RSC2601 Research in Social Sciences Exam Notes for Psychology Students: UNISA Foundational Psychology Study Guide

Research in the social sciences is the backbone of psychological knowledge because it explains how evidence is produced, evaluated, and applied. For UNISA psychology students, RSC2601 is especially important because it builds the reasoning skills needed to understand research methods, interpret findings, and judge whether psychological claims are trustworthy. These notes provide a structured, exam-focused guide to the major ideas, concepts, and skills that typically appear in first-year social science research study material.

1. What Research in the Social Sciences Means for Psychology

Research in the social sciences is the systematic process of asking questions about human behaviour, experience, interaction, institutions, and culture. Psychology sits within this broad social science tradition because it studies how people think, feel, and act in social and individual contexts. The key difference between everyday opinion and research is that research follows a planned, transparent, and evidence-based method of inquiry.

1.1 Why psychology students study research methods

Psychology students need research knowledge for several reasons. First, psychological claims in textbooks, media articles, and social media posts often sound convincing but may not be supported by strong evidence. Second, psychology as a discipline depends on empirical investigation, meaning that ideas must be tested against real-world observations. Third, students are expected not only to read research but also to evaluate whether the findings are reliable, valid, ethical, and applicable to real-life settings.

For a first-year psychology student, research knowledge is not just a technical subject. It is a way of thinking. It trains the mind to ask:

What exactly is being measured?
How was the information collected?
Who participated?
Could the results be explained in another way?
Can the findings be trusted and repeated?

This type of questioning is important because psychological research often deals with complex human behaviour that is influenced by multiple factors, including age, gender, culture, language, socioeconomic status, trauma, family environment, and education. A good researcher tries to identify patterns without oversimplifying the lived reality of people.

1.2 Social science research versus everyday observation

Everyday observation can be useful, but it is limited. For example, a student might think, “People who study in groups always perform better,” based on observing a few classmates. That conclusion may be false because the student may have ignored important factors such as the quality of the study group, prior knowledge, motivation, or the difficulty of the course. Research avoids this problem by using planned methods, larger samples, and rules for analysis.

The difference can be summarised as follows:

Everyday observation	Scientific social science research
Based on personal impressions	Based on systematic procedures
Often selective and informal	Uses structured methods and records
Easily influenced by bias	Attempts to reduce bias
May not be repeatable	Designed to be replicable
Produces broad guesses	Produces evidence-based conclusions

This does not mean personal experience is useless. In psychology, lived experience can be a valuable starting point for a research question. However, research turns a personal question into a disciplined investigation.

1.3 Major characteristics of scientific inquiry

Scientific inquiry in the social sciences usually has several features:

Systematic: steps are planned in a logical sequence.
Empirical: claims are based on observation or measurement.
Objective: the goal is to reduce the influence of personal bias.
Replicable: others should be able to repeat the study using the same procedure.
Transparent: the researcher should explain how the study was done.
Theoretical: research is guided by ideas, concepts, and frameworks.
Critical: findings are evaluated rather than accepted uncritically.

Psychology often balances objectivity with sensitivity to context. For example, when studying depression, it is not enough to count symptoms. Researchers must also consider how culture, language, stigma, and access to healthcare shape how people report distress.

1.4 Common research questions in psychology

Psychology research questions often fall into a few broad categories:

Descriptive questions: What is happening? How common is it?
Comparative questions: Are there differences between groups?
Relational questions: Are two or more variables associated?
Causal questions: Does one factor influence another?
Interpretive questions: How do people understand their experiences?

Examples include:

What percentage of first-year students report high academic stress?
Is there a difference in test anxiety between students who live on campus and those who commute?
Is sleep duration related to concentration levels?
Does a stress-management intervention improve exam performance?
How do students describe the emotional experience of entering university?

Each question type suggests a different method. A descriptive question may require a survey, whereas a causal question usually needs an experiment or quasi-experiment.

1.5 The role of theory in research

Theory is a structured explanation of how and why phenomena occur. In psychology, theory helps researchers move beyond isolated facts. For instance, a theory of social support may explain why people with stronger peer networks cope better with stress. A theory of memory may explain why rehearsal improves recall. A theory of motivation may explain why intrinsic goals support persistence more effectively than external pressure.

Research and theory are linked in two directions:

Theory guides research by suggesting what to investigate.
Research tests theory by checking whether predictions are supported.

A strong theory is useful because it is clear, logical, and open to testing. A weak theory is vague and cannot be meaningfully examined. In exam questions, it is often important to distinguish between a theory, a hypothesis, and a finding. A theory is the broader explanatory framework; a hypothesis is a testable prediction; a finding is the result of a study.

2. Research Process, Problems, and Literature Review

A research project in the social sciences follows a sequence of connected steps. Although real studies sometimes move back and forth between steps, the general process remains fairly stable: identify a problem, review the literature, develop a question, choose a method, collect data, analyse the data, interpret results, and report findings. For psychology students, understanding this process is essential because exam questions often ask not only what the steps are, but also why each step matters.

2.1 From curiosity to a research problem

Research usually begins with curiosity. A student may notice that many classmates report stress before exams, or that some students who work part-time seem to struggle with attendance. Curiosity becomes a research problem when the issue is narrowed into something specific, measurable, and researchable.

A research problem should be:

Relevant to psychology or the social sciences
Specific rather than vague
Feasible within available time, resources, and access
Ethically acceptable
Researchable using appropriate methods

For example, “student stress” is too broad. A better problem would be “the relationship between hours of sleep and perceived stress among first-year psychology students at a South African university.” This version identifies the population, the variables, and the context.

2.2 Literature review and why it matters

A literature review is a careful examination of existing research and scholarly writing on a topic. It prevents duplication, highlights gaps in knowledge, and shows what is already known. In psychology, literature reviews are especially important because human behaviour is complex and no single study can answer every question.

A good literature review does more than list sources. It:

compares findings from different studies,
identifies consistent patterns,
notes disagreements or contradictions,
evaluates the quality of evidence,
shows how the current study fits into the field.

Suppose a student wants to study academic procrastination. The literature review may show that procrastination is linked to poor time management, low self-regulation, perfectionism, and anxiety. It may also reveal that previous studies mostly used students from high-income countries, creating a gap for research in South African contexts. That gap can justify the new study.

2.3 Sources used in a literature review

Psychology students should distinguish between source types:

Primary sources: original research articles reporting new data
Secondary sources: reviews, summaries, and textbooks
Tertiary sources: encyclopedias, dictionaries, and general reference works

Primary sources are most valuable for research because they show how the knowledge was produced. Textbooks are useful for background understanding, but they may simplify debates or omit methodological detail. In exam preparation, students should practice reading abstracts, method sections, results, and discussion sections of journal articles.

2.4 Research questions and hypotheses

A research question is a clear question the study aims to answer. A hypothesis is a tentative, testable statement predicting an expected relationship or difference.

Examples:

Research question: Is there a relationship between social media use and sleep quality among university students?
Hypothesis: Higher social media use is associated with poorer sleep quality among university students.
Research question: Do students who attend peer tutoring sessions score higher than those who do not?
Hypothesis: Students who attend peer tutoring sessions will score higher on the test than students who do not attend peer tutoring sessions.

Hypotheses can be:

Directional: predicting the direction of the effect
Non-directional: stating that a difference or relationship exists without specifying direction
Null: stating that there is no significant relationship or difference

The null hypothesis is central to statistical testing because researchers usually begin by assuming no effect and then test whether data provide enough evidence to reject that assumption.

2.5 Variables and operationalisation

A variable is any characteristic that can take different values. Psychological research depends on clear variables because concepts such as stress, intelligence, self-esteem, prejudice, or resilience are not directly visible. They must be operationalised, meaning defined in terms of how they will be measured.

For example:

“Stress” could be operationalised as a score on a perceived stress scale.
“Sleep quality” could be measured by self-report ratings or hours slept.
“Academic performance” could be measured by average marks or examination scores.

Operationalisation matters because the same concept can be measured in more than one way. If a study defines depression using a clinical interview, the findings may differ from a study that uses a brief screening scale. Students must therefore pay attention to definitions in research reports.

2.6 Sampling and the problem of representativeness

Researchers cannot usually study everyone in the population, so they use samples. A sample is a smaller group drawn from the larger population. Ideally, the sample should represent the population well.

Common sampling methods include:

Random sampling: every member has an equal chance of being selected
Systematic sampling: selecting every nth person from a list
Stratified sampling: dividing the population into subgroups and sampling within each
Convenience sampling: using available participants
Purposive sampling: selecting participants with specific characteristics
Snowball sampling: using participants to recruit others

In psychology, convenience sampling is common because it is practical, but it limits generalisation. For instance, if a study on student anxiety uses only psychology students from one campus, the findings may not apply to students from rural colleges, working adults, or older distance learners.

A useful exam distinction is between:

Population: the full group of interest
Sample: the subset actually studied
Sampling frame: the list or source from which participants are selected

2.7 Ethics at the planning stage

Ethics should be considered before a study begins, not after data are collected. A research proposal should anticipate risks and explain how participants will be protected. In psychology, ethical issues often involve emotional discomfort, privacy, power relationships, and informed consent. A study on trauma, for example, may trigger distress, so the researcher must plan for support and referral if needed.

Common ethical principles include:

respect for persons,
voluntary participation,
informed consent,
confidentiality,
protection from harm,
fairness in recruitment,
the right to withdraw.

Ethics is not only about following rules. It is about recognising that research involves real people, not just data points.

3. Research Designs, Methods, and Data Collection

Research design is the blueprint of a study. It determines how questions are answered, how participants are selected, what data are collected, and how conclusions are drawn. In psychology, the choice of design affects whether the study can describe a phenomenon, compare groups, explore relationships, or test causality. Understanding design is crucial because many exam questions require students to identify the best method for a given research problem.

3.1 Quantitative, qualitative, and mixed methods

Research in the social sciences is often divided into three broad approaches:

Quantitative research

Quantitative research uses numbers, measurements, and statistical analysis. It is useful for testing hypotheses, comparing groups, and examining relationships between variables. Examples include surveys with rating scales, experiments, and structured observational studies.

Qualitative research

Qualitative research focuses on meaning, experience, and interpretation. It uses interviews, focus groups, observations, and textual data to understand how people make sense of their lives. In psychology, qualitative methods are useful when the goal is to understand subjective experience, cultural context, or complex social processes.

Mixed methods research

Mixed methods combines quantitative and qualitative approaches in one study. This can provide a fuller understanding than either method alone. For example, a study might measure stress levels numerically and then conduct interviews to explore how students explain their stress.

Each approach has strengths:

Quantitative research offers comparability and general patterns.
Qualitative research offers depth and context.
Mixed methods can triangulate findings and improve understanding.

3.2 Descriptive, correlational, and experimental designs

Descriptive design

Descriptive research describes what exists. It does not attempt to manipulate variables or prove causation. Common forms include surveys, case studies, and observational studies. A descriptive study might report the percentage of students who feel overwhelmed during exams.

Correlational design

Correlational research examines whether variables are related. It can show whether high levels of one variable tend to occur with high or low levels of another. However, correlation does not prove causation. If stress and poor sleep are correlated, it is not automatically clear whether stress causes poor sleep, poor sleep causes stress, or a third factor causes both.

Experimental design

Experimental research tests cause-and-effect relationships by manipulating an independent variable and observing its effect on a dependent variable. A classic experiment might compare students who receive a mindfulness intervention with a control group that does not. If the intervention group shows lower stress after the program, the researcher may infer a causal effect, provided the design is strong.

The relationship between design and inference can be shown as follows:

Design	Main purpose	Can show causation?	Typical example
Descriptive	Describe a phenomenon	No	Survey of study habits
Correlational	Identify relationships	No	Stress and sleep study
Experimental	Test effects	Yes, with control	Mindfulness intervention
Qualitative	Interpret experience	Not in statistical sense	Interviews about exam anxiety

3.3 Independent and dependent variables

In experiments, the independent variable is the factor the researcher changes or compares, and the dependent variable is the outcome being measured.

Example:

Independent variable: type of study strategy used
Dependent variable: test performance

If students are assigned to either a retrieval-practice group or a rereading group, and their test scores are compared, the study strategy is the independent variable and performance is the dependent variable.

It is important not to confuse variables with labels. The independent variable is not always something the researcher physically manipulates in the real world; sometimes it is a pre-existing grouping variable such as gender, year of study, or exposure to a programme. In that case, the design may be quasi-experimental rather than fully experimental.

3.4 Reliability and validity

Measurement quality is central to research. A study can have a beautiful design but weak measures, producing misleading results.

Reliability

Reliability refers to consistency. A reliable measure gives similar results under similar conditions. Types of reliability include:

Test-retest reliability: stability over time
Internal consistency: items on a scale measure the same construct
Inter-rater reliability: different observers agree in their ratings

Validity

Validity refers to whether a measure actually assesses what it claims to measure. Types include:

Content validity: covers the full range of the concept
Construct validity: truly measures the theoretical construct
Criterion validity: corresponds with an external criterion
Face validity: appears to measure the concept on the surface

A scale can be reliable without being valid. A bathroom scale that always shows 3 kilograms too much is reliable but not valid. In psychology, a questionnaire that consistently measures the wrong aspect of stress would also be unreliable in usefulness, even if internally consistent.

3.5 Data collection methods

Different research questions require different methods.

Surveys and questionnaires

Surveys are efficient for collecting data from many participants. They can measure attitudes, behaviours, beliefs, and demographic variables. However, self-report data may be affected by social desirability, memory errors, or misunderstanding of questions.

Interviews

Interviews allow researchers to ask open-ended questions and probe responses in detail. They are useful for studying experiences, perceptions, and meanings. Structured interviews use fixed questions; semi-structured interviews allow flexibility; unstructured interviews are more conversational.

Focus groups

Focus groups use guided group discussion to explore shared views and differences. They are especially useful for understanding social norms and collective experiences, but dominant voices can influence the discussion.

Observation

Observation involves watching behaviour in natural or controlled settings. It may be participant observation or non-participant observation. Observational research is useful when people may not accurately report what they do, such as helping behaviour or classroom interactions.

Case studies

Case studies examine one individual, group, event, or institution in depth. They are valuable for rare or unusual cases, but generalisation is limited.

3.6 Choosing the right design

Choosing a design depends on the research question, ethical concerns, available time, and resources. A useful decision process is:

Define the research problem clearly.
Decide whether the goal is description, explanation, comparison, or interpretation.
Determine whether the data should be numerical, textual, or both.
Consider feasibility, access, and ethics.
Select the method that best fits the question.
Plan how data will be analysed.

A study on exam stress among first-year psychology students could be handled in several ways:

a survey to measure prevalence,
an experiment to test a stress-reduction technique,
interviews to understand lived experience,
mixed methods to combine both prevalence and personal meaning.

A strong researcher does not choose a method simply because it is fashionable. The method must fit the question.

4. Data Analysis, Interpretation, and Research Quality

Once data are collected, they must be organised, analysed, and interpreted carefully. This stage is often where students lose marks in exams because they confuse descriptive statistics with inferential statistics, or they interpret findings too strongly. In psychology, the analysis phase is critical because it transforms raw observations into conclusions that can support, challenge, or refine theory.

4.1 Descriptive statistics

Descriptive statistics summarise data in a clear and manageable form. They help researchers understand the general pattern before making deeper conclusions.

Common descriptive statistics include:

Mean: average value
Median: middle value
Mode: most frequent value
Range: spread from lowest to highest
Standard deviation: average spread around the mean
Percentage: proportion out of 100

Example: if a group of students has stress scores of 12, 14, 14, 16, and 18, the mean helps describe the average stress level, while the range shows how spread out the scores are.

Graphs and tables also help present descriptive information:

bar charts,
histograms,
line graphs,
pie charts,
frequency tables.

In psychology, descriptive statistics are useful because they provide an initial picture of a sample, such as average age, gender distribution, average test scores, or symptom frequency.

4.2 Inferential statistics

Inferential statistics allow researchers to draw conclusions about a population based on a sample. They test whether observed differences or relationships are likely to be real or due to chance.

Common inferential tests include:

t-tests for comparing two groups,
ANOVA for comparing more than two groups,
chi-square tests for categorical data,
correlation analysis for relationships,
regression analysis for prediction,
non-parametric tests when assumptions are not met.

A key concept is statistical significance, often represented by a p-value. A result is statistically significant when the observed pattern is unlikely to have occurred by chance alone, given a chosen threshold such as 0.05. However, statistical significance does not automatically mean practical importance. A tiny effect may be statistically significant in a large sample but meaningless in everyday life.

4.3 P-values, effect sizes, and practical significance

Many students think p-values tell the whole story. They do not. A p-value helps judge whether an effect is likely to be due to random variation, but it does not show how large or meaningful the effect is.

P-value: probability of obtaining the data, or more extreme data, if the null hypothesis were true
Effect size: how strong or large the effect is
Practical significance: whether the result matters in real-world terms

Example: if a mindfulness programme reduces exam anxiety by only 1 point on a 100-point scale, the result may be statistically significant but not practically useful. If another programme reduces anxiety by 15 points and improves concentration, it may have stronger practical value.

Psychology students should therefore interpret findings carefully and avoid overclaiming.

4.4 Correlation and causation

One of the most tested ideas in research methods is the difference between correlation and causation. Correlation means two variables vary together. Causation means one variable produces change in another.

A correlation does not prove causation because:

the direction of influence may be reversed,
a third variable may be responsible,
the relationship may be coincidental or indirect.

For example, suppose higher stress is correlated with lower academic performance. This does not prove that stress causes poor performance. Poor performance could increase stress, or a third variable such as lack of sleep, financial pressure, or poor study environment could affect both.

To establish causation, researchers need evidence of:

temporal order,
covariation,
elimination of alternative explanations.

Experiments help because they control conditions and isolate effects better than correlational studies.

4.5 Internal validity and external validity

Two major concerns in research quality are internal validity and external validity.

Internal validity

Internal validity refers to whether the study accurately shows that the independent variable caused the observed effect. Threats include:

confounding variables,
selection bias,
history effects,
maturation,
testing effects,
instrumentation changes,
attrition.

External validity

External validity refers to how well findings generalise beyond the study sample and context. A study may be internally strong but externally limited. For example, research conducted only with urban university students may not generalise to rural youth or older adults.

A well-designed study tries to balance these forms of validity. Highly controlled experiments may improve internal validity but reduce realism. Naturalistic studies may improve realism but weaken control. This trade-off is central in social science research.

4.6 Bias and how it affects research

Bias can enter research at many stages. In psychology, common forms include:

sampling bias: sample not representative,
response bias: participants answer in socially desirable ways,
researcher bias: expectations influence interpretation,
confirmation bias: looking only for evidence that supports one’s belief,
attrition bias: certain participants drop out systematically.

Reducing bias requires:

clear procedures,
randomisation where possible,
blinding in some studies,
careful wording of questions,
neutral data recording,
transparent reporting.

4.7 Interpreting findings responsibly

Good interpretation is cautious and evidence-based. A researcher should ask:

What do the results actually show?
What do they not show?
Are there alternative explanations?
How strong is the evidence?
Do the conclusions match the data?

For example, if students who attend counselling report lower stress, it would be wrong to conclude immediately that counselling alone caused the reduction unless the design supports that claim. Students who choose counselling may already differ in motivation, openness, or stress severity. Interpretation must match the method.

A useful exam habit is to separate:

results: what the data show,
discussion: what the results mean,
conclusion: the final answer to the research question.

4.8 Assessing quality in published studies

When evaluating an article, psychology students should consider:

Was the research question clear?
Was the sample appropriate?
Were ethical issues addressed?
Were the measures reliable and valid?
Was the design suited to the question?
Were statistics reported correctly?
Are the conclusions justified?
Are the limitations acknowledged?

A strong study does not need to be perfect, but it should be honest about its limits. Research quality is judged not only by results, but by methodological integrity.

5. Ethics, Critical Thinking, and Exam Application

Ethics and critical thinking are inseparable in social science research. Ethics protects participants, while critical thinking protects the discipline from weak arguments, misleading claims, and careless conclusions. For psychology students at UNISA, these skills are especially important because research ethics, evidence evaluation, and application of findings often appear in examination questions and assignments.

5.1 Core ethical principles in psychology research

Ethical research respects human dignity and minimises harm. Several principles are especially important in psychology:

Informed consent

Participants should know the purpose of the study, what they will do, possible risks, and their rights before agreeing to participate. Consent must be voluntary, not forced or manipulated.

Voluntary participation and right to withdraw

People should be free to refuse participation or leave the study at any time without penalty. This is vital when the researcher has power over participants, such as in a classroom or workplace context.

Confidentiality and anonymity

Confidentiality means participant information is protected and not shared in identifiable form. Anonymity means even the researcher cannot link data to a participant’s identity. In many studies, confidentiality is more realistic than full anonymity.

Protection from harm

Research should not expose participants to unnecessary physical, emotional, psychological, or social harm. If sensitive topics are studied, the researcher should anticipate distress and provide support or referrals where appropriate.

Debriefing

If deception is used, participants should be informed afterward about the true purpose and any misleading elements, provided that ethical approval allows this and no harm results from disclosure.

Justice and fairness

Participants should not be exploited. Risk and burden should be distributed fairly, and vulnerable groups should not be targeted simply because they are easy to access.

5.2 Ethical dilemmas in social science research

Ethical principles are often clear in theory but difficult in practice. For example, a study on prejudice may need participants to express socially sensitive views. A study on trauma may risk distress but also produce knowledge that could improve support services. A study in a university setting may involve students who feel pressured to participate because the researcher is also a lecturer or tutor.

Common dilemmas include:

balancing privacy with detailed reporting,
deciding how much deception is acceptable,
managing vulnerable participants,
handling disclosures of harm or illegal activity,
preventing coercion in recruitment.

In psychology, ethical research requires sensitivity, humility, and planning. The question is not only “Can the study be done?” but “Should it be done in this way?”

5.3 Critical thinking and research literacy

Critical thinking is the ability to assess evidence logically and fairly. Research literacy means being able to read a study and understand how it works. Together, these skills help psychology students avoid common mistakes such as:

assuming that all research is equally strong,
confusing correlation with causation,
trusting a result because it is statistically significant,
believing a study because it confirms personal beliefs,
dismissing findings without reading the method.

A critical thinker asks:

What is the claim?
What evidence supports it?
How was the evidence produced?
What are the limitations?
What other explanations exist?
How applicable is the finding to the real world?

This habit is especially valuable in psychology, where popular claims about intelligence, personality, relationships, trauma, and mental health can spread quickly without strong evidence.

5.4 Applying research to psychological practice

Research in the social sciences becomes meaningful when it informs practice. In psychology, research can influence:

counselling approaches,
mental health interventions,
educational support,
workplace wellbeing strategies,
community programmes,
public health messages.

However, application should be careful. A technique that works in one setting may not work in another. An intervention developed in one cultural context may need adaptation before use in South Africa. Students should therefore think about transferability, cultural relevance, and local constraints.

For example, a stress-reduction programme based on expensive technology may be less realistic in under-resourced environments than one based on simple routines such as time management, peer support, and relaxation exercises. Research application is strongest when it is both evidence-based and context-sensitive.

5.5 Common exam pitfalls and how to avoid them

Students often lose marks because they:

define concepts too vaguely,
mix up reliability and validity,
confuse sample and population,
treat correlation as causation,
describe a method without explaining why it is appropriate,
write general opinions instead of research-based answers,
ignore ethics in questions that clearly require it.

A strong exam answer should do more than list definitions. It should connect concepts. For example, if asked about an experiment, mention:

manipulation of the independent variable,
measurement of the dependent variable,
control of extraneous variables,
ethical safeguards,
possible limitations in generalisation.

If asked about a survey, mention:

sampling,
questionnaire design,
response bias,
reliability and validity,
ethical consent and confidentiality.

5.6 A compact revision framework

A useful way to revise RSC2601-type material is to remember five linked questions:

What is the problem?
What does the literature already show?
Which method fits best?
What do the data mean?
What are the ethical and practical implications?

This framework keeps the entire research process connected. Psychology research is not only about producing results. It is about producing trustworthy knowledge that can improve understanding of behaviour and support human wellbeing.

5.7 Final high-yield summary for psychology students

For exam purposes, the most important ideas in research in the social sciences are the following:

Research is systematic, empirical, and theory-driven.
Psychology relies on research because it studies behaviour scientifically.
A good research problem is specific, feasible, and ethical.
Literature reviews identify what is known and where gaps remain.
Hypotheses are testable predictions; theories are broader explanations.
Sampling affects how well findings represent the population.
Quantitative, qualitative, and mixed methods serve different purposes.
Experiments are strongest for causal claims, but not every question needs an experiment.
Reliability and validity determine measurement quality.
Descriptive and inferential statistics serve different functions.
Correlation is not causation.
Ethics protects participants and strengthens research integrity.
Critical thinking is essential for evaluating claims and applying evidence responsibly.

When these ideas are understood together, research methods become more than an isolated module. They become the foundation for studying psychology as a disciplined, ethical, and evidence-based science.