(EDL 715) Database Decision Making and Technology
Syllabus of Record
Catalog Description: Principles of data-based decision making and their applications in
educational settings will be explored through readings and case studies. Technology's use in
addressing problems in management and instruction will be included. Three credits.
Unit Mission, Philosophy, Values:
Our Mission:
“Teaching, Leading and Learning in a Democratic Society”
The College of Education prepares candidates who enhance the individual growth of their
students while working to establish policies and practices that promote the principles of
democratic education. The College articulates this mission as Teaching, Leading, and
Learning in a Democratic Society.
Philosophy:
Student Potential, Ethical Implications
Believing that schools function as social and political entities as well as for the growth of
individuals, the College of Education prepares teachers and leaders
a) to enhance the academic and personal potential of their students
b) to evaluate the social and ethical implications of educational policies and practices.
Values:
“Expertise, Equity, Liberal Education, Social Responsibility”
The College of Education values expertise to guide our practice, equity to guide our
interactions, liberal education to guide our perspectives, and social responsibility to guide
our commitment to democratic education. We value these ideals in our preparation of
candidates, our development of faculty, and our relationships with the larger community we
serve.
Unit and Program Standards:
Common Unit Standards: Michigan Department of Education (MDE), This course supports the
Standards for Advanced Programs in Educational Leadership as developed by the Educational
Leadership Constituent Council (ELCC), a constituent member of the National Council for
Accreditation of Teacher Education (NCATE).
Specialty Program Standards: Educational Leadership Constituent Council (ELCC)
Course Standards and Assessments:
1. Analyze school achievement data needs to construct school improvement
plans.
(ELCC 1.2,1.3, 1.4)
2. Analyze district school data to develop district wide school improvement
plans.
(ELCC 2.1)
3. Review demographic data to make informed decisions on diversity education
and cross cultural competencies. (ELCC 2.1)
4. Review data from multiple data sets for use in the data-based decision
making model. (ELCC 2.2)
5. Have experiences in understanding the integral part data mining plays in
strategic planning. (ELCC 3.1)
6. Understand the importance of data management as a function of leadership.
(ELCC 3.2)
7. Create a resource of data sets that can inform and support leadership
decisions.(ELCC 3.2)
8. Describe the basic concepts of data warehousing and data mining.
(ELCC 3.3)
9. Compare and contrast test results to state standards (GLCEs) and develop
instructional adaptations based on those comparisons. (ELCC 2.2)
10. Compare and contrast unlike data sets (ELCC 3.3)
11. Develop strategies in which student achievement data can be discussed with
colleagues. (ELCC 1.1)
12. Create a collection of presentation formats for sharing a broad range of
student data. (ELCC 1.2)
13. Develop an inquiry model for reviewing and analyzing student achievement
data.(ELCC 2.2)
14. Review and synthesize the literature on data-based decision making.
(ELCC 2.2)
Common Assessment: Data-based Instructional Improvement: Analysis of a broad range
of student data in designing an instructional improvement set of objectives based on that
data. Students will be required to integrate state educational standards in that
improvement process.
Major Topics:


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Use of data in the decision making process for school leaders
Constructing action plans around data sets
Understanding the concepts of data warehousing and data mining
Course Knowledge Base:
This course is based on a framework provided from multiple sources including:
Bernhardt, V. (2000). Designing and Using Databases for School
Improvement. Eye on Education, Inc.
Fullan, M. (2001). Leading in a culture of change. San Francisco: Jossey-Bass
Kongshem, L. (1999, September). Mining the school district data
Warehouse. Electronic School. Retrieved February, 28, 2001,
From http://www.electronic-school.com/199909/0999fl.html
Noyce, P., Perda, D., & Traver, R. (2000). Creating data-driven schools.
Educational Leadership, 57, 52-56.
Pereus, S. (2001). Beyond the classroom: how technology can improve
Your district’s management and operating systems. American
School Board Journal, 188(7), 16-20
.
Senge, P. (1990). The fifth discipline. New York: Doubleday/Dell
Shaw, D (2001). Data mining, Curriculum Administrator, 52, 54-57.
Wagner, T. et al. (2006). Change leadership. Jossey-Bass. San Fransisco, CA.