Introduction to Scientific Research Course (Level G2)

Lesson 1 • Ethics in Scientific Research

Covers core ethical principles governing research involving humans, animals, and data. Establishes responsible conduct as a prerequisite for credible science.

Lesson 2 • Types of Scientific Research

Surveys descriptive, correlational, experimental, and applied research categories. Helps students match research type to their specific questions.

Lesson 3 • The Scientific Method Overview

Traces the classic observe-hypothesise-test-conclude cycle and its iterative nature. Provides the procedural backbone students will apply throughout the course.

Lesson 4 • Nature and Goals of Science

Defines science as a systematic knowledge-building enterprise and contrasts it with pseudoscience. Anchors the chapter by establishing why methodological rigour is non-negotiable.

Lesson 1 • Reviewing Existing Literature

Teaches systematic searching and critical reading of prior studies to contextualise a new question. Prevents duplication and reveals theoretical frameworks.

Lesson 2 • Developing Testable Hypotheses

Converts research questions into directional and null hypotheses with clear predictions. Prepares students for variable operationalisation and statistical testing.

Lesson 3 • Identifying a Research Problem

Guides students from a general topic to a focused, researchable problem. Connects to the scientific method by grounding inquiry in observable gaps.

Lesson 4 • Writing a Research Proposal Outline

Integrates problem statement, literature context, and hypotheses into a coherent proposal skeleton. Serves as the planning document for subsequent design chapters.

Lesson 1 • Qualitative Research Designs

Introduces phenomenology, grounded theory, case study, and ethnography as structured inquiry approaches. Expands the methodological toolkit beyond numerical data.

Lesson 2 • Mixed-Methods Research Design

Explains how quantitative and qualitative strands are integrated for richer findings. Addresses sequencing, weighting, and rationale for mixing methods.

Lesson 3 • Sampling Strategies

Compares probability and non-probability sampling methods and their impact on representativeness. Directly informs data collection planning in the next chapter.

Lesson 4 • Validity, Reliability, and Bias

Defines internal and external validity, reliability, and common bias types that threaten study quality. Equips students to evaluate and strengthen any design.

Lesson 1 • Observation and Field Methods

Introduces systematic observation, field notes, and participant vs. non-participant roles. Builds direct measurement skills for naturalistic settings.

Lesson 2 • Existing Data and Secondary Sources

Explains how to locate, evaluate, and repurpose archival records, databases, and published datasets. Broadens data options without primary data collection costs.

Lesson 3 • Instrument Validity and Reliability Testing

Applies content, construct, and criterion validity checks alongside reliability coefficients to finalise instruments. Ensures data quality before full-scale collection.

Lesson 4 • Surveys and Questionnaires

Covers question types, response scales, and layout principles for effective survey instruments. Connects to sampling by addressing how delivery mode affects response quality.

Lesson 1 • Regression and Predictive Analysis

Covers simple and multiple linear regression for modelling relationships and making predictions. Extends correlation skills toward explanatory and predictive research goals.

Lesson 2 • Inferential Statistics Fundamentals

Introduces probability, sampling distributions, confidence intervals, and hypothesis testing logic. Bridges descriptive summaries to population-level inferences.

Lesson 3 • Descriptive Statistics

Teaches measures of central tendency, dispersion, and frequency distributions to summarise datasets. Provides the first layer of interpretation before inferential testing.

Lesson 4 • Common Statistical Tests

Applies t-tests, ANOVA, chi-square, and correlation to research scenarios. Students select the correct test based on data type and research question.

Lesson 1 • Organising and Managing Qualitative Data

Covers transcription, data organisation, and software-assisted management of text and media. Establishes orderly data handling as the foundation for rigorous analysis.

Lesson 2 • Other Qualitative Analysis Approaches

Introduces content analysis, narrative analysis, and discourse analysis as alternatives to thematic work. Broadens analytical options for diverse qualitative data types.

Lesson 3 • Thematic Analysis

Applies a six-phase thematic analysis process to identify patterns across coded data. Produces interpretive themes that answer qualitative research questions.

Lesson 4 • Trustworthiness in Qualitative Research

Applies credibility, transferability, dependability, and confirmability criteria to validate findings. Addresses the qualitative equivalent of validity and reliability from Chapter 3.

Lesson 1 • Citation, Referencing, and Academic Integrity

Applies major citation styles and plagiarism-avoidance strategies to produce properly attributed work. Reinforces the ethical standards established in Chapter 1.

Lesson 2 • Scientific Writing Fundamentals

Covers precision, objectivity, conciseness, and discipline-specific conventions in academic prose. Strong writing skills are essential for all report sections that follow.

Lesson 3 • Data Visualisation and Tables

Teaches principles for selecting and designing figures, charts, and tables that accurately represent data. Effective visuals enhance comprehension and support written findings.

Lesson 4 • Interpreting Results in Context

Guides students to connect findings back to hypotheses, theoretical frameworks, and prior literature. Prevents over-generalisation and unsupported claims.

Lesson 1 • Narrative and Scoping Reviews

Distinguishes narrative and scoping reviews from systematic reviews and explains their appropriate uses. Expands synthesis options for broad or emerging research areas.

Lesson 2 • Translating Evidence into Practice

Applies synthesised evidence to real-world decisions, policy recommendations, and future research agendas. Completes the research cycle by connecting findings to action.

Lesson 3 • Critical Appraisal of Research Articles

Applies structured checklists to evaluate study design, methodology, analysis, and conclusions. Builds the evaluative lens needed for evidence-based practise and synthesis.

Lesson 4 • Systematic Review Methodology

Covers PRISMA guidelines, inclusion/exclusion criteria, and data extraction for systematic reviews. Provides a replicable, transparent process for synthesising a body of evidence.