Frameworks for Analyzing Data CREATE Center for Research, Evaluation and Advancement of Teacher Education TxATE October 20, 2013

Consortium of 54 Texas Universities – Texas A&M University System – Texas State University System – University of Houston System – University of Texas System – Other Public Universities – Private Universities WHO WE ARE

WHAT WE DO ADVANCE THE QUALITY AND EFFECTIVENESS OF TEACHER PREPARATION PROGRAMS IN TEXAS UNIVERSITIES

OUR WORK  Expand Knowledge Through Research  Build Capacity for Institutional Change  Initiate Action Through Programs

There’s a lot of data out there… How do you make sense of it? What do you do with it?

Data Frameworks Utility of Data Frameworks Tie related data sources together: (e.g., preparation to employment) Organize data into meaningful formats Track current and trend patterns Augment data available internally for “big picture” look Target areas for program improvement Set goals with measurable outcomes Benchmark Determine long-term assessment of impact

Data Frameworks Structuring Data Conversation for Action: All of our frameworks began with a series of questions. For example: Who prepares teachers? Where do they go? How long do they stay?

CREATE’S Data Frameworks PACE -- Performance Analysis for Colleges of Education DaRTS –-Data Reporting Tool for Schools Customized data sets for both PACE and DaRTS

PACE Performance Analysis for Colleges of Education What are the characteristics of area schools? What do the achievement patterns of area schools look like by campusl level? Are universities preparing the teachers district’s need?

DaRTS Data Reporting Tool for Schools Who is employed in the schools? What do they teach? Where are they prepared? How long do they stay?

DaRTSPACECustomized Teacher Employment Assignment Retention Public Schools Enrollment Trends Impact Trends University Teacher Production Supply/Demand Retention Demographic Employment Assignment Certification Audience: Public School Districts Universities Audience: Universities Audience: Public School Districts Universities Data Frameworks

PACE Performance Analysis for Colleges of Education

DaRTS Data Reporting Tool for Schools

CUSTOMIZED DATA

DEMOGRAPHIC INFORMATION ID NumberLast NameFirst Name Middle Name EthnicityGender A unique identifier for each person listed in the database. For each employment year, a person's last, first and middle name will appear on a separate row for every class taught until % FTE adds up to 1.0. For each employ- ment year, a per- son's last, first, and middle name will appear as a separate row for every class taught until % FTE adds up to 1.0. Am. Indian/Alaska Native Asian Black/African American Hispanic/Latino White Female Male EMPLOYMENT INFORMATION Employment Year Campus Code Campus Name Role Population Served Subject Area Subjects Taught % FTE All employment is calculated in the spring of the academic year. If employment year is 2013, then employment took place during the academic year. Code assigned to campus where teacher is employed. Name of public school campus where teacher is employed. As defined by PEIMS. Teacher Principal Asstistant Principal Counselor Librarian Educational Aide Diagnostician Intrepreter Type of student: Regular Bilingual Compensatory/Remedial Gifted/Talented Career/Technical Special Education English as a Second Language Adult Basic Education Honors Migrant The general subject area of the teaching assignment for each FTE up to 1.0 Description of the teaching assignment. This is tied to the % FTE column. If the % FTE is less than 1.0, there will be a line for each subject taught and the % FTE of the assignment. For each employment year, the allotment of subject taught per class up to 1.0. FIRST THROUGH EIGHTH CERTIFICATE Certification YearOrganization Program Type Certification Type Certification Subject AreaCertification Subject Field Starts at FY Data before are not available. Name of recommending organization. Standard Post-baccalaureate Alternative By examination Jamison Bill Vocational experience Out-of-State Permit Paraprofessional Unknown Emergency (3 types) Non-renewable One year Paraprofessional & Standard Para. Probationary Professional Provisional Standard Stardard Professional Unknown Vocational Broad description of certification area.Detailed description of certification area.

Data-Informed Conversations 1)Setting the stage. What question is to be addressed? What information is needed to answer the question? Is the information available? 2) Examining the data. What patterns are revealed or observations can be made? 3)Understanding the findings. What are the possible causes for the patterns? 4)Developing an action plan. 5)Monitoring progress and measuring success

CONTACT INFORMATION Mona S. Wineburg Executive Director Sherri Lowrey Associate Director of Research John Beck Higher Education Research Liaison