Course Overview
Master advanced research methodologies for your PhD journey with comprehensive theoretical frameworks and practical applications.
Course Objectives
- • Develop comprehensive understanding of research paradigms
- • Master quantitative and qualitative methodologies
- • Apply mixed methods approaches effectively
- • Ensure ethical compliance throughout research process
Learning Outcomes
Upon completion, students will demonstrate:
- • Critical evaluation of research designs
- • Proficiency in statistical analysis techniques
- • Ethical decision-making in research context
- • Effective communication of research findings
Chapter List
Comprehensive curriculum for advanced research methodology
Chapter 1: Research Paradigms
Understanding positivist, interpretivist, and critical paradigms
Learn More →Chapter 2: Literature Review
Systematic review methods and critical analysis techniques
Learn More →Quantitative Methods
Master experimental design, survey methods, and statistical analysis for robust quantitative research
Key Learning Objectives
- ▸ Design experimental and quasi-experimental studies
- ▸ Develop valid and reliable measurement instruments
- ▸ Apply advanced statistical techniques appropriately
- ▸ Interpret statistical results with confidence
Experimental Design
Randomized controlled trials, factorial designs, and causal inference
Survey Methodology
Sampling techniques, questionnaire design, and response analysis
Statistical Analysis
Regression, ANOVA, multivariate analysis, and power calculations
Measurement & Validity
Construct validity, reliability testing, and psychometric evaluation
Software & Tools Covered
Qualitative Research
Explore interpretive approaches to understand complex phenomena through in-depth analysis
Research Paradigms
- • Interpretivism
- • Constructivism
- • Phenomenology
- • Grounded Theory
Ethnographic Methods
Participant observation, field notes, and cultural analysis techniques
Interview Techniques
Semi-structured, in-depth, and focus group methodologies
Data Analysis
Thematic analysis, coding strategies, and pattern identification
Case Study Design
Single and multiple case study approaches with validation
Software & Tools
Mixed Methods
Integrate quantitative and qualitative approaches for comprehensive research insights
Integration Strategies
Design Frameworks
Sequential, concurrent, and transformative designs
Data Integration
Merging, connecting, and embedding data sources
Validation Techniques
Triangulation, member checking, and credibility
Reporting Standards
Good reporting of mixed methods studies (GRAMMS)
Statistical Analysis
Master advanced statistical techniques for rigorous data analysis and interpretation
Descriptive Statistics
Central tendency, variability, and distribution analysis
Inferential Statistics
Hypothesis testing, t-tests, ANOVA, and regression
Multivariate Analysis
MANOVA, factor analysis, and structural equation modeling
Non-parametric Methods
Chi-square, Mann-Whitney, and Kruskal-Wallis tests
Software Proficiency
Learning Outcomes
- • Select appropriate statistical tests
- • Interpret statistical output accurately
- • Validate assumptions and limitations
- • Report findings following APA standards
Research Design
Master the art of designing robust research frameworks that answer complex questions effectively
Design Components
- → Problem formulation and hypothesis development
- → Operational definitions and variables
- → Population and sampling strategies
- → Data collection procedures
Experimental Design
Randomized controlled trials, factorial designs, and quasi-experiments
Cross-sectional Studies
Survey design, correlation analysis, and descriptive studies
Longitudinal Design
Panel studies, cohort analysis, and repeated measures
Case-Control Studies
Retrospective analysis and comparative design
Ethics
Navigate ethical challenges and ensure compliance throughout your research journey
Core Principles
- → Beneficence and non-maleficence
- → Respect for autonomy and persons
- → Justice and fairness
- → Fidelity and responsibility
IRB Procedures
Institutional Review Board protocols and approval processes
Informed Consent
Consent forms, capacity assessment, and voluntary participation
Data Privacy
GDPR compliance, anonymization techniques, and data security
Vulnerable Populations
Special considerations for minors, prisoners, and marginalized groups
Ethics Checklist
Pre-Research
- • Risk-benefit analysis
- • Participant recruitment ethics
- • Confidentiality protocols
- • Conflict of interest disclosure
During Research
- • Ongoing consent monitoring
- • Adverse event reporting
- • Data integrity maintenance
- • Participant withdrawal rights
Assessment
Comprehensive evaluation methods and grading criteria
Evaluation Components
Assessment Timeline
Grading Rubric
- A (90-100): Exceptional work, exceeds expectations
- B (80-89): Good work, meets expectations
- C (70-79): Adequate work, basic requirements met
- D (60-69): Below expectations, needs improvement
- F (Below 60): Unsatisfactory, major revisions required
Support Available
- • Office hours: MW 2-4pm
- • Writing center support
- • Peer review sessions
- • Online resources