01
Introduction to Experiments
Hypotheses, independent and dependent variables, operationalisation, experimental designs, controls and quasi-experiments are developed through the Dual Coding demonstration and Rosenthal and Jacobson study.
Unit Purpose
Research methodology is the connective tissue of the programme. Students first learn how experiments are designed, sampled, evaluated and conducted responsibly, then apply perspectives to the claims psychologists make. The data-analysis sequence develops correlation, data classification, representation, descriptive statistics, reliability and validity so students can interpret evidence with appropriate caution across all four contexts.
Curriculum Journey
Topics 1–5 establish the core methodology sequence. Topics 6.1–6.5 extend data-analysis understanding for all students and are assessed directly in the HL examination.
02
Sampling Techniques
Target populations, self-selected, opportunity, random and stratified sampling are compared through scenarios that connect representativeness, bias and responsible generalisation.
03
Limitations of Experiments
Internal, external, construct, ecological and population validity are examined alongside confounds, demand characteristics, expectancy effects, placebo effects, social desirability and carryover effects.
04
Ethics in Experiments
Consent and assent, anonymity, withdrawal, deception, protection from undue stress or harm and debriefing are applied to proposals, historical examples and a mock ethics-board review.
05
Perspectives in Psychology
Reductionism and holism, biological and environmental determinism, cultural relativism, free will and responsibility are used to compare explanations and judgments.
6.1
Correlations & Scatterplots
Direction and strength are read from scatterplots while students distinguish correlation from causation and consider bidirectional, third-variable and spurious relationships.
6.2
Data: Predict, Observe, Infer
Students classify levels and forms of data, sources of evidence and study designs before separating what was predicted, what was observed and what can reasonably be inferred.
6.3
Data Representation
Line graphs, bar charts, histograms and box plots are selected and critiqued in relation to data type, research purpose, visual clarity and misleading presentation.
6.4
Descriptive Statistics
Mean, median, standard deviation, quartiles, box plots and statistical significance are interpreted to understand patterns and variation; examination emphasis is on interpretation rather than calculation.
6.5
Reliability & Validity
Inter-rater, test-retest and procedural reliability are evaluated alongside internal, construct, ecological and population validity through applied research scenarios.
Skills Developed
Experimental Design & Causality
Students identify hypotheses, variables, designs, controls and confounds, then judge when an experimental conclusion can—and cannot—support causation.
Sampling & Generalisation
Students compare sampling techniques, identify selection bias and connect representativeness to the population to which findings may responsibly apply.
Validity, Reliability & Bias
Students diagnose threats to measurement and procedure, distinguish forms of validity and reliability, and recommend justified improvements.
Ethics & Responsibility
Students apply ethical principles to realistic proposals and defend decisions that balance scientific value, participant welfare and responsible communication.
Perspectives & Conceptual Thinking
Students examine how reductionism, determinism, culture, free will and responsibility shape explanations and interpretations of behaviour.
Data Interpretation & Exam Communication
Students read data displays and descriptive statistics, separate observation from inference, evaluate claims and communicate evidence with appropriate caution.
Assessment Connections
Research methodology supports the four course contexts; it is not a fifth context. Formal Class Practicals are completed within those contexts rather than inside this Research unit.
Paper 1 — Concepts, Content & Contexts
Research terminology and concepts such as bias, causality, measurement and responsibility support evidence-based responses across the four contexts.
Paper 2 — Practical Knowledge & Research Evaluation
This unit supplies the methodological foundation students use when discussing their four context-based Class Practicals and evaluating an unseen study.
Paper 3 — Data Analysis & Interpretation
The 6.1–6.5 sequence directly prepares students to interpret correlations, data types, graphs, descriptive statistics, reliability, validity, transferability and source evidence.
Unit Activities
These are the activities taught in the uploaded Research sequence. The Dual Coding and Stroop tasks are classroom demonstrations, not formal Class Practicals.
Dual Coding Demonstration & Study Analysis
Students compare words presented with and without images, calculate group means, identify the hypothesis and variables, and analyse Rosenthal and Jacobson’s experiment.
Sampling Scenarios
Eight applied scenarios and a mindfulness-and-sport study require students to select sampling techniques and evaluate representativeness, bias and generalisability.
Confounds, Bias & Construct Validity
Students diagnose flaws in stereotype, mathematics, vocabulary and competition studies, then distinguish extraneous variables from threats to valid conclusions.
Mock Ethics Board
Historical cases, eight proposed studies and a self-esteem manipulation prompt are used to apply ethical principles and justify responsible research decisions.
Perspective Case Analysis
Kenneth Parks, applied scenarios and the Daniel R. profile are interpreted through reductionism, holism, determinism, culture, free will and responsibility.
Scatterplot & Correlation Tasks
Students plot and interpret relationships, critique causal claims and examine the relationship between income and happiness for alternative explanations and bias.
Predict, Observe, Infer Protocol
Sleep, school and mindfulness examples develop accurate classification of data and evidence while separating observations from defensible inferences.
Choosing & Critiquing Graphs
Students select line, bar, histogram or box-plot representations, identify limitations and propose improvements using Paper 3-style prompts.
Stroop Data & Descriptive Statistics
A Stroop-style comparison is used to calculate for understanding, graph results and interpret mean, median, spread, quartiles and statistical significance.
Reliability & Validity Scenarios
Marriage communication, oxytocin and trust, free-throw visualisation, and stress-and-attention studies are evaluated for reliability and validity.
Paper 3 Source Practice
Students complete the supplied culture-and-relationships source paper to integrate data interpretation, methodological evaluation and evidence-based communication.