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Perkins V: Using Student Performance Data to Drive CTE Decisions

Wednesday, July 17, 2019

One of the goals of the Strengthening CTE for the 21st Century Act (Perkins V) is to ensure that local decisions about CTE programs are data-driven. Understandably then, reviewing student performance data is a key step in the comprehensive local needs assessment (CLNA), which must be done prior to starting the Perkins application.

The first step in examining data is to identify which data should be used. To get a clear picture, the data should be disaggregated, or broken out, by subgroup populations such as:

  • gender, race and ethnicity, and migrant status;
  • individuals with disabilities;
  • individuals from economically disadvantaged families, including low-income students;
  • individuals preparing for nontraditional occupations;
  • single parents;
  • English learners;
  • homeless individuals; and
  • students who are in or who have aged out of the foster care system.

By breaking out the information this way, and then breaking it out further by program or cluster, you’ll see which programs are thriving and which are not. This will give you an opportunity to explore the “why” behind the data.

As you get started, you’ll want to work with those responsible for data collection and record maintenance in your service area. They can provide longitudinal, disaggregated, program-level, and student-level data. Here are some of the sources you’ll want to tap into:

  • CTE district profile data (for overall district performance)
  • CTEERS files in the disaggregate: Composite Enrollment Report and Graduate Follow-up Report*
  • WISEdash for Districts: break out by subgroups, schools, or school years to identify trends
  • WISEdash Public Portal: summary-level data and trends
  • District and school report cards
  • ESSA Accountability Report
  • Any other local reports

How do you go about analyzing your data? First, ask data stewards to provide data in an easy-to-read format so that key trends stand out.

Second, create tables and graphs that compare each of the subgroup populations to its appropriate comparison group, disaggregated by program or cluster.

Third, examine data to identify significant differences in performance between subpopulations and across programs, noting areas of success and areas of concern, as well as trends in participation. This will put you in a better position to determine the underlying meaning, implications, and root causes of success as well as underperformance.

Once you’ve had a chance to digest the data, then supplemental surveys, interviews, and focus groups with different stakeholders can shed additional light on missed opportunities, potential strategies, and resources.

For more information and resources on reviewing student performance, refer to DPI’s Perkins V webpage for links to the Wisconsin Guide for Conducting the Comprehensive Local Needs Assessment as well as a webcast series on various Perkins V topics.

*Your district already has the raw data that will allow you to aggregate and disaggregate by CTE program, special population groups, and any other variables.

Mai Choua Thao—Submitted by Mai Choua Thao, CTE Data Consultant, Career and Technical Education, Wisconsin Department of Public Instruction