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How Are Teacher Education Institutions Using Data to Improve Programs?. Lessons Learned from the SUNY Teacher Education Program Assessment FIPSE Project, 2003-07 A presentation at the Carnegie Roundtable Discussion
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How Are Teacher Education Institutions Using Data to Improve Programs? Lessons Learned from the SUNY Teacher Education Program Assessment FIPSE Project, 2003-07 A presentation at the Carnegie Roundtable Discussion “Improving New York’s Teacher Education Programs Through Evidence-Based Decision Making” April 18, 2007 Albany, New York Suzanne Weber, Project Director & Associate Dean School of Education, SUNY Oswego
How Are Teacher Education Institutions Using Data to Improve Programs? • 3 big ideas for my remarks (3 handouts with more information): • Describe collaborative SUNY FIPSE Project • Illustrate typical data now available and used by the SUNY colleges to improve programs • Describe a framework for a new educational quality information system that could provide data to NYSED, colleges and the schools to improve PK-12 student achievement
SUNY Teacher Education Program Assessment FIPSE Project • Purpose of SUNY FIPSE project is to create campus-level assessment systems that support data-driven program improvements to increase beginning teacher competency • Involves all 16 teacher education institutions in the SUNY System • Includes a wide variety of institutions and programs • SUNY prepares about 30% of college-recommended teachers in New York State • Involves high level of collaboration across campuses and with SUNY System
SUNY Teacher Education Program Assessment FIPSE Project • About 2/3 of the SUNYs are NCATE, 1/3 TEAC, no RATE • Whatever the accreditation agency, all SUNYs are collecting and analyzing data in five major categories:Candidate Content Knowledge Performance Candidate Curriculum Development Performance* Candidate Teaching Performance* Candidate Impact on PK-12 Student Learning* Program & Operational Effectiveness • *Usually includes assessment of Candidate Ability to Meet Needs of Diverse Learners, Instructional Technology Skills, and/or Professional Dispositions • Provide selected examples in each category (complete set in handout)
Teacher Candidate Performance Content Knowledge (Of great interest to A&S faculty) Example 1. Social Studies CST Results (SUNY TCED) X Axis: 0=Total, 1=History, 2=Geography, 3=Economics, 4=Civics, Citizenship & Government, 5=Social Studies Skills, 6=Essay on History Y Axis: 220 is passing score; 300 is maximum score.
Teacher Candidate Performance Content Knowledge Example 2. All SUNY Social Studies CST Results X Axis: 0=Total, 1=History, 2=Geography, 3=Economics, 4=Civics, Citizenship & Government, 5=Social Studies Skills, 6=Essay on History Y Axis: 220 is passing score; 300 is maximum score.
Teacher Candidate Performance Content Knowledge (Of great interest to A&S faculty) Example 4. Content Knowledge in Student Teaching Ant His Geg Psy Soc Pol Eco STS GLS Civ X Axis: Social Studies Content Areas Y Axis: 2=Met But Needs Development, 3=Met (Target), 4=Met with Distinction
Teacher Candidate Performance Teaching Performance Example 6. Instructional Skill in Student Teaching Content Human Adapting Multiple Manage Comm Planning Assess Reflect Partner Prof Instruct Know Dev Instruct Strategy Motivate Skill Disp Tech X Axis: INTASC Standards Y Axis: 2=Met But Needs Development, 3=Met (Target), 4=Met with Distinction
Teacher Candidate Performance Lesson/Unit PlanningImpact on P-12 Student Learning Example 9. Teacher Work Sample Traditional lesson & unit plan objectives embedded in TWS Requires analysis of pre/post test data (and assessment of higher order thinking skills) X Axis: Class Goals Assess Instruct Anal Student Reflection Context Plan Sequence Learning Y Axis: 2=Met But Needs Development, 3=Met (Target), 4=Met with Distinction
Teacher Candidate Performance Lesson/Unit Planning Example 11. Teacher Work Sample X Axis: Class Goals Assessment Instructional Context Plan Sequence Y Axis: 2=Met But Needs Development, 3=Met (Target), 4=Met with Distinction
Teacher Candidate Performance Program Effectiveness Example 13. Candidate Exit Survey X Axis: Overall Career Student Fellow Support Admin Fac & Assess Educ Equity Student Res & Teach Qual Serv Teach Cand Serv Serv Courses Constit Diversity Dev Prof Dev Strat Instruct Y Axis: 4=Good, 5=Very Good, 6=Excellent
Teacher Certification Certification Route, Initial & Additional Certification(s) 1 TEACH Tracking Enhancement (Planned) Teacher Candidate Characteristics Program, GPA/SAT/GRE, Diversity, Admission & Transfer Status Teacher Employment Location, Assignment, Diversity, Persistence, Demand 2 TEACH Pipeline Enhancement (Planned) School Characteristics Location, High Needs, Diversity, Report Cards, Administration Teacher Candidate Performance Content Knowledge, Curriculum Development, Instructional Performance,Impact on PK-12 Student Learning Teacher Examinations General Knowledge, Content Specialty, Pedagogy 3 TEACH Certification Exam Enhancement (Possible) Preservice/Inservice Teacher Performance Link (Possible) 4 PK-12 Student Achievement Gr 3-8 Annual Tests, Regents Exams Teacher Performance Annual Professional Performance Review (APPR) Teacher Characteristics Certifications, Diversity, Experience, Professional Development Student & Environment Student Ability & Motivation, Peers, Family, Social Setting School Conditions Class Size, Learning Environment, Leadership,Facilities, Funding Toward a New York State PK-16 Educational Quality Information System
PK-12 Student Achievement Gr 3-8 Annual Tests, Regents Exams Toward a New York State PK-16 Educational Quality Information System • Teacher education institutions are already using data to improve programs: • Candidate Content Knowledge; • Curriculum Development Performance; • Teaching Performance; • Impact on PK-12 Student Learning; and • Program & Operational Effectiveness • 2. A PK-16 educational quality information system is needed in New York State to: • Understand teachers’ career paths and performance, and • Enhance PK-12 student achievement
How Are Teacher Education Institutions Using Data to Improve Programs? Lessons Learned from the SUNY Teacher Education Program Assessment FIPSE Project, 2003-07 A presentation at the Carnegie Roundtable Discussion “Improving New York’s Teacher Education Programs Through Evidence-Based Decision Making” April 18, 2007 Albany, New York Suzanne Weber, Project Director & Associate Dean School of Education, SUNY Oswego www.oswego.edu/~educate/fipse
Teacher Candidate Performance Content Knowledge Example 3. Benchmarked Content GPA X Axis: Year (2002-03, 2003-04, 2004-05, 2005-06) Y Axis: Content GPA (2.00, 2.50, 3.00, 3.50, 4.00)
Teacher Candidate Performance Content Knowledge Example 5. Content Knowledge in Student Teaching Ant His Geg Psy Soc Pol Eco STS GLS Civ Total
Teacher Candidate Performance Teaching Knowledge Example 7. Social Studies ATS-W Results X Axis: 0=Total, 1=Student Dev, 2=Instruct & Assess, 3=Prof Env, 4=Essay on Instruct & Assess Y Axis: 220 is passing score; 300 is maximum score.
Teacher Candidate Performance Teaching Knowledge Example 8. All SUNY Social Studies ATS-W Results X Axis: 0=Total, 1=Student Dev, 2=Instruct & Assess, 3=Prof Env, 4=Essay on Instruct & Assess Y Axis: 220 is passing score; 300 is maximum score.
Teacher Candidate Performance Lesson/Unit PlanningImpact on P-12 Student Learning Example 10. Teacher Work Sample X Axis: Class Goals Assess Instruct Student Reflection Context Plan Sequence Learning Total
Teacher Candidate Performance Impact on P-12 Student Learning Example 12. Teacher Work Sample X Axis: Analysis of Evaluation & Student Learning Reflection Y Axis: 2=Met But Needs Development, 3=Met (Target), 4=Met with Distinction