How Are Teacher Education Institutions Using Data to Improve Programs?

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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 Yorks 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
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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

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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

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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)

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Teacher Candidate Performance Lesson/Unit
PlanningImpact on P-12 Student Learning
Example 9. Teacher Work Sample
Requires analysis of pre/post test data (and
assessment of higher order thinking skills)
Traditional lesson unit plan objectives
embedded in TWS
X Axis Class Goals Assess
Instruct Anal Student Reflection
Context Plan
Sequence Learning Y
Axis 2Met But Needs Development, 3Met
(Target), 4Met with Distinction
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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 4Good, 5Very Good, 6Excellent
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Toward a New York State PK-16 Educational
Quality Information System
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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

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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 Yorks 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
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Pass Rate 100 100 97 97 100 100 100 100 100 100 99
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Pass Rate 100 100 98 100 100 100 100
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