Lecture 3 _ Common Research Methods

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Common Research Methods in HDFS Lecture 3 | HDFS 1300 Development of Contemporary Families Taking notes in your own words (not simply copying word-for-word from the slides) will help you to learn the material. Paraphrasing helps you to ensure you fully understand the information. I also encourage you to practice applying the concepts to real-world situations because you will be required to demonstrate this ability when you complete the lecture quiz. Feel free to reach out to me if you have questions about the material. Key Terms to Understand (Not Simply to Memorize) These are some terms that we will reference during the class period. You will also encounter some of these terms when reading research articles for the class or when reading the book. These are very basic definitions of these terms. (You will learn more in your research methods course.) The Very Basic Terms ● Variable : anything that can vary or change ● Operational definition : a precise description of a variable reflecting how it is measurable ● Sample versus a population o Population : all of the people in a group of interest (i.e., all families in the United States; all families in the world; all dual-income families in the United States) o Sample : a group of participants drawn from the population (not everyone in the population); Example: the dual-income families living in the United States that you successfully recruit for your study ● Hypothesis versus a research question o Hypothesis : a precise, specific, testable statement indicating whether or not changes in one variable will be associated with changes in another variable o Research question : typically, an open-ended question that is less precise than a hypothesis; useful when there is not much known about the topic of interest Terms Related to Research Design ● Longitudinal versus a cross-sectional design o Longitudinal : type of research study in which the same participants are observed/measured over time and data are collected at multiple time points o Cross-sectional : type of research study in which data are collected at one time point and groups are compared 1 HDFS 1300 | Dr. Erica Jordan

● Qualitative versus quantitative data o Qualitative : open-ended, detailed, descriptive data used by the researcher(s) to identify themes o Quantitative : data that are numerical (or that are converted into a numerical format, such as a scale); researchers use for statistical analyses (everything from basic frequencies and percentages to sophisticated statistical models) ● Correlational versus causational o Correlational : a type of research design that illustrates the association between two variables but that does NOT prove one variable is the cause of this association o Causational : a type of research design that illustrates how one variable causes changes in another variable because the researcher has strict controls and has manipulated the independent variable Data Collection Techniques in HDFS ● Case study : in-depth interviews and/or direct observation of one participant or a very small group of participants ● Ethnography : immersing oneself in the environment of the population of interest as much as possible over a relatively long period of time ● Focus group : trained facilitator asks questions to a small group about a specific topic of interest ● Interview, questionnaire, and survey : face-to-face interview, phone interview, or self- report survey/questionnaire; especially helpful if questions have been validated (accurately measures what they should) and tested for reliability (consistently measures what they should) ● Naturalistic observation : carefully recording or notetaking about participants in their own environment (i.e., home, school, workplace, playground, neighborhood) ● Laboratory observation : carefully recording or notetaking about participants in an artificial/researcher-created setting (i.e., lab, apartment setup for observation, Gottman’s “Love Lab,” playground setup for observation) ● Experiment : researcher randomly assigns participants to groups (experimental and control groups) and participants receive different treatments/situations/experiences. Can be in a lab or outside of a lab but MUST involve the manipulation of the variable of interest by the researcher. o Independent variable : the variable that the researcher manipulates (or changes) based on the group/condition the participant is placed in o Dependent variable : the variable that changes based on changes in the independent variable (often thought of as the “outcome” variable, but this term is somewhat debatable) o Control variables : variables that remain the same/constant across all groups/conditions 2 HDFS 1300 | Dr. Erica Jordan

● Natural (or quasi-) experiment : Comparing groups that naturally occur in nature (and are not manipulated by the researcher); Example: comparing child development outcomes in a town that had access to the internet and a town that did not ● Physiological measurements : measuring information about bodily functions (i.e., heart rate, temperature, cortisol level, eye tracking, sweat) ● Secondary data analysis : using data that have already been collected for a previous reason and analyzing it in a different way ● Mixed-methods : combining two or more techniques in a single study Question to Consider Your Answer Theories inform research. Research informs theories. Both can inform practices with real families! Defining Terms for Research Opening Activity: 1. How would you define religiosity? 2. How would you measure it? 3. How would you define marital satisfaction? 4. How would you measure it? 1. How strong someone’s faith is. 2. By how devote someone is in their daily life. For ex: how much does one practice their religion and abide by it. 3. How happy and content one is with their partner, future, environment, and financially. 4. By the frequencies in arguments or feelings of negativity with their partner How do your thoughts compare? I agree with this for the most part. What are operational definitions? Why are they important when conducting research studies? How many ways can you measure a variable? - Operational definitions are clear, precise (not vague), and measurable. - Accurate in the sense that you’ll get similar responses from a multitude of individuals. - a BAD example : “how religious somebody is” - a BETTER example : “religiosity refers to people’s varying tendencies to commit themselves to religious beliefs, principles, and activities - It’s important that variables are clearly defined and someone shows how they measure them to verify the accuracy and validity of the statements - clear summaries of research allow for replication, debate, and ongoing advancement of science - A few measuring ways for religiosity: - self-report survey asking if they are religious - Self-report survey asking how often they pray, attend religious services, etc - Asking whether or not they are a member of a religious group - Observing how much they contribute time or money to religious organizations 3 HDFS 1300 | Dr. Erica Jordan

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