Highlights of the KSU Teacher Education Assessment System

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Highlights of the KSU Teacher Education
Assessment System
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Assessment System Highlights

• Consistent Flexible Reporting Options
• Valid and Reliable Collection of Candidate
  Performance data
• Data Reflections
• Faculty Data

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Consistent Reporting

• Admission to Teacher Education Decisions populate
  the University Systems Student Information
  System (Banner)
• Consistency of reporting University
• Generation of the PTEU Candidate Profile Summary
  by program and unit

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Flexible Reporting

• Flexibility to generate reports for State,
  National agencies

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Data Collection

• Promotes the valid and reliable processes for
  data collection based on the individual program
  area specifications
• Control access of Unit assessment instruments by
  major code, department, course, field experience,
  semester, date.
• Target the appropriate assessment instruments to
  the right people at the right time.

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Data Reflections

• Completed Systematically, Regularly and
  Collaboratively
• Programming of the technology captures the data
  and adds it to the actual data reflection screen

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Data Reflections

• Enables easy archival and retrieval of the data
  reflections to support continuous improvement
  efforts
• Enables longitudinal reflection to build on each
  year.

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Faculty Information System

• Systematic collection and reporting of faculty
  qualifications data
• Integrated with other university data collection
  efforts

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Lessons Learned End Users

• Build in Usability Field test with end users NOT
  technies
• Employ KISS Consistency of user process the
  perception of stability within the system
• Provide multiple levels of help documentation for
  users

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Lessons Learned - Technical

• Separate development phase from simultaneous live
  use and production
• Created a climate of distrust technical
  instability when using a system in development
• Anticipate Security Accessibility Issues
• Establish data elements so that you can aggregate
  and disaggregate by assessment instrument,
  decision point, evaluator types (candidate,
  collaborating teacher/mentor, faculty), etc.

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Lessons Learned - Procedural

• Chunk your Goals ? Prioritize ? Re-Visit Often
• Collaborate across campus with Institutional
  Research, Academic Computing Services,
  Information Technology Services, etc.
• Prioritize data collection efforts - Surveys
  should not be a high priority used to provide
  global feedback on programs and unit due to know
  limitations.

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Learned about Programs?

• Understanding how the business process of
  teacher education works
• Identifying gaps and redundancies
• Anticipating assessment needs of future programs

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What Do You Know Now That We Wish We Had Known
Earlier?

• Need for a data manager to coordinate
  facilitate the process.
• Flexibility to meet Reporting Requirements
• Emerging tensions between NCATE unit assessments
  and focused SPA assessment expectations

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Next Steps

• Leverage additional University wide Faculty
  Resource Tracking processes
• Continue the development of an Academic Candidate
  Profile

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For More Information

• Dr. Beverly F. Mitchellbmitchel_at_kennesaw.edu
• Dr. M. Leigh Funklfunk_at_kennesaw.edu