(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:
- Analyze school achievement data needs to construct school improvement plans.
(ELCC 1.2,1.3, 1.4)
- Analyze district school data to develop district wide school improvement plans.
(ELCC 2.1)
- Review demographic data to make informed decisions on diversity education and cross cultural competencies. (ELCC 2.1)
- Review data from multiple data sets for use in the data-based decision making model. (ELCC 2.2)
- Have experiences in understanding the integral part data mining plays in strategic planning. (ELCC 3.1)
- Understand the importance of data management as a function of leadership.
(ELCC 3.2)
- Create a resource of data sets that can inform and support leadership decisions.(ELCC 3.2)
- Describe the basic concepts of data warehousing and data mining.
(ELCC 3.3)
- Compare and contrast test results to state standards (GLCEs) and develop instructional adaptations based on those comparisons. (ELCC 2.2)
- Compare and contrast unlike data sets (ELCC 3.3)
- Develop strategies in which student achievement data can be discussed with colleagues. (ELCC 1.1)
- Create a collection of presentation formats for sharing a broad range of student data. (ELCC 1.2)
- Develop an inquiry model for reviewing and analyzing student achievementdata.(ELCC 2.2)
- 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:
- 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
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.