Doctorate in Education by Dunster Business School

About This Course

What is Doctorate in Education?

The Doctorate in Education (Ed.D) is a professional degree that signifies the highest level of expertise in education leadership. With a growing demand for specialized training in managing educational systems, Ed.D graduates can take on senior roles in educational leadership, policy-making, and consulting.

Who Should Attend?

• Education professionals and aspiring leaders
• Global Ph.D. seekers in Education
• Students aiming for advanced skills and recognition
• Professionals enhancing leadership expertise

Key Offerings

• Training: 100 Hours of Two-Way Live Online Interactive Sessions
• Projects: Facility to undergo projects in Article Dissertation, Designing Research & more
• Masterclass: Access to 12+ Masterclass Sessions for essential soft skill development
• Membership: 36 Months of Membership of Kodakco for Doctorate in Education
• E-Learning: Free access to E-learning Portal and future updates. Get access to PPTs, self-paced Video based learning, library, practice tests, and doubt sessions.
• Certification: Earn a Doctorate degree from Dunster Business School
• Placement: Get 3 in 1 Placement support through Placement Drives, Premium access to the Job portal & Personalized Job Consulting

Trainers at Kodakco

• Most respected industry experts with 17+ years of working experience and recognized by numerous organizations over the years for their work
• They have delivered 450+ keynote classes for the Doctorate in Education
• Have delivered 550+ lectures and are currently empaneled as domain experts with Kodakco

Gold Membership Benefits

• Avail 36 months of Gold Membership of Kodakco Management Academy that includes E-Learning Access through recorded Videos, Games, Projects, CPDSPe Studies
• Access to Masterclass Sessions
• Earn the Prestigious Dunster Business School / Kodakco Alumni Status and become one of the reputed 12000+ Alumni across the globe.
• Experience Industry Projects during the training

Key Takeaways

• Understand the principles of research and data collection methods
• Enhance your knowledge regarding dissertation
• Deepen the knowledge of specialized subjects
• Gain expertise in designing, conducting and publishing a high quality research
• Effectively write academic articles and convey complex ideas
• Gain skills required for quality presentation
• Enhance skills and expertise for efficiently grow in competitive market
• Learn about the process of publishing a good research 
• On completion of Doctorate in Education (Ed.D), become eligible for various Job Roles

Module 1: Thesis management

Research

• Scope and Significance
• Types of Research
• Research Process
• Characteristics of Good Research
• Identifying Research problem
• Meaning of Sampling Design
• Steps in sampling
• Criteria for good sample design
• Types of Sample Design
• Probability and non-probability sampling methods
• Meaning of Measurement
• Types of scales

Review of Literature

• Data Collection
• Types of Data
• Sources of Data Collection
• Methods of Data collection
• Constructing questionnaire
• Establishing, reliability and validity
• Data processing
• Coding, Editing and tabulation of data
• Meaning of Report writing
• Types of Report
• Steps of report writing
• Precautions for writing report
• Norms for using Tables
• Charts and diagram
• Appendix: - Index, Bibliography

Module 2: General Research Methodology

• Meaning and importance of Research
• Types of Research
• Selection and formulation of Research Problem
• Meaning of Research Design
• Need of Research Design
• Features of Research Design
• Inductive, Deductive and Development of models
• Developing a Research Plan
• Exploration, Description, Diagnosis, Experimentation
• Determining Experimental and Sample Designs
• Analysis of Literature Review
• Primary and Secondary Sources
• Web sources
• Critical Literature Review
• Hypothesis
• Different Types of Hypothesis
• Significance
• Development of Working Hypothesis
• Null hypothesis
• Research Methods: Scientific method vs Arbitrary Method
• Logical Scientific Methods: Deductive, Inductive, Deductive-Inductive
• Pattern of Deductive
• Inductive logical process
• Different types of inductive logical methods.

Module 3: Quantitative Research Methods

Introduction to Quantitative Research

Part 1:

• Session Overview
• RQ Hypothesis Course Context Video
• What is Quantitative Research?
• Ethics of Quantitative Research
• Session Summary

Part 2:

• Session Overview
• Introduction to the Scientific Method of Research
• Comparing Descriptive, Predictive and Prescriptive Research
• Inductive and Deductive Approaches to Quantitative Research
• Constructing Models
• Session Summary

Exploring Quantitative Research Design
Part 1:

• Session Overview
• Fundamentals of Research Design
• Components of a Research Design
• Characteristics of a Research Design
• Session Summary

Part 2:

• Session Overview
• Research Design for Experimental Research Studies
• Research Design for Quasi Experimental Studies
• Research Design for Non-Experimental Research Studies
• Evaluating Quantitative Research Design
• Session Summary

Data Collection for Quantitative Research
Part 1:

• Session Overview
• Defining Surveys
• Exploring Survey Methods
• Session Summary

Part 2:

• Session Overview
• The Process of Questionnaire Development
• Designing a Questionnaire
• Designing Rating Scales
• The Art of Asking Questions
• Session Summary

Part 3:

• Session Overview
• Tips to Conduct Effective Surveys
• Ethics of Using Technology in Surveys
• Session Summary

Measurement and Sampling
Part 1:

• Session Overview
• What is Measurement?
• True Score Theory, Estimating Measurement Errors
• Evaluating Validity of Measures
• Evaluating Reliability of Measures
• Session Summary

Part 2:

• Session Overview
• Basic Concepts of Sampling
• Problems and Blases in Sampling
• Probability Sampling
• Non-Probability Sampling
• Session Summary

Part 3:

• Session Overview
• Determining the Sample Size
• Sampling Distribution and Statistical inference
• Demonstrations on Sampling
• Session Summary

Constructing Statistical Models
Part 1:

• Session Overview
• Significance of Comparing Means for Analysis
• What is ANOVA?
• Types of ANOVA
• Calculating and Interpreting One-Way ANOVA
• Session Summary

Part 2:

• Session Overview
• Building a Statistical Model
• Effect of Moderating and Mediating Variables
• Demonstration on Mediation and Moderation
• Session Summary

Enhancing Statistical Models
Part 1:

• Session Overview
• What is Factor Analysis?
• Conducting Factor Analysis
• Demonstration on R: Factor Analysis
• Interpreting Factor Scores
• Session Summary

Part 2:

• Session Overview
• What is Factorial ANOVA?
• Dealing with Interaction Effects in Factorial ANOVA
• Calculating and Interpreting Factorial ANOVA
• Session Summary

Multivariate Analyses
Part 1:

• Session Overview
• Multivariate regression
• MANOVA
• Logistic Regression
• Structural Equation Modeling
• Tree Structured Methods
• Conjoint Analysis
• Session Summary

Part 2:

• Session Overview
• Time Series
• Cluster Analysis
• Session Summary

Writing a Quantitative Research Paper
Part 1:

• Session Overview
• Introduction to Formatting the Research Project for Quantitative Research
• Components of a Quantitative Research Paper
• Writing the Summary, Background and Purpose of Quantitative Research
• Writing the Literature Review
• Detailing your Research Design/Methodology
• Curating your Results, Analysis and Supplimentary Findings
• Outlining your Conclusions and Reccomendations
• Making Appendices
• Session Summary

Part 2:

• Session Overview
• Writing Different Types of Quant Papers
• Guidelines for Fine Tuning your Research Presentation
• Session Summary

Module 4: Qualitative Research Methods

Introduction to Qualitative Research

• Key Elements of Qualitative Research
• Writing Qualitative Research Question
• Qualitative Research: Framework
• Steps to Write a Qualitative Research Paper
• Ethics for Qualitative Research and IRB
• Introduction to Design Strategies
• Data-Collection and Analysis Strategies
• Introduction to research design
• Major aspects of research design

Data Collection in Qualitative Research

• Sources of Evidence: A Comparative
• Assessment (Forms-Strengths-Weaknesses)
• Principles of Data Collection
• Sampling
• Reliability and Validity

Interviews and Focus Groups

Introduction to Data Analysis

• An Introduction to Data Analysis
• First Cycle Coding (Description +Demo)
• Second Cycle Coding (Description +Demo)
• Jottings and Analytic Memoing (Description +Demo)
• Assertions and Propositions (Description +Demo)
• Within Case and Cross-Case Analysis (Description+Demo)

Data Display and Exploration

• Matrix and Networks
• Timing, formatting
• Extracting Inferences and Conclusions
• Exploring Fieldwork in Progress
• Exploring Variables
• Exploring Reports in Progress

Data Analysis Process - Next Steps

• Describing Participants
• Describing Variability
• Describing Action
• Ordering by time
• Ordering by process
• Explaining Interrelationship-Change
• Explaining Causation
• Making Predictions

Verifying Conclusions

• Tactics to achieve integration among diverse pieces of data
• Tactics to sharpen understanding by differentiation
• Tactics of seeing relationships in data abstractly
• Tactics to assemble a coherent understanding of data
• Tactics for testing or confirming findings
• Standards for quality of conclusions

Writing Report and New Technologies

• Other methods in Qualitative Research
• Audiences and Effects
• Different aspects / apa
• An Introduction to Mixed Methods Research