EDAD 6906 - Data-Coaching and Decision Making
Fall 2026 Syllabus, Section A02, CRN 42072,
Credit hours: 3
Course Meeting Times
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Instructor
Christopher Rateno
Email: cjrateno@ysu.edu
Course Description
Course Readings
| Group | Title | Author | ISBN |
|---|---|---|---|
| Required |
Required Text/Resources
Holcomb, E. L. (2017). Getting MORE excited about USING data (3rd ed.). Thousand Oaks, CA: Corwin Press.
Recommended Text/Resources
Publication Manual of the American Psychological Association. 6th Edition.
Required Readings –
Bernhardt, V. L. Measuring What We Do in Schools: How to Know If What We Are Doing Is Making a Difference,Chapters 1, 2, & 4 ASCD, 2017, pp. 1-25; 52-65. Gale. LINK
Bernhardt, V. L., (1998, March). Multiple Measures. California Association for Supervision and Curriculum Development (CASCD).
Couros, G. (2015). The Innovator’s Mindset: Empower Learning, Unleash Talent, and Lead a Culture of Creativity, pp 81-92. Dave Burgess.
Summey, Dustin C. (2013) Developing Digital Literacies: A Framework for Professional Learning, 2013, pp. 1-21 Corwin.
Crompton, H., Burke, D., Jordan, K., & Wilson, S. W. G.. Learning with technology during emergencies: A systematic review of K-12 education. British Journal of Educational Technology. 2021; 52: 1554– 1575.
The course readings are subject to change in the event of extenuating circumstances, research developments, current events, and/or to ensure better learning.
Assignments/Assessments
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Schedule of Topics and Assignments
| Week of | Reading(s) | Proposed Topic | Due/To Prepare for Class |
|---|---|---|---|
| 8/24 | ● Syllabus ● Course Direction and Requirement ● Bernhardt Articles Chapter 1 (Holcomb | Getting started with data (why data, & what data) Overview to data types available | Posting 1. Data Usage: Where, What, and How |
| 8/31 | Chapters 2-4) (by Holcomb) | Week 2: High Quality Student Data (Achievement Data) Overview of available data sources and identifying needs. Data types and data interactions ● OST ● MAP/STAR local data Basic data analysis techniques ● Frequency ● Mean ● Percentile ● Standard deviation Data Conversations | Posting 2. Common data sources. Final Project Parts 1 & 2 (3 Types of Available Data and critique) |
| 9/7 | Chapters 5-7 (by Holcomb) | : HQSD: Growth Data Data types and data interactions ● EVAAS Value Added ● EVAAS Diagnostic | Posting 3. Solution on a real dataset by identifying data types, needs assessment questions and possible data interactions Data Manipulation Spreadsheet Assignment |
| 9/14 | Chapters 8-10 (by Holcomb) | Week 4: Other data sources and using data effectively for continuous school improvement Data types and data interactions ● Survey ● Attendance ● Discipline 5 Step Process/Evidence Based Interventions | Posting 4. Collaborative solution on a dataset by creating data analysis for a practical decision making agenda Final Project Part 3 (Logic Model) |
| 9/21 | Couros Ch. 5 Summey Ch. 1 Crompton Et el. | Week 5: Using data and technology effectively for continuous school improvement ● Needs of 4 levels of stakeholders ● Effective application of technology for continuous improvement | ISTE Assignment needs to be posted to both blackboard and SLL. |
| 9/28 | Chapters 11-12 (by Holcomb) | Week 6: Develop action plan guided by data and monitor for fidelity and effectiveness ● Connect data results with needs ● Connect data results with actions ● Connect action with time ● Connect action with vision and stakeholders ● Connect data results with educators for accountability | School Improvement Action Plan Part 4 & 5 (formative) due Peer critique for final project |
| 10/5 | Week 7: Using data for Organizational Learning and Continuous Improvement of Educational Practice | Final Project Field Experience Log Screen Shot Comprehensive Exams: OTLES #2, OTLES #4: |
The course schedule, policies, procedures, and assignments in this course are subject to change in the event of extenuating circumstances, by mutual agreement, and/or to ensure better learning.