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According to the research . . .

Improving Data Quality: Tech Prep Consortia Meet the Challenge Catherine Kirby, University of Illinois at Urbana-Champaign Virginia Johnson, Sauk Valley Community College Sharon Kennedy, Moraine Valley Community College Connections Conference: March 13-14, 2007.

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According to the research . . .

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  1. Improving Data Quality: Tech Prep Consortia Meet the ChallengeCatherine Kirby, University of Illinois at Urbana-Champaign Virginia Johnson, Sauk Valley Community CollegeSharon Kennedy, Moraine Valley Community College Connections Conference: March 13-14, 2007

  2. The “sheer volume of dissonant statistics” . . . demands colleges “fortify their institutional research capacities.”~ Cliff Adelman. “The Toolbox Revisited: Paths to Degree Completion from High School to College.” (2006).

  3. According to the research . . . • Successful data tracking . . . • Can be aided by the creation of a data warehouse • Involves a high degree of interagency collaboration • Often results in the creation of contracts among partners providing the data • Places a high priority on insuring privacy • Is aided by the establishment of cohorts • Relates data to instructional and program improvement – the feedback loop so often ignored!

  4. Data accountability and Tech Prep . . . • Perkins IV calls for higher degrees of accountability • And “statewide systems of measurements and standards” • Illinois’ consortia data are improving • Trend reports of Illinois consortia demonstrate gradual increases in reliability over six years • Some consortia are still not able to provide accurate or reliable data • Improved data tracking was cited as 1 of 3 strategic issues for FY07 • A data mapping project ensued and is currently underway; limited early findings are reported here

  5. OCCRL Data Mapping Project Goals • Determine data currently transmitted • Determine overall pathway/structure • Determine factors that enable & hamper . . . • Determine specific data that are difficult to track from secondary to postsecondary • Determine if and how data outcomes are used within the consortia

  6. Early Findings • Factors that enable data sharing and/or reliability include • Frequent and collegial communication among partners • Consistent definitions arrived at through consensus • A person in a leadership position who understands and has earned the respect of both the secondary and postsecondary partners • Factors that hamper data sharing and/or reliability include • Incompatible software • Unwillingness to share student names or other means to id students • Inconsistent definitions used within the consortium • The lack of authority of the consortium

  7. More Early Findings • Data that are difficult to accurately measure and track include • Accurate count of secondary and postsecondary TP students (which affects other data) • Secondary to postsecondary matriculation rates • Ways that data are being used include • Recruitment of students to the college • Informing superintendents of their students’ post high school progress including matriculation and remediation rates • Encouraging teachers to understand how to use data in improving programs and curricula • The creation of a data driven culture

  8. Data Tracking at Sauk Valley Community College SVCC uses data information provided by: The area high schools The area Career Center Tech Prep career path students

  9. SVCC Data Information Collected Includes • Students’ names • Students’ home addresses • Identification number/birth date • Students’ phone number • Home high school’s name • Year of graduation • Career path student is pursuing

  10. High School Data • Data information is updated yearly • Student is identified as being a Tech Prep or not a Tech Prep student. • Student is identified if he/she is taking any dual credit classes • Student is identified if he/she has earned any articulated credits

  11. Community College Data • Students are tracked • once they graduate from high school & attend SVCC; • by the type of remediation needed when they enter the college; • by career pathway and CIP code; • by the certificate and/or degree earned; and • by employment opportunities.

  12. Issues in the SVCC Tracking System • Collecting accurate data from the high schools • Time required to input data into the college’s computer system • Identifying the Tech Prep students at the high schools • Getting articulation agreements in place with the high schools and putting it on the transcript at the college • Offering dual credit opportunities for the high school students

  13. Benefits of the SVCC Tracking System • The ability to track students from high school to SVCC career programs • The college can anticipate areas of growth • The creation of a database for use in sending information to potential students • The establishment of a communication system with area high schools • The ability to provide superintendents and counselors with important data regarding their students • It enables improved Tech Prep planning strategies

  14. Future Hopes for SVCC Tech Prep • All students can receive a seamless transition from high school to our college. • All students will have access to a career plan and pathway to help them better prepare for college • All students can earn articulated and/or dial credit while still attending high school • All students will complete college and earn a degree of some kind

  15. Tracking Tech Prep Students at Moraine Valley Community College Issues MVCC encountered include: • Exploration of relationship with EFE • Adequate resources at the community college • Availability of grant dollars to leverage • Identification of problems in the system • Research report needs • What kind of information needs to be retrieved

  16. Problems MVCC Encountered Include: • Time to schedule project meetings among 5 people • Investment of time in Enrollment/Admissions Office for data entry and collaboration with Research Office • Identification of proper office to analyze student records. • Identification of stakeholders interested in the analysis and findings. • Questioning whether the evaluation would lead to improvement in the system.

  17. Analysis of a Sample of Tech Prep Students • Sample representing 18 percent of 176 fall, 2006 enrollees indicate 4 were registered as a career student, and 66 percent were either Liberal Arts Transfer or Transfer Course Enrollee, but were taking career and technical courses along with non-career courses • All Students indicated they had plans to transfer to a 4-year institution • The Liberal Arts and Transfer Course Enrollee designation is made at time of application/default designation

  18. Added Value of MVCC Tech Prep Data:Student Success Issues • Track persistence/retention of students and compare to non tech prep/dual credit students • Identify a better means of tracking students, either on the application forms with different questions or adding new markers in student record system • Use of data to communicate with high school administrators/faculty about the success of a cohort of students

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