Syllabus

Master of Science in Education

EDU 726: Telling your School’s Story through Data Analysis – Summer B 2024

Credits - 3

Description

This course will focus on the use of data to create inclusive environments for all students. Participants in this course will apply the components of the Continuous School Improvement Framework (Plan-Implement-Evaluate-Improve). Participants will use data readily available in their classroom, school, or district. Several protocols for analysis will be used. Themes will include using data to support a shared vision and using data to examine school core values.

Materials

Required

Harlacher, J., Potter, J., & Collins, A. (2024). Untangling data-based decision making: A problem-solving model to enhance MTSS. Marzano.

Supplemental

American Psychological Association. (2019). Publication manual of the American Psychological Association (7th ed.). American Psychological Association. ISBN: 978-1433832154. E-text: 978-1433832185

Learning Objectives and Outcomes

Upon completing this course, students will be able to:

Apply the components of a four-step decision-making model (Identify-Analyze-Implement-Evaluate) within the inclusive environment.
Use data-based decision-making to inform best practices within a schoolwide multitiered system of support (MTSS).
Apply a structured process to delve deeply into multiple sources of data to analyze the intersections and make informed decisions regarding teaching and learning.
Use the problem-solving cycle to make informed decisions regarding teaching and learning.
Use protocols to lead a school site through an analysis of current teaching and learning status.
Evaluate the relationship between the data available and the core values of an organization.
Create a proposed vision and a plan for continuous improvement for inclusive education.

Assignments

Weekly Discussions

This course has required weekly discussions. The discussion topics are related to weekly topics and provide an opportunity for students to share ideas about how the content applies to professional practice. Your instructor will participate in the discussions as both a guide and an observer.

Week 2 Letter: Sharing the Story with Families

Imagine you are the school’s principal; write a letter to families that clearly outlines the school’s plan for the Comprehensive Assessment System, including ongoing progress monitoring, for the upcoming school year.

Week 3 Data-Based Problem Solving Model: Story Outline

Create a detailed visual model of the steps in the data-based problem solving method in a format of your choice.

Week 4 Presentation: Story Setting

Create a Professional Development presentation for faculty at your school providing an overview of the steps of a data-based problem solving model.

Week 5 Interview: Story Context

Interview a building principal using the framing questions below as jumping points for your conversation. Write a 1-2 page written reflection regarding your insights.

Week 6 Tier 2 Supports: Examining Common Themes

PART ONE:

Create the Identification Process and Placement Protocol that will be used by your school to identify students who need tier 2 interventions. Utilize the information in your textbook, specifically the procedures for Problem Identification and Analysis.

PART TWO:

Write a brief recommendation list that your team will follow to complete the last two steps of the problem solving process, Plan Identification and Implementation and Plan Evaluation

*Note: This does not have to be a comprehensive list. The recommendations you make now will be revised in the final course assessment.

Week 7 Supports: Character Analysis

Based on the scenario provided in Brightspace, complete the Plan Identification and Implementation and Plan Evaluation. You will need to utilize additional resources to complete these tasks.

Week 8 Proposal for Story Revision

Create a formal proposal in a format of your choosing to your school district’s administration detailing your recommended school-wide process for implementing a data-based decision making model at Tier 1, Tier 2, and Tier 3.

Grading Policy

Your grade in this course will be determined by the following criteria:

Grade Breakdown

Assignments	Points
Weekly Discussions (Weeks 1-6, 8)	28 pts (4 pts. each weekly discussion)
Week 2 Letter: Sharing the Story with Families	8 pts
Week 3 Data-based Problem-solving Model: Story Outline	8 pts
Week 4 Presentation: Story Setting	8 pts
Week 5 Interview: Story Context	10 pts
Week 6 Tier 2 Supports: Examining Common Themes	10 pts
Week 7 Tier 3 Supports: Character Analysis	10 pts
Week 8 Proposal for Story Revision	18 pts
Total	100 pts

Grade Scale

Grade	Points Grade	Point Average (GPA)
A	94 – 100%	4.00
A-	90 – 93%	3.75
B+	87 – 89%	3.50
B	84 – 86%	3.00
B-	80 – 83%	2.75
C+	77 – 79%	2.50
C	74 – 76%	2.00
C-	70 – 73%	1.75
D	64 – 69%	1.00
F	00 – 63%	0.00

Schedule

Course Schedule

Week 1: Jul 3 – Jul 7
Week 2: Jul 8 – Jul 14
Week 3: Jul 15 – Jul 21
Week 4: Jul 22 – Jul 28
Week 5: Jul 29 – Aug 4
Week 6: Aug 5 – Aug 11
Week 7: Aug 12 – Aug 18
Week 8: Aug 19 – Aug 25

Weeks	Topics	Activities & Assignments	Dates
Week 1	The Data Story	Watch: Week 1 Lecture Why storytelling is more trustworthy than presenting data \| Karen Eber \| TEDxPurdueU Read: Weekly Overview Introduction of Harlacher, J., Potter, J., Collins, A. (2024). Syllabus Submit: Week 1 Discussion: Introductions	Due: Sun. 11:59 PM ET Initial discussion responses should be posted by FRIDAY night
Week 2	Multi-tiered Systems of Support	Watch: Effective Family Engagement Practices in a Turnaround School Using Data to Support Teacher and Student Growth Read: Weekly Overview Chapter 1 of Harlacher, J., Potter, J., Collins, A. (2024). Why is data and data-based decision making such a critical part of instruction and intervention? \| Center on Multi-Tiered Systems of Support Submit: Week 2 Discussion: MTSS and Comprehensive Data Systems Week 2 Assignment – Letter: Sharing the Story with Families	Due: Sun. 11:59 PM ET Initial discussion responses should be posted by WEDNESDAY night
Week 3	Defining Data-Based Decision Making	Read: Weekly Overview Chapter 2 of Harlacher, J., Potter, J., Collins, A. (2024). Submit: Week 3 Discussion: School Collaboration Week 3 Assignment – Data-Based Problem Solving Model: Story Outline	Due: Sun. 11:59 PM ET Initial discussion responses should be posted by WEDNESDAY night
Week 4	Decision Making at the Schoolwide Level	Read: Weekly Overview Chapter 3 of Harlacher, J., Potter, J., Collins, A. (2024). Submit: Week 4 Discussion: Tier 1 Standards of Practice Week 4 Assignment – Presentation: Story Setting	Due: Sun. 11:59 PM ET Initial discussion responses should be posted by WEDNESDAY night
Week 5	Decision Making at Tier 1	Read: Weekly Overview Chapter 4 of Harlacher, J., Potter, J., Collins, A. (2024). Submit: Week 5 Discussion: Interview Reflection Week 5 Assignment – Interview: Story Context	Due: Sun. 11:59 PM ET Initial discussion responses should be posted by FRIDAY night
Week 6	Decision Making at Tier 2	Watch: Under the Table – The Importance of Presuming Competence \| Shelly Moore \| TEDxLangley ED The Sweeper Van by Shelley Moore Read: Weekly Overview Chapter 5 of Harlacher, J., Potter, J., Collins, A. (2024). Submit: Week 6 Discussion: Interventions Week 6 Assignment – Tier 2 Supports: Examining Common Themes	Due: Sun. 11:59 PM ET Initial discussion responses should be posted by WEDNESDAY night
Week 7	Decision Making at Tier 3	Read: Weekly Overview Chapter 6 of Harlacher, J., Potter, J., Collins, A. (2024). Submit: Week 7 Assignment – Tier 3 Supports: Character Analysis	Due: Sun. 11:59 PM ET; No discussion this week
Week 8	The Next Chapter	Watch: Building capacity and improving outcome with DBI: Wyoming’s implementation story Submit: Week 8 Discussion: Challenges and Strategies for Future Implementation of MTSS Week 8 Assignment – Proposal for Story Revision	Due: FRIDAY 11:59 PM ET Initial discussion responses should be posted by WEDNESDAY night

Student Resources

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Policies

AI Use

The Graduate Programs in Education holds the position that Grammarly and other AI writing and generative technology should not be used when completing course assignments, unless explicitly permitted by course faculty and assignment instructions. These tools do not support a student’s personal and direct capacity to develop and hone skills in creativity, logic, critical thinking, analysis, evaluation, theorization, and writing, which are central to graduate-level rigor, assessment, and research. Use of these tools when not explicitly permitted may result in an academic integrity infraction.

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The College of Professional Studies uses Turnitin to help deter plagiarism and to foster the proper attribution of sources. Turnitin provides comparative reports for submitted assignments that reflect similarities in other written works. This can include, but is not limited to, previously submitted assignments, internet articles, research journals, and academic databases.

Make sure to cite your sources appropriately as well as use your own words in synthesizing information from published literature. Webinars and workshops, included early in your coursework, will help guide best practices in APA citation and academic writing.

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Course Evaluation Policy

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Late Policy

Assignments: Late assignments will be accepted up to 3 days late; however, there is a 10% grade reduction (from the total points) for the late submission. After three days the assignment will not be accepted.

Discussion posts: If the initial post is submitted late, but still within the discussion board week, there will be a 10% grade reduction from the total discussion grade (e.g., a 3 point discussion will be reduced by 0.3 points). Any posts submitted after the end of the Discussion Board week will not be graded.

Please make every effort ahead of time to contact your instructor and your student support specialist if you are not able to meet an assignment deadline. Arrangements for extenuating circumstances may be considered by faculty.

Attendance Policy

8 week: Students taking online graduate courses through the College of Professional Studies will be administratively dropped for non-participation if a graded assignment/discussion post is not submitted before Sunday at 11:59 pm ET of the first week of the term. Reinstatement is at the purview of the Dean's Office.

16 week: Students taking online graduate courses through the College of Professional Studies will be administratively dropped for non-participation if a graded assignment/discussion post is not submitted before Friday at 11:59 pm ET of the second week of the term. Reinstatement is at the purview of the Dean's Office.

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UNE Online Student Handbook

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Academic dishonesty includes, but is not limited to the following:

Cheating, copying, or the offering or receiving of unauthorized assistance or information.
Fabrication or falsification of data, results, or sources for papers or reports.
Action which destroys or alters the work of another student.
Multiple submissions of the same paper or report for assignments in more than one course without permission of each instructor.
Plagiarism, the appropriation of records, research, materials, ideas, or the language of other persons or writers and the submission of them as one's own.

Charges of academic dishonesty will be reviewed by the Program Director. Penalties for students found responsible for violations may depend upon the seriousness and circumstances of the violation, the degree of premeditation involved, and/or the student’s previous record of violations. Appeal of a decision may be made to the Dean whose decision will be final. Student appeals will take place through the grievance process outlined in the student handbook.