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Data Sharing Between Educational Organizations: Problems and Prospects

Data Sharing Between Educational Organizations: Problems and Prospects. EPCC/UTEP Data-Sharing Symposium July 6, 2010 Dr. Ed Fuller, PhD Education Consultant and Associate Director, Univ Council for Educ Admin The Penn State University. Topics. 1) FERPA 2) Data Connections in Texas

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Data Sharing Between Educational Organizations: Problems and Prospects

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  1. Data Sharing Between Educational Organizations: Problems and Prospects EPCC/UTEP Data-Sharing Symposium July 6, 2010 Dr. Ed Fuller, PhD Education Consultant and Associate Director, Univ Council for Educ Admin The Penn State University

  2. Topics • 1) FERPA • 2) Data Connections in Texas • 3) Examples of Data Sharing

  3. FERPA • Two Types of Educational Records There are two types of educational records as defined under FERPA. Each type of educational record is afforded different disclosure protections. Therefore, it is important for faculty and staff to know the type of educational record that is being considered for disclosure. Directory Information • Some information in a student's educational record is defined as directory information under FERPA. The school may disclose this type of information without the written consent of the student. However, the student can exercise the option to restrict the release of directory information by submitting a formal request to the school to limit disclosure. Directory information may include: • Name; Address; Phone number and email address; Dates of attendance; Degree(s) awarded; Enrollment status; Major field of study. Non-directory Information • Non-directory information is any educational record not considered directory information. Non-directory information must not be released to anyone, including parents of the student, without the prior written consent of the student, unless certain requirements are met. Further, faculty and staff can access non-directory information only if they have a legitimate academic need to do so. Non-directory information may include: • Social security numbers; Student identification number; Race, ethnicity, and/or nationality; Gender Transcripts; grade reports ; grades; test scores;

  4. FERPA Exceptions (a) An educational agency or institution may disclose personally identifiable information from an education record of a student without the consent required by §99.30 if the disclosure meets one or more of the following conditions: • (1)(i)(A) The disclosure is to other school officials, including teachers, within the agency or institution whom the agency or institution has determined to have legitimate educational interests. • (B) A contractor, consultant, volunteer, or other party to whom an agency or institution has outsourced institutional services or functions may be considered a school official under this paragraph provided that the outside party— • (1) Performs an institutional service or function for which the agency or institution would otherwise use employees; • (2) Is under the direct control of the agency or institution with respect to the use and maintenance of education records; and • (3) Is subject to the requirements of §99.33(a) governing the use and re-disclosure of personally identifiable information from education records.

  5. (B) A contractor, consultant, volunteer, or other party to whom an agency or institution has outsourced institutional services or functions may be considered a school official under this paragraph provided that the outside party— • Performs an institutional service or function for which the agency or institution would otherwise use employees; • (2) Is under the direct control of the agency or institution with respect to the use and maintenance of education records; and • (3) Is subject to the requirements of §99.33(a) governing the use and re-disclosure of personally identifiable information from education records.

  6. Connections Between and Among the K-12 and Higher Education Spheres

  7. IHE Enrollment School Graduates Aggregate GPA School Achievement IHE Enrollment STUDENT K-12 Data STUDENT IHE Data School Demographics IHE Degrees Test Scores Diploma Type Campus District Demographic Courses Test Scores Grades/GPA Degree/Major IHE Demographic Courses School Characteristics IHE TASP/ Tx. Success Init. School Educators Educator Prep Program

  8. Some Examples • Example 1: Evaluating professional development • Example 2: Setting school targets and assessing student growth • Example 3: Teacher placement and attrition • Example 4: Student achievement and teacher placement

  9. Example 1: Evaluating professional development • One school district • Matched teachers to students • Compared gains in achievement of teachers participating in PD vs. those teachers not participating in PD

  10. Example 2: Setting school targets and assessing student growth • One school district • All students: TAKS scores, demographics • Set targets for DATE grant based on historical patterns of achievement • Assessed whether schools achieved performance targets • Assessed student growth using value-added analysis

  11. Example 3: Teacher placement and attrition • Selected teachers and principals from University preparation program and competing programs in the local labor market (LLM) • Examined the percentage of teachers in each school from the programs in the LLM • Statistically compared attrition rates of educators from the programs • Compared student gains in achievement

  12. Example 4: Student Performance and Enrollment in Higher Education • Used student level data to determine the TAKS scores of incoming 9th graders in Tx high schools • Statistically examined the relationship between the ability level of incoming 9th graders and the percentage of students enro0lling in higher education institutions

  13. Ed Fuller, PhD Education Consultant edfuller@mail.utexas.edu

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