail in the 2015 Student Equity Plan Template

12. Table 1. 2008-09 Cohort Six-Year Transfer Rate Ethnicity Cohort
Count
Percent
African-American
7,490
6.06
2,566
5.51
American Indian/Alaskan Native
1,079
0.87
314
0.67
Asian
21,674
17.54
10,765
23.10
Hispanic
43,329
35.06
12,662
27.17
Multi-Ethnicity 29
0.02 12
0.03
Pacific Islander
1,303
1.05
452
0.97
White
48,671
39.39
19,828
42.55
Smaller sample sizes less reliable. Do not analyze for samples less than ten.

13. 80% Rule
The methodology is based on the Equal Employment Opportunity Commission (EEOC) 80% Rule, outlined in the 1978 Uniform Guidelines on Employee Selection Procedures, and was use in Title VII enforcement by the U.S. Equal Opportunity Commission, Department of Labor, and the Department of Justice.

14. 80% Rule
The 80% Rule methodology compares the percentage of each disaggregated subgroup attaining an outcome to the percentage attained by a reference subgroup.
Any disaggregated group that is included in a desired outcome at less than 80% when compared to a reference group is considered to have suffered an adverse – or disproportionate - impact.

15. American Indian/Alaskan Native 1,079 314 0.29 0.59 Asian 21,674 10,765
Table % Rule With Highest Performing Reference Group By Ethnicity
Ethnicity
Cohort
Transfer
Percent Transfer
80 Percent Index
African-American
7,490
2,566
0.34
0.69
American Indian/Alaskan Native
1,079
314
0.29
0.59
Asian
21,674
10,765
0.50
1.00
Hispanic
43,329
12,662
Multi-Ethnicity 29 12
0.41
0.83
Pacific Islander
1,303
452
0.35
0.70
White
48,671
19,828
0.82
Statewide
123,575
46,599
0.38
Sometimes difficult to select the best reference group.

16. Table 2. 80 % Rule With Largest Reference Group By Ethnicity Ethnicity
Cohort
Transfer
Percent Transfer
80 Percent Index
African-American
7,490
2,566
0.34
0.84
American Indian/Alaskan Native
1,079
314
0.29
0.71
Asian
21,674
10,765
0.50
1.22
Hispanic
43,329
12,662
0.72
Multi-Ethnicity 29 12
0.41
1.02
Pacific Islander
1,303
452
0.35
0.85
White
48,671
19,828
1.00
Statewide
123,575
46,599
0.38
Problematic if one disaggregated subgroup comprises a large portion of the sample.

17. Table 2. 80 % Rule With Statewide Reference Group By Ethnicity
Cohort
Transfer
Percent Transfer
80 Percent Index
African-American
7,490
2,566
0.34
0.91
American Indian/Alaskan Native
1,079
314
0.29
0.77
Asian
21,674
10,765
0.50
1.32
Hispanic
43,329
12,662
Multi-Ethnicity 29 12
0.41
1.10
Pacific Islander
1,303
452
0.35
0.92
White
48,671
19,828
1.08
Statewide
123,575
46,599
0.38
1.00
Sometimes use overall rate as reference group. (Produces the same values as proportionality.)

18. Gap Analysis
The percentage point gap methodology compares the percent of students in a disaggregated subgroup who succeed in an outcome with the percent of all students who succeed in the same outcome.
Percentage point gap measurements are calculated by subtracting the all student success rate from the success rate of a disaggregated subgroup in the same outcome. According to this methodology, a ‘-3 percentage point gap or greater’ is evidence of a disproportionate impact.

19. Table 3. Percentage Point Gap By Ethnicity Ethnicity Cohort Transfer
Percent Transferred
Gap
African-American
7,490
2,566
0.34
-0.03
American Indian/Alaskan Native
1,079
314
0.29
-0.09
Asian
21,674
10,765
0.50
0.12
Hispanic
43,329
12,662
-0.08
Multi-Ethnicity 29 12
0.41
0.04
Pacific Islander
1,303
452
0.35
White
48,671
19,828
0.03
Statewide
123,575
46,599
0.38
Imperial Hispanic 89.54%

20. Proportionality Index
The proportionality index reflects differences in percentages for race/ethnicity subgroups between two conditions (milestones or group inclusion).
The formula for proportionality is the percentage in the outcome group divided by the percentage in the original cohort (outcome percentage/cohort percentage).

21. Proportionality Index
Interpretation
1.0
Proportions of subgroups are equal.
Less Than 1.0
Subgroup is less prevalent in the outcome group.
More Than 1.0
Subgroup is more prevalent in the outcome group.
Bensimon and Malcom-Piqueux (2014) specified a cutoff of 0.85 to identify performance below equity when proportionality is used as a performance measure.

22. Table 4. Transfer Proportionality By Ethnicity
Cohort
Transfer
Proportionality
Count
Percent
African-American
7,490
6.06
2,566
5.51
0.91
American Indian/Alaskan Native
1,079
0.87
314
0.67
0.77
Asian
21,674
17.54
10,765
23.10
1.32
Hispanic
43,329
35.06
12,662
27.17
Multi-Ethnicity 29
0.02 12
0.03
1.10
Pacific Islander
1,303
1.05
452
0.97
0.92
White Non-Hispanic
48,671
39.39
19,828
42.55
1.08
Statewide
123,575
100.00
46,599

23. REFERENCES
Bensimon, E.M., & Malcom-Piquex, L. (2014, March). Assessing Hispanic-Servingness at HSIs. Presented at The Academic Success of Hispanics Conference, American Association of Hispanics in Higher Education.