frameworks for analyzing data create center for research, evaluation and advancement of teacher...
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Frameworks for Analyzing Data
CREATECenter for Research, Evaluation and Advancement of Teacher Education
TxATEOctober 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?
DaRTS PACE Customized
Teacher Employment
Assignment
Retention
Public Schools Enrollment Trends Impact Trends
University Teacher Production Supply/Demand Retention
Demographic
Employment
Assignment
Certification
Audience:Public School DistrictsUniversities
Audience:Universities
Audience:Public School DistrictsUniversities
Data Frameworks
PACE
Performance Analysis for Colleges of
Education
DaRTS
Data Reporting Tool for Schools
CUSTOMIZED DATA
DEMOGRAPHIC INFORMATION
ID Number Last Name First Name Middle Name Ethnicity Gender
A unique identifierfor 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 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 NativeAsianBlack/African AmericanHispanic/LatinoWhite
FemaleMale
EMPLOYMENT INFORMATIONEmployment
YearCampus
CodeCampus
Name Role Population Served Subject Area Subjects
Taught % FTEAll employment is calculated in the spring of the academic year. If employment year is 2013, then employment took place during the 2012-2013 academic year.
Code assigned to campus where teacher is employed.
Name of public school campus where teacher is employed.
As defined by PEIMS.
TeacherPrincipal Asstistant PrincipalCounselorLibrarianEducational AideDiagnosticianIntrepreter
Type of student:
Regular BilingualCompensatory/RemedialGifted/TalentedCareer/TechnicalSpecial EducationEnglish as a Second LanguageAdult Basic EducationHonorsMigrant
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 allotmentof subject taught per class up to 1.0.
FIRST THROUGH EIGHTH CERTIFICATE
Certification Year Organization Program Type Certification Type Certification Subject Area Certification Subject Field
Starts at FY 1990. Data before 1989-1990 are not available.
Name of recommending organization.
StandardPost-baccalaureate AlternativeBy examinationJamison BillVocational experienceOut-of-StatePermitParaprofessionalUnknown
Emergency (3 types)Non-renewableOne yearParaprofessional& Standard Para.ProbationaryProfessionalProvisionalStandardStardard ProfessionalUnknownVocational
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
http://ies.ed.gov/ncee/edlabs
CONTACT INFORMATION
Mona S. Wineburg Executive Director
Sherri Lowrey Associate Director of Research
John Beck Higher Education Research Liaison