Action Research and Traditional Research
Action Research and Traditional Research
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Action research and traditional research are different mainly in their purpose, process, and application. Action research is done by people working in real situations, like teachers or professionals, who want to improve their own practice. It focuses on solving problems in a specific, real-world setting and follows a cyclical process of trying something, observing, and making changes over time.
On the other hand, traditional research is more structured and formal and focuses on building general knowledge or theories. It usually follows a linear, step-by-step process and looks for results that can apply to a larger population. While traditional research aims to create broad, generalizable findings, action research focuses on making immediate, meaningful improvements in a specific environment.
Qualitative, Quantitative, & Mixed Methods Reseach Design
Qualitative, Quantitative, & Mixed Methods Reseach Design
Quantitative and qualitative research approaches differ in purpose, process, and outcomes, but both are essential for understanding and improving learning. Quantitative research focuses on analyzing numerical data to identify patterns and measure results, while qualitative (Design-Based Research) focuses on understanding experiences and improving practices through real-world application and iteration. Together, they provide a complete picture for evidence-based decision-making. Mixed methods research combines both quantitative and qualitative approaches to provide a more complete understanding of a problem. It uses numerical data to identify patterns and qualitative data to explain the meaning behind those patterns. This approach strengthens research by offering both measurable results and deeper insight.
Purpose of Quantitative Analysis Software
Helps transform data into actionable insights
Supports evidence-based decision-making in education
Allows analysis of patterns, relationships, and differences in data
Focus on Application (Not Just Theory)
Emphasis on doing analysis, not just understanding it
Requires selecting correct statistical tests
Interpreting results responsibly is critical
Key Skills Developed
Using statistical software (Jamovi, JASP, PSPP)
Running analyses like:
Descriptive statistics
Correlation
t-tests
ANOVA
Creating data visualizations (graphs, charts)
Structured Analysis Process
Define the research question
Examine the dataset
Select the correct method
Run the analysis
Interpret results
Make recommendations
Importance of Decision-Making
Errors come from poor decisions, not math mistakes
Must align:
Research question
Data type
Statistical test
Real-World Application
Used in instructional design and education
Helps evaluate programs and interventions
Supports communication with non-technical stakeholders
Key Takeaway
Software is a tool, not a shortcut
Success depends on how well you interpret and apply results
Mixed Methods Approach
Combines qualitative + quantitative data
Uses triangulation to strengthen findings
Provides deeper understanding of results
Definition
Combines quantitative (numbers) + qualitative (experiences)
Provides a more complete understanding of research problems
Purpose
Use numbers to identify trends
Use qualitative data to explain why those trends occur
Key Idea
Goes beyond just “what happened”
Explains both results + meaning
Triangulation
Uses multiple data sources to confirm findings
Increases credibility and accuracy of results
Data Sources
Quantitative → test scores, statistics, performance data
Qualitative → interviews, observations, reflections
Benefits
More complete and balanced understanding
Stronger evidence for decision-making
Reduces bias by combining perspectives
Application
Evaluating programs or interventions
Understanding both outcomes and experiences
Common in education, leadership, and instructional design
Challenges
More time-consuming
Requires understanding of both methods
Data integration can be complex
Purpose of Qualitative / DBR
Improve educational practices and interventions
Understand learner experiences and behaviors
Generate design principles for future use
Key Characteristics
Conducted in authentic (real-life) settings
Focuses on complex learning environments
Embraces multiple variables instead of controlling them
Collaborative between researchers and practitioners
Iterative (Cyclical) Process
Analyze problem
Design solution
Implement in real setting
Evaluate results
Refine and repeat
Continuous improvement over time
Types of Qualitative Data Used
Interviews and focus groups
Observations
Student work/artifacts
Reflection notes
Helps explain why outcomes happen
Key Concepts
Conjecture Mapping → connects design ideas to expected outcomes
Design Principles → general ideas that guide future learning design
Implementation Fidelity → ensures the design is used as intended
Real-World Application
Improves courses, programs, and learning environments
Supports instructional design and leadership decisions
Focuses on solving real educational problems
Key Takeaway
Qualitative research is about understanding experiences, not just measuring outcomes
DBR turns educators into designers + researchers improving learning over time
5430 - Research Proposal
5430 - Research Proposal
Research Method: Mixed-Methods Action Research
Action Research Focus:
Conducted within a real classroom
Aimed at improving instructional practice
Quantitative Data:
Pre- and post-assessments
Behavior tracking and engagement data
Qualitative Data:
Surveys (Likert-scale + short answer)
Student and parent perceptions
Purpose:
Evaluate impact on engagement and academic performance
Provide a well-rounded understanding of classroom implementation
6430 - Research Proposal
6430 - Research Proposal
Research Method: Quantitative (Quasi-Experimental Design)
Approach:
Deductive (theory → hypothesis → testing)
Design Features:
Comparison between two groups (participants vs. non-participants)
Pre- and post-measurements
Data Collected:
Parent surveys (knowledge & confidence)
Student academic data (grades, attendance, behavior)
Parent-teacher communication records
Purpose:
Measure impact of parent workshops on engagement and student success
Determine cause-and-effect relationships
Reflection
Reflection
Through completing these research projects, I developed a deeper understanding of different research methods, including mixed methods, action research, and quantitative quasi-experimental design. I learned how each approach serves a different purpose, mixed methods provides a well-rounded perspective by combining data types, action research focuses on improving real-world practice, and quantitative research allows for measuring outcomes and identifying cause-and-effect relationships.
One of the most valuable skills I gained was the ability to design research that aligns with a specific goal or problem. I learned how to create research questions, develop hypotheses, and choose appropriate data collection methods such as surveys, assessments, and observations. I also strengthened my ability to analyze both numerical data and qualitative feedback to draw meaningful conclusions.
These experiences helped me understand the importance of using data to inform decisions, especially in educational settings. I now see research not just as an academic task, but as a practical tool for improving instruction, student engagement, and learning outcomes.
In my future career, I plan to use these skills to evaluate instructional tools and strategies, make data-driven decisions, and continuously improve my practice. Whether I am implementing new technology like ClassDojo or designing learning experiences, I will apply research methods to assess effectiveness and make adjustments that better support learners. Overall, this process has prepared me to be a more reflective, analytical, and effective educator and instructional designer.
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