Scientific Research Methods Training

Lesson 1 • Ethics in Scientific Research

Establishes core ethical obligations governing research conduct and reporting. Grounds ethical reasoning in principles of integrity, consent, and harm avoidance.

Lesson 2 • Core Principles of Scientific Reasoning

Covers inductive and deductive logic as tools for building and testing theory. Connects reasoning patterns to hypothesis formation and evidence evaluation.

Lesson 3 • Nature and Purpose of Science

Defines science as a systematic method of knowledge production. Establishes the epistemological basis for all subsequent research design decisions.

Lesson 1 • Identifying a Research Problem

Teaches how to locate gaps in existing knowledge through literature scanning. Connects problem identification to the broader scientific conversation in a field.

Lesson 2 • Conducting a Preliminary Literature Review

Introduces rapid literature scanning to map existing work before deep review. Builds the habit of grounding new questions in prior evidence.

Lesson 3 • Developing Hypotheses

Explains hypothesis structure, directionality, and testability criteria. Links hypothesis formation to deductive reasoning introduced in Chapter 1.

Lesson 1 • Validity and Reliability in Design

Defines internal, external, construct, and statistical validity as design quality criteria. Teaches strategies to build validity and reliability into the design phase.

Lesson 2 • Writing a Research Proposal

Synthesises prior chapter skills into a structured proposal document. Covers problem statement, objectives, design rationale, and ethical considerations.

Lesson 3 • Quantitative vs. Qualitative Approaches

Contrasts the ontological and methodological assumptions of quantitative and qualitative research. Prepares students to justify paradigm choice for their own studies.

Lesson 4 • Mixed Methods Design

Introduces integration strategies that combine quantitative and qualitative strands. Covers convergent, explanatory, and exploratory mixed methods frameworks.

Lesson 1 • Probability Sampling Methods

Covers simple random, stratified, cluster, and systematic sampling techniques. Links each method to conditions under which it maximises representativeness.

Lesson 2 • Defining Populations and Sampling Frames

Clarifies the distinction between target population, accessible population, and sampling frame. Establishes how frame construction affects representativeness.

Lesson 3 • Sample Size Determination

Introduces power analysis and saturation concepts for quantitative and qualitative studies. Teaches students to calculate and justify adequate sample sizes.

Lesson 1 • Measurement and Operationalisation

Defines levels of measurement and links abstract constructs to observable indicators. Builds on hypothesis operationalisation from Chapter 2.

Lesson 2 • Observation and Field Methods

Introduces systematic observation, ethnographic fieldwork, and field note practices. Connects observational data to naturalistic validity in research design.

Lesson 3 • Interviewing Techniques

Teaches structured, semi-structured, and unstructured interview protocols. Develops skills in probing, active listening, and minimising interviewer bias.

Lesson 4 • Survey and Questionnaire Design

Covers question types, response scales, and layout principles for survey instruments. Addresses common design errors that introduce measurement bias.

Lesson 1 • Inferential Statistics and Hypothesis Testing

Introduces probability, sampling distributions, and the logic of null hypothesis significance testing. Connects to hypothesis formulation from Chapter 2.

Lesson 2 • Descriptive Statistics and Data Exploration

Covers measures of central tendency, dispersion, and distributional shape. Establishes data exploration as a prerequisite to inferential analysis.

Lesson 3 • Regression Analysis

Introduces simple and multiple linear regression for prediction and explanation. Covers model assumptions, diagnostics, and interpretation of coefficients.

Lesson 4 • Effect Size and Practical Significance

Distinguishes statistical significance from practical importance using effect size measures. Reinforces the power analysis concepts introduced in Chapter 4.

Lesson 1 • Grounded Theory and Narrative Analysis

Introduces grounded theory as an inductive theory-building method and narrative analysis for story-based data. Expands the analytical toolkit beyond thematic approaches.

Lesson 2 • Ensuring Rigour in Qualitative Research

Covers member checking, triangulation, peer debriefing, and negative case analysis. Builds quality assurance practices into the full qualitative workflow.

Lesson 3 • Thematic Analysis

Covers the six-phase thematic analysis process from familiarisation to reporting. Applies to interview and observational data collected in Chapter 5.

Lesson 4 • Foundations of Qualitative Analysis

Establishes the epistemological basis for qualitative interpretation and rigour criteria. Contrasts qualitative rigour standards with quantitative validity concepts from Chapter 3.

Lesson 1 • Peer Review and Publication Process

Explains the journal submission workflow, peer review types, and responding to reviewer feedback. Prepares students to navigate the publication system strategically.

Lesson 2 • Academic Writing Style and Clarity

Addresses precision, concision, hedging language, and disciplinary voice in scientific prose. Targets common writing errors that weaken manuscript quality.

Lesson 3 • Tables, Figures, and Data Visualisation

Teaches principles of effective visual data presentation aligned with publication standards. Covers table formatting, figure design, and caption writing.

Lesson 4 • Citation, Referencing, and Academic Integrity

Covers major citation styles, reference management tools, and plagiarism avoidance. Reinforces integrity principles established in Chapter 1.