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Research Methodology Course
More than 2 million students worldwide

Research Methodology Course

4.8

Master every stage of the research process, from formulating precise questions to publishing your findings. This course gives you a rigorous, practical foundation in research methodology across quantitative, qualitative, and mixed methods approaches. Whether you're writing a thesis, conducting applied research, or pursuing funding, you'll have the tools to do it right.

Dedika for Business

What you will learn:

You will learn how to identify and narrow research problems, build conceptual frameworks, and craft well-formed research questions and hypotheses. The course covers systematic literature review strategies, research design selection, and sampling techniques for both quantitative and qualitative studies. You will design and pilot-test data collection instruments, then analyze your data using appropriate statistical and interpretive methods. Topics also include research ethics, academic integrity, grant writing, and structuring reports for publication. By the end, you will be equipped to plan, execute, and communicate a complete research study.

How you study in practice Research Methodology Course

How you practise Research Methodology Course

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Course Content

8 Chapters • 35 LessonsDuration between 4 and 360 hours (you decide)

Chapter 1See details

Foundations of Research Methodology

  • Lesson 1 • The Research Process Overview

    Maps the end-to-end research cycle from problem identification to dissemination. Provides a roadmap that frames every subsequent chapter in the course.

  • Lesson 2 • Nature and Purpose of Research

    Defines research, its goals, and its role in advancing knowledge across disciplines. Establishes the vocabulary and mindset needed for all subsequent methodological study.

  • Lesson 3 • Research Paradigms and Worldviews

    Introduces positivism, interpretivism, pragmatism, and critical theory as philosophical foundations. Connects paradigm choice to methodology selection throughout the course.

  • Lesson 4 • Types of Research

    Classifies research by purpose, approach, and time horizon. Students use these distinctions to select appropriate designs in later chapters.

Chapter 2See details

Formulating Research Problems and Questions

  • Lesson 1 • Identifying and Narrowing a Research Problem

    Guides students from broad topic areas to specific, researchable problems. Connects problem clarity to feasibility and significance of the study.

  • Lesson 2 • Developing Hypotheses and Objectives

    Explains the role of hypotheses in quantitative research and objectives in qualitative work. Students practice translating questions into testable or explorable statements.

  • Lesson 3 • Crafting Research Questions

    Teaches criteria for well-formed research questions aligned with paradigm and purpose. Strong questions directly shape design choices covered in later chapters.

  • Lesson 4 • Conceptual and Theoretical Frameworks

    Distinguishes conceptual maps from formal theoretical frameworks and shows how each guides inquiry. Frameworks anchor variable selection and interpretation in subsequent chapters.

Chapter 3See details

Conducting and Synthesizing Literature Reviews

  • Lesson 1 • Purpose and Types of Literature Reviews

    Explains why literature reviews are essential and distinguishes narrative, systematic, and scoping reviews. Sets expectations for the depth and rigor required in academic research.

  • Lesson 2 • Critical Appraisal of Sources

    Teaches frameworks for evaluating methodological quality, credibility, and relevance of sources. Critical appraisal skills prevent weak evidence from undermining the research argument.

  • Lesson 3 • Searching and Managing Sources

    Covers database search strategies, Boolean operators, and reference management tools. Efficient source management directly supports the synthesis tasks in later sections.

  • Lesson 4 • Synthesizing and Writing the Review

    Moves from annotation to thematic synthesis and coherent academic writing. Students learn to identify gaps that justify their own study.

Chapter 4See details

Research Design and Strategy

  • Lesson 1 • Writing the Research Design Rationale

    Guides students in articulating and defending design choices in a written proposal section. Connects design decisions back to the research questions and paradigm established earlier.

  • Lesson 2 • Qualitative Research Designs

    Introduces phenomenology, grounded theory, ethnography, case study, and narrative inquiry. Each design is linked to specific epistemological assumptions and data collection methods.

  • Lesson 3 • Core Research Design Concepts

    Defines research design as the logical plan linking questions to conclusions. Establishes validity, reliability, and rigor as design evaluation criteria used throughout the course.

  • Lesson 4 • Mixed Methods Research Designs

    Explains convergent, explanatory sequential, and exploratory sequential mixed designs. Students learn when integration of methods adds value beyond single-approach studies.

  • Lesson 5 • Quantitative Research Designs

    Covers experimental, quasi-experimental, and non-experimental designs with their strengths and limitations. Students match design type to causal or descriptive research questions.

Chapter 5See details

Sampling Strategies and Participant Selection

  • Lesson 1 • Non-Probability Sampling Methods

    Explains purposive, snowball, convenience, and quota sampling for qualitative and exploratory work. Students recognize when non-probability methods are appropriate and how to justify them.

  • Lesson 2 • Sample Size Determination

    Teaches power analysis for quantitative studies and saturation principles for qualitative work. Students calculate or estimate required sample sizes for their own research designs.

  • Lesson 3 • Probability Sampling Methods

    Covers simple random, systematic, stratified, and cluster sampling with procedural steps. Students select the method that best balances precision and practical constraints.

  • Lesson 4 • Fundamentals of Sampling

    Defines population, sample, and sampling frame and explains why sampling decisions affect generalizability. Establishes core concepts that underpin all sampling techniques covered next.

Chapter 6See details

Data Collection Methods and Instruments

  • Lesson 1 • Surveys and Questionnaires

    Covers question types, scale construction, and survey administration modes. Well-designed surveys reduce measurement error and improve data quality for analysis.

  • Lesson 2 • Secondary Data and Document Analysis

    Explains how to locate, evaluate, and extract data from existing records, archives, and datasets. Secondary data extends research scope while reducing data collection costs and time.

  • Lesson 3 • Interviews and Focus Groups

    Teaches structured, semi-structured, and unstructured interview design and focus group facilitation. These methods generate rich qualitative data aligned with interpretive research designs.

  • Lesson 4 • Validity and Reliability of Instruments

    Covers face, content, construct, and criterion validity alongside internal consistency and test-retest reliability. Instrument quality directly determines the credibility of findings.

  • Lesson 5 • Observation and Field Methods

    Introduces participant and non-participant observation, field notes, and structured observation schedules. Observation methods capture naturally occurring behavior that self-report cannot access.

Chapter 7See details

Data Analysis: Quantitative and Qualitative

  • Lesson 1 • Qualitative Data Analysis

    Covers thematic analysis, coding procedures, and constant comparative methods for qualitative data. Students develop codebooks and construct themes grounded in participant data.

  • Lesson 2 • Mixed Methods Data Integration

    Explains joint display, meta-inference, and transformation strategies for integrating quantitative and qualitative findings. Integration produces insights neither strand alone can generate.

  • Lesson 3 • Advanced Quantitative Analysis

    Introduces multiple regression, factor analysis, and structural equation modeling for complex research questions. Students interpret outputs and assess model fit and assumptions.

  • Lesson 4 • Preparing and Cleaning Data

    Covers data entry, coding, missing value treatment, and outlier detection before analysis begins. Clean data is a prerequisite for valid quantitative and qualitative analysis.

  • Lesson 5 • Descriptive and Inferential Statistics

    Teaches measures of central tendency, dispersion, and key inferential tests including t-tests, ANOVA, and chi-square. Students select tests based on data type and research question.

Chapter 8See details

Research Ethics, Writing, and Dissemination

  • Lesson 1 • Academic Integrity and Plagiarism

    Defines plagiarism, self-plagiarism, fabrication, and falsification and explains prevention strategies. Integrity standards apply to every stage of writing and publication.

  • Lesson 2 • Research Ethics Principles and Compliance

    Covers informed consent, confidentiality, beneficence, and justice as core ethical principles. Ethical compliance protects participants and ensures research integrity across all designs.

  • Lesson 3 • Structuring the Research Report

    Guides students through IMRaD structure, abstract writing, and section-specific conventions. A well-structured report communicates findings clearly to reviewers and readers.

  • Lesson 4 • Presenting and Publishing Research

    Covers conference presentation design, journal submission processes, and peer review navigation. Dissemination skills extend the impact of completed research beyond the classroom.

Certification

Your valid completion certificate

This course is for you:

  • Graduate students: need structured guidance to complete a rigorous thesis proposal.

  • Research analysts: want to formalize instincts into defensible, replicable methodologies.

  • Healthcare professionals: must evaluate clinical evidence and conduct applied studies.

  • NGO program officers: need to design evaluations that satisfy donor reporting requirements.

  • Career changers entering academia: building credentials through independent research projects.

  • Policy advisors: seeking to ground recommendations in methodologically sound primary evidence.

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