EDAD 8194 A01: Dissertation Data Analysis

EDAD 8194 - Seminar in Educational Research – Dissertation: Data Collection Analysis

Fall 2026 Syllabus, Section A01, CRN 42548,

Credit hours: 2

Course Meeting Times

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Instructor

David Bowlin

Email: dabowlin@ysu.edu

Public Instructor Information

Instructor Title: Professor Dr. David Bowlin 
Instructor Professional Qualifications: 

Ed.D., Administration and Policy Studies, University of Pittsburgh, 2004

Master’s, Education Administration, Duquesne University, 2000

Master’s, Secondary Education (Biology), Duquesne University, 1993

Bachelor’s, Biology, Carlow College, 1986

Instructor Office Location: Virtual Office 
Instructor Office Phone: 412-352-8571

Private Instructor Information

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Course Description

8194. Seminar in Educational Research – Dissertation: Data Collection & Analysis. The purpose of this course is to build candidate knowledge and skills in developing Chapter 4 of their dissertation. Students will collect the data for their dissertation and complete the analysis of that data and write up their findings in Chapter 4 of their dissertation, broken down into manageable milestones, following the guidelines set forth in the YSU Educational Leadership Dissertation Guidelines and template. Prereq.: EDAD 8191, EDAD 8192, and EDAD 8193. 2 s.h.

Course Readings

Group Title Author ISBN
Optional A concise guide to writing a thesis or dissertation: Educational research and beyond (2nd ed.). Kornuta, H. M., & Germaine, R. W. 13: 978-0-367-17458-3
Optional APA Manual American Psychological Association 9781433832161

Dissertation Handbook:
https://ysu.edu/educational-leadership-dissertation-guidelines-handbook#tab-9976    Password: edulead26

The course readings are subject to change in the event of extenuating circumstances, research developments, current events, and/or to ensure better learning.  

Additional Course Materials

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Course Learning Outcomes/Objectives/Goals

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How to Succeed in This Course

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Attendance Expectations

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Late Work Submission Policy

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Additional Course Expectations

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Artificial Intelligence Policy Statement

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Assignments/Assessments

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Grading and Grading Scale

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University Policies

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Schedule of Topics and Assignments

Week of Reading(s) Proposed Topic Due/To Prepare for Class
8/24 Module 1 Completed Introduction Chapter 3
8/31 Module 1 Completed Introduction Chapter 4 Introduction and Data Formatted for Analysis
9/7 Module 2 Completed Introduction Chapter 4 Introduction and Data Formatted for Analysis
9/14 Module 2 Completed Introduction Chapter 4 Introduction and Data Formatted for Analysis
9/21 Module 3 Descriptive Analysis; Preliminary Data Analysis Conduct all Descriptive Analysis & Preliminary Data Analysis
9/28 Module 3 Descriptive Analysis; Preliminary Data Analysis Conduct all Descriptive Analysis & Preliminary Data Analysis
10/5 Module 4 Descriptive Analysis; Preliminary Data Analysis Conduct all Descriptive Analysis & Preliminary Data Analysis
10/12 Module 4 Descriptive Analysis; Preliminary Data Analysis Conduct all Descriptive Analysis & Preliminary Data Analysis
10/19 Module 5 Descriptive Analysis; Preliminary Data Analysis Conduct all Descriptive Analysis & Preliminary Data Analysis
10/26 Module 5 Descriptive Analysis; Preliminary Data Analysis Conduct all Descriptive Analysis & Preliminary Data Analysis
11/2 Module 6 Descriptive Analysis; Preliminary Data Analysis Conduct all Descriptive Analysis & Preliminary Data Analysis
11/9 Module 6 Descriptive Analysis; Preliminary Data Analysis Conduct all Descriptive Analysis & Preliminary Data Analysis
11/16 Module 7 Finalize Results and Interpretations Review the analysis and interpretations.
11/23 Module 7 Finalize Results and Interpretations Review the analysis and interpretations.
11/30 Module 7 Completed Revisions Final Draft Completed
12/7 Module 7 Completed Revisions Finalize Edits

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.