Research Methodology

Research Methodology is one of the three core modules (about a quarter of the course). It is examined in Section I through multiple-choice questions and short answers, and its ideas also turn up whenever a question asks you to judge evidence. The Independent Research Project (IRP) is a school-based task, but the exam tests the methodology behind it.

• Research fundamentals: purpose of research, sampling (methods, group and size), primary and secondary data, qualitative and quantitative data, reliability and validity, and ethics (respect, integrity, privacy and bias).
• Research methods: questionnaires, interviews, observation, case studies and literature reviews: what each is, its strengths and limitations, and when to use it.
• The research process: planning (proposal, time and resource management), conducting (collecting, recording and acknowledging data) and interpreting (presenting, analysing and drawing conclusions).

Research is a planned, systematic way of finding out about something. In CAFS it is used to understand the needs of individuals, groups, families and communities, and to judge whether services and policies meet those needs. Good research starts with a clear research question (what you want to find out) or a hypothesis (a testable statement that predicts a relationship, such as "Young people who work more than 15 hours a week report higher stress than those who work fewer hours").

A research question asks; a hypothesis predicts. A topic ("young people and work") is neither.

Primary and secondary data

• Primary data is collected first-hand by the researcher for the current study, for example the answers to your own questionnaire.
• Secondary data has already been collected and published by someone else, for example an ABS report, a journal article or a website.

Primary data fits your question exactly but takes time to collect. Secondary data is quick to obtain and often based on large samples, but it may be out of date, collected for another purpose or biased. Whether data is primary or secondary depends on who collected it, not on how reliable it is. An official government report is still secondary data for you.

Qualitative and quantitative data

• Quantitative data is numerical or can be counted: percentages, ratings on a scale, hours, yes/no tallies. It is easy to graph and compare.
• Qualitative data is descriptive: words, opinions, feelings and reasons, such as an interview transcript or answers to open-ended questions. It gives depth and explains why.

A rating scale (for example 1 to 5) measures an opinion but produces quantitative data, because the answers are numbers. Many good studies use both kinds: numbers to show how common something is, and words to explain it.

The population is everyone the research is about; the sample is the group actually studied. A sample should be large enough and representative enough that its results can be generalised to the population.

Sample group means who is in the sample (their characteristics). Sample size means how many. A small sample of people who are alike (for example ten of your friends) cannot represent a whole school, let alone all Australians. When a question asks about the effect of sampling, discuss both who and how many, then link to validity.

• Validity: the research measures what it says it measures, and its conclusions are justified by the data. Think _accuracy_.
• Reliability: the research gives consistent results when it is repeated under similar conditions. Think _consistency_.

A bathroom scale that always reads 2 kg too heavy is reliable (consistent) but not valid (wrong). Research can be reliable without being valid, but it cannot really be valid if it is unreliable.

Ways to improve them:

• Use a representative, adequately sized sample (validity).
• Ask clear, neutral questions that actually measure the topic (validity).
• Pilot-test a questionnaire before using it.
• Use the same questions, checklist or procedure for every participant (reliability).
• Repeat observations on different occasions (reliability).
• Use more than one method or source and compare results (triangulation), which strengthens both.

The syllabus names four ethical ideas. Know them and be able to apply them to a situation.

1. Respect: participants take part voluntarily, with informed consent given before the research starts. They know the purpose, what is involved and that they can withdraw at any time. For participants under 18, or people who cannot consent for themselves, a parent, guardian or person responsible should also consent. Respect also means sensitivity to the topic and the participants' wellbeing.
2. Integrity: data is collected, analysed and reported honestly. The researcher does not make up or change results and acknowledges sources (referencing), avoiding plagiarism.
3. Privacy: personal information is kept confidential. Use anonymity or pseudonyms, store data securely and only use it for the agreed purpose.
4. Bias: anything that pushes results one way. Bias can come from leading questions ("Don't you agree that…?"), an unrepresentative sample, the researcher's own opinions or interests, or participants giving answers they think are expected.

Questionnaires

A set of written questions answered by participants, on paper or online. Closed questions (yes/no, multiple choice, rating scales) give quantitative data; open-ended questions give qualitative data.

• Strengths: reach large samples quickly and cheaply; can be anonymous, encouraging honest answers; closed questions are easy to collate and graph.
• Limitations: no chance to clarify questions; low response rates; poorly worded questions give invalid data; people without internet access or with low literacy may be excluded.

Interviews

A conversation in which the researcher asks questions face to face, by phone or by video. Structured interviews use set questions in a set order; unstructured interviews are more like a guided conversation.

• Strengths: in-depth qualitative data; the interviewer can follow up and clarify; suits sensitive or complex topics.
• Limitations: time-consuming, so samples are small; interviewer bias (tone, wording or reactions can influence answers); participants may be less candid face to face.

Observation

Watching and recording behaviour, often with a checklist. In participant observation the researcher joins the group's activities; in non-participant observation the researcher only watches.

• Strengths: records what people actually do rather than what they say they do; useful with young children.
• Limitations: people may change their behaviour when watched; does not reveal reasons or feelings; observer bias; ethical issues if people do not know they are being observed.

Case studies

An in-depth investigation of one person, family, group or organisation, often using several methods (interviews, observation, documents).

• Strengths: rich, detailed understanding of a real situation.
• Limitations: findings cannot easily be generalised; time-consuming; the researcher's interpretation can introduce bias.

Literature reviews

A summary and evaluation of existing published research on a topic.

• Strengths: shows what is already known and where the gaps are; helps refine the research question and methods; gives secondary data to compare with your findings.
• Limitations: sources may be outdated, biased, overseas or of uneven quality, so they must be evaluated.

Choosing a method

Match the method to the question. "How many?" or "how common?" suits a questionnaire. "How do people experience…?" or "why?" suits interviews or a case study. "What do people actually do?" suits observation. Strong research often combines methods.

Planning

• Choose a topic, then narrow it to a clear research question or hypothesis.
• Do a preliminary literature review.
• Write a research proposal: aims, question or hypothesis, methods, sample, ethical considerations, resources and a timeline.
• Manage time and resources: set milestones, book participants early and allow time for things going wrong.

Conducting

• Access secondary sources and record full references.
• Collect primary data consistently and ethically.
• Record data accurately (raw data sheets, recordings with consent, a research diary of decisions and problems).

Interpreting

• Present data in a suitable form: tables; column graphs for comparing categories; pie charts for parts of a whole; line graphs for change over time; quotations and themes for qualitative data.
• Analyse: look for patterns, trends, similarities and differences; compare with the literature.
• Draw conclusions that the data actually supports. A relationship between two things (a correlation) does not prove that one causes the other.
• Acknowledge limitations (for example sample size) and make recommendations.

Question (original, 4 marks): A youth worker wants to know why few young people in her town use the local youth centre. Recommend a research method and justify your choice.

Answer: Semi-structured interviews with about 12 young people aged 14–18 would suit this question. The worker wants to know _why_ young people do not use the centre, so she needs qualitative data about their reasons and feelings, which interviews provide. She can follow up on answers, for example asking what would make the centre more appealing. To reduce bias, she should interview young people who do _not_ use the centre, chosen from different schools, not just regular visitors. Interviews take time, so she could add a short anonymous online questionnaire to check how common the main reasons are across a larger group.

• Defining validity and reliability the wrong way round.
• Calling a rating scale qualitative.
• Thinking an official report is primary data.
• Saying only "the sample is too small" without discussing who was sampled.
• Drawing a cause-and-effect conclusion from survey data that only shows a relationship.
• Listing ethical terms without applying them to the scenario.
• Saying "interviews are more reliable" — interviews give depth, not automatically consistency.

• Command verbs matter. _Outline_ = sketch the main features. _Describe_ = give characteristics and features. _Explain_ = show cause and effect, use "because" and "this means". _Compare_ = similarities and differences. _Evaluate/assess_ = make a judgement with criteria and evidence. _Analyse_ = identify components and the relationships between them.
• Always use the scenario in the question: name the method, the sample and the ethical issue for that situation.
• For a "suitability of a method" question, weigh strengths and limitations for that topic and finish with a judgement.
• Use the terms precisely: validity, reliability, bias, informed consent, sample size, sample group, qualitative, quantitative.

• Groups in Context and Parenting and Caring: questions often give you statistics or survey results about a group or carers. Use research skills to interpret them and judge the evidence.
• Social Impact of Technology option: online questionnaires, data privacy and digital research tools.
• Your IRP: the exam may ask you to draw on your own research experience; use it as a specific example.