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Use of Data to Improve Courses, Programs, & the Unit

Specific examples of assessment data use are described in the document on the web site entitled EXAMPLES OF CHANGES MADE TO COURSES, PROGRAMS AND UNIT IN RESPONSE TO DATA GATHERED FROM THE ASSESSMENT SYSTEM. This document details the extent to which programs, courses, learning targets, and a host of other factors have been revised based on assessment evidence.

While the direct assessment of candidates through the Initial and Advanced Programs Assessment System is important, other mechanisms can and should also be used to gauge the quality of the FSEHD and its programs.  Unit improvements based on data from aggregated candidate assessments, faculty evaluations, and statistics from the Office of Institutional Research include: more pro-active search processes to enhance faculty diversity; focused attention to improve candidate preparation for work with English language learners from a variety of sociocultural backgrounds; needs-based faculty professional development events (e.g. on new state standards and proficiency-based graduation requirements, on case-based instruction, and on using technology to enhance instruction); professional development for faculty about the assessment system and how to use it; redesign of the Annual Department report format; grant-seeking to support faculty knowledge and skill development (successes include a $500,000 federal Teacher Quality Enhancement grant); reconsideration of FSEHD graduate candidate recruitment efforts and a new focus on growing programs; and expansion of Continuing Education opportunities for practicing educators in Early Spring (a new 4-week January semester only for FSEHD) and summer.

Ongoing Efforts

As the Initial and Advanced Programs Assessment Systems mature and further evidence of their reliability and validity is amassed, they will be used systematically to provide further evidence for needed improvements in programs and the unit.  As data-based programmatic and unit changes are implemented, the validity and reliability of the modified system will continue to be assessed, in order to ensure that subsequent inferences and decisions made based on assessment data are appropriate and defensible.

References

McLeod, S. (2005).  Data-driven teachers.  Minneapolis:  School Technology Leadership Initiative, University of Minnesota.  Available at:  www.scottmcleod.net/storage/2005_CASTLE_Data_Driven_Teachers.pdf

Smith, D. & Miller, L.  (2003).  Comprehensive local assessment systems (CLASs) primer:  A guide to assessment system design and use.  Gorham, ME:  Southern Maine Partnership, University of Southern Maine.

Stiggins, R.J. (2001).  Leadership for Excellence in Assessment: A Powerful New School District Planning Guide. Portland, OR: Assessment Training Institute.