Scorecard Update Salary Surfer/Wage Tracker Alice van Ommeren Ryan Fuller Research, Analysis and Accountability

Updates on the Scorecard April was the release of the Scorecard Scorecard metrics now on the DataMart – Calculate rates by district – Allows for multiple crosstabs (demographics) – Disabled Students Programs & Services (DSPS) & Economically Disadvantaged Status System Level Report to BOG in September Scorecard Advisory Group reconvenes in the fall

Cohort Challenges for CTE Metric Identifying a CTE /Vocational student – Student stated goal is not valid – Difficult to determine student behavior Defining success/completion – 1-2 vocational courses, leave college – Not capturing employment/licensing Students not tied to Programs

CTE Rate: The Cohort Cohort (denominator, SSN students) – First-time in CTE course defines cohort – Completed greater than 8 units in 3 years in a single discipline of vocational/technical courses (2-TOP) – At least one of the courses coded as Sam B or C

CTE Rate: The Outcomes Outcomes (numerator) within 6 years – Certificates 12+ units (CO approved) – Associate of Arts/Sciences – Transfer – Transfer Prepared

CTE Rate by Demographics Filipino and Asians have the highest CTE rate, and African Americans the lowest CTE Rate is higher for females than for males Compared to other age groups, 24 year olds and younger have the highest CTE Rate Economically disadvantaged have slightly higher rates, also those receiving disability services

CTE Rates by Special Populations to to to to to Economically Disadvantaged Disabled Student Program Services

CTE Rates and Outcomes Distribution of Outcomes in CTE Rate – Certificates (17%) – Associate of Arts/Sciences (28%) 22% of the students have just this one outcome – Transfer (16%) – Transfer Prepared (39%) 25% of the students have just this one outcome

Limitations of the CTE Rate Based on behavioral intent, not on students declared or stated goal The rate has been developed and has face validity, need to determine construct validity Besides concentrators, not able to analyze at the program level Does not capture CTE Skills Upgrade students

We are working on… Continue (construct) validating the metric Analyze the rates by discipline focus Regional/colleges differences among rates Include apprenticeship data as an outcome – Department of Apprenticeship Standards Linking to wage data, including NCIS codes Develop a “Skills Builder" metric for CTE

Salary Surfer and Wage Tracker Tools on Datamart

Methodology Two different methodologies – System wages for award completers – College wages for award completers Award completer data joined with EDDUI wage data. Both wage methodologies break out by award discipline (6-digit TOP code) and award type.

System Wage Tracker (Salary Surfer) Award completers over 5 academic years, exclude: – Enrolled anywhere in higher education after award – 21 and under at time of award Join with EDDUI (Unemployment Insurance) wage file Sum all quarters of wages to student annual wage All wages inflation adjusted using California CPI-U Calculate median wages by discipline and award type Median calculated for students with wages 2 years before award, 2 years after and 5 years after award

College Wage Tracker (DataMart) Same methodology as system wages, except: – Series of 8 years of award completers (to increase the number of students in the cohorts) – Median calculated for students in cohort with wages 3 years after award Calculate median wages by “college,” discipline and award type Includes locally approved certificates and the count of students matched

System vs. College Methodology College System

Data Caveats EDDUI Data contains wages of occupations covered by CA Unemployment Insurance Excludes military, federal government, self- employed, out of state and unemployed No way of determining part time or full time wages. Hours worked not in the EDDUI data. Only students with SSNs Wages are adjusted for inflation to current dollars using the California CPI-U

Analysis Caveats Region/locale significantly impacts wages, so caution in comparing earnings across the state Wages are not necessarily from employment associated with a particular award discipline Wage outcomes should not be a sole measure of institutional effectiveness/program quality Other factors besides earnings motivate students to earn an award in a specific discipline

Accessing Tools and Resources Query modules using both methods are available in Datamart – System Wage Tracker & College Wage Tracker Salary Surfer is the same as System Wage Tracker and available at salarysurfer.cccco.edu Additional wage resources on our webpagewebpage Median wages by program code are available for colleges in Data-on-Demand

College Wages by Program Available on Data-on-Demand (password) College Wages for Awards by Program Code (SP04) instead of TOP Code (SP01) Select award year and shows the individual years, between 2 years before and 5 years after Wages are not adjusted for inflation No cell suppression, so able to see more wages Includes median wages and associated counts