PEPC 011 - Field Methods Of Psychology PDF

PEPC 011 - Field Methods of Psychology Ray-Jun Manglicmot | PSY3A | TThSat | 5-9pm CHAPTER 1: PSYCHOLOGY AS A SCIENCE WHAT IS PSYCHOLOGY? Trained observers would report on the contents of...

PEPC 011 - Field Methods of Psychology Ray-Jun Manglicmot | PSY3A | TThSat | 5-9pm CHAPTER 1: PSYCHOLOGY AS A SCIENCE WHAT IS PSYCHOLOGY? Trained observers would report on the contents of their own immediate states of Psychology is the scientific study of mental consciousness. processes and behavior. The consciousness model was later renamed It is interested in using the scientific method structuralism by one of his students, Edward to understand how living things think, feel, and Titchener. act. Structuralism sought to identify the components of the conscious mind. Psychology comes from the Greek words “Psyche”, meaning mind, and “Logos”, meaning William James (1842-1910) the study of. He is the first major American psychologist. People often confuse psychology with He developed an approach to Psychology psychiatry because psychiatry is a branch in known as functionalism. the field of Psychology. Functionalism deals with how the conscious Psychiatry is a branch of medicine practiced mind helps humans survive and successfully by physicians concerned with the diagnosis adapt to their environment. and treatment of psychological disorders. Psychiatrists complete medical school and Sigmund Freud (1856-1939) obtain an MD. Psychologists complete graduate school and He is the founder of psychoanalysis. obtain a PhD or a PsyD. He developed an approach to psychology through clinical practice. EARLY PIONEERS OF PSYCHOLOGY He developed a theory that all human behavior is determined by hidden or unconscious Wilhelm Wundt (1832-1920) motives and desires that are sexual in nature. He is the world’s first psychologist. He developed therapy techniques and He developed a method of studying known as personality tests designed to reveal hidden or introspection. unconscious thought (ex: dream analysis, In introspection… resistance analysis,object relations therapy, THE PSYCHOANALYSIS AND BEHAVIORIST etc.) PERSPECTIVES STILL INFLUENCE THEORY AND RESEARCH. John Watson (1878-1958) Psychoanalysis In explaining personality, it downplays Freud’s He is the founder of behaviorism. emphasis on sexual drives and emphasizes He said that psychology should study cultural experience instead. observable behavior. It rejects Freud’s view that personality development is complete by age 5. Instead, it The underlying philosophy is known as logical accepts Erikson’s view that personality is positivism. continually shaped and changed. It states that all knowledge should be expressed in terms that can be verified Behaviorism empirically or through direct observation. It was founded by B.F. Skinner (1904-1990). It sought to describe, explain, predict, and It stressed the role of consequences in control behavior. controlling behavior. People and other animals tend to repeat behaviors that are followed Women and ethnic minorities faced by positive consequences and tend to avoid discrimination as pioneers in psychology. behaviors that bring negative consequences. Mary Calkins HUMANISTIC PSYCHOLOGY AND POSITIVE PSYCHOLOGY HIGHLIGHT PERSONAL She was the first female president of the GROWTH American Psychological Association. Humanistic psychology Margaret Washburn It emphasizes people’s innate capacity for personal growth and their ability to make She was the first woman to receive a PhD in conscious choices. psychology. Its pioneers are Carl Rogers (1902-1970) and Abraham Maslow (1908-1970) George Sanchez (1906-1972) Positive Psychology He was an early pioneer in educational and It is a scientific approach to studying optimal cultural psychology. human functioning that asserts that the normal functioning of human beings cannot be CONTEMPORARY PERSPECTIVES AND AREAS accounted for with purely negative OF SPECIALIZATION (problem-focused) terms. COGNITIVE PSYCHOLOGY FOCUSES ON HOW THE SOCIOCULTURAL PERSPECTIVE STUDIES THE MIND ORGANIZES AND INTERPRETS HOW BEHAVIOR IS SHAPED BY SOCIAL AND EXPERIENCES. CULTURAL FORCES. Cognitive Psychology Sociocultural Perspective It comes from the Latin phrase “to know”. It is an approach to psychology that It is an approach that attempts to understand emphasizes social and cultural influences on behavior by studying how the mind organizes behavior. perceptions, processes information, and interprets experiences. Culture It refers to the total lifestyle of people THE NEUROSCIENCE PERSPECTIVE FOCUSES from a particular social grouping, including all ON THE NERVOUS SYSTEM. the ideas, symbols, preferences, and material objects they share. Neuroscience Perspective It is an approach to psychology that attempts Dynamic Systems Theory to understand behavior and mental processes It is the idea that new forms of behavior by examining the nervous system. emerge from the interactions between people’s biology and their culture and physical EVOLUTIONARY PSYCHOLOGY STUDIES HOW environment. BEHAVIOR IS SHAPED BY NATURAL SELECTION. INDIVIDUALISM AND COLLECTIVISM Evolutionary Psychology Individualism It is an approach to psychology based on the It refers to a philosophy of life stressing the principle of natural selection. priority of personal goals over group goals, a preference for loosely knit social Natural Selection relationships, and a desire to be relatively It is the process by which organisms with autonomous of others’ influences. inherited traits best suited to the environment reproduce more successfully than less Collectivism well-adapted organisms over a number of It refers to a philosophy of life stressing the generations which leads to evolutionary priority of group goals over personal goals, a changes. preference for tightly knit social relationships, and a willingness to submit to the Evolution influence of one's group. It refers to the genetic changes that occur in a species over generations due to natural SEVEN AREAS OF SPECIALIZATION FOR selection. RESEARCH PSYCHOLOGISTS Neuroscience  Developmental Psychology population has an equal chance of being Experimental Psychology chosen. Comparative Psychology (studies similarities and differences in Critical Thinking behavioral organization among living It is the process of deciding what to believe beings, study of animals to find out based and how to act based on careful about humans) evaluation of the evidence. Cognitive Psychology Personality Psychology STAGES IN THE PSYCHOLOGICAL RESEARCH Social Psychology PROCESS FOUR AREAS OF SPECIALIZATION FOR Stage 1: Selecting a Topic and Searching the APPLIED PSYCHOLOGISTS Literature Ideas come from a variety of sources, including existing theories, past research, Clinical Psychology current social events, and personal Counseling Psychology experiences. Industrial/Organizational Psychology Educational and School Psychology Once a topic has been selected, psychologists must not only become knowledgeable about SCIENTIFIC METHOD IN PSYCHOLOGY past research findings in their area of interest, but also keep abreast of recently SCIENTIFIC METHODS MINIMIZE ERROR AND published studies and those reported at LEAD TO DEPENDABLE GENERALIZATIONS. scientific meetings. Scientific Method It refers to a set of procedures used in Stage 2: Developing a Theory and Formulating science to gather, analyze, and interpret Hypotheses Once the research literature has been information in a way that reduces error and digested, a theory is formulated and leads to dependable generalization. hypotheses that can be empirically tested must then be developed. Sample It refers to a group of subjects selected to participate in a research study. Stage 3: Selecting a Scientific Method and Submitting the Study for Ethical Evaluation Research can be conducted in the laboratory Population or in the field, and the psychologist can It refers to all the members of an identifiable employ a variety of methods, including group from which a sample is drawn. correlational, experimental, and case study. Random Selection All institutions seeking federal research It is a procedure for selecting a sample of funding must establish institutional review people to study in which everyone in the boards to evaluate the potential benefits and risks of proposed studies. THE SECOND STAGE INVOLVES DEVELOPING A THEORY AND HYPOTHESIS. Stage 4: Collecting and Analyzing Data and Reporting Results Theory The three basic techniques of data collection It is an organized system of ideas that seeks are self-reports, direct observations, and to explain why two or more events are archival information. related. Data can be analyzed using either descriptive Hypothesis or inferential statistics, with the latter It is an educated guess or prediction about mathematical analysis being the more valuable the nature of things based upon a theory. as it allows researchers to generalize their findings to the population of interest. The Theory-Hypothesis Relationship Psychologists principally report their results The theory provides the foundation for the at professional meeting and by publishing hypothesis. articles in scientific journals. The hypothesis is a specific prediction based THE FIRST STAGE INVOLVES SELECTING A on the theory. TOPIC AND SEARCHING THE LITERATURE. The data is collected to test the hypothesis. If Topics generally come from the following: the data supports the hypothesis, it Someone else’s research strengthens the theory. If the data does not An incident in the daily news support the hypothesis, the theory may need Personal experience to be revised or abandoned. Once a topic is selected, the following In summary, the image demonstrates the occurs: scientific method, which involves formulating a theory, deriving a hypothesis, collecting data, Investigators search the scientific literature and testing the hypothesis to either support to determine whether prior investigations of or refute the theory. the topic exist THE THIRD STAGE INVOLVES SELECTING A Literature uses a number of computer based SPECIFIC METHOD AND OBTAINING IRB databases APPROVAL (ETHICAL EVALUATION). Searching for research literature may be Seek to determine the relationship between thought of as a never-ending endeavor two or more factors known as variables. because it occurs throughout the study Variables whether the data support or do not In scientific research, these are factors that support the research hypothesis can be measured and can vary. Replication Operational Definition It is repeating a previous study’s scientific procedures using different participants in an It is a scientist’s precise description of how a attempt to duplicate findings. variable has been quantified so that it can be measured. Meta-Analysis It is when researchers analyze the findings Replication across many studies. It is the use of statistical techniques to sum It refers to repeating previous study’s up a body of similar studies in order to scientific procedures using different objectively estimate the reliability and overall participants in an attempt to duplicate findings. size of the effect. THE FOURTH STAGE INVOLVES COLLECTING DESCRIPTION IS THE GOAL OF AND ANALYZING DATA AND REPORTING OBSERVATIONAL RESEARCH RESULTS Naturalistic Observation Three Basic Techniques of Data Collection: It is a scientific method that describes how Self-Reports - it measures important people or animals behave in their natural subjective data but it relies of people environment. accurately describing internal stats Direct Observation - it is preferred Participant Observation over self-report by some researchers It is a descriptive method in which a group is Archival Information - accumulated studied from within by a researcher who records from a wide variety of records behavior as it occurs in its natural sources environment. Statistical Analysis: Case Study Descriptive Statistics - Numbers that It is a descriptive scientific method involving summarize and describe the behavior in-depth analysis of a single subject, usually a or characteristics of a particular person. sample or participants in a study Inferential Statistics - mathematical analyses that are used to determine  CORRELATIONAL RESEARCH IS USED TO ANALYZE THE NATURE OF THE Random Assignment RELATIONSHIP BETWEEN VARIABLES. It is the placement of research participants Research is designed to examine the nature into experimental conditions in a manner that of the relationship between two or more guarantees that all have an equal chance of naturally occurring variables. being exposed to each level of the independent variable. Survey Experimental Condition It is a structured set of questions or statements given to a group of people to It is the condition in an experiment whereby measure their attitudes, belief, values, or participants are exposed to different levels behaviors. of the independent variable. EXPERIMENTAL RESEARCH DETERMINES Control Condition CAUSE-EFFECT RELATIONSHIP It is the condition in an experiment in which Experimental research is designed to test participants are not exposed to the cause-effect relationships between variables. independent variable. Independent Variable There are no “final truths” in science. It is the experiment variable that the Science is a continually evolving field, and new researcher manipulates. evidence can always challenge existing theories. What we consider "truth" today may Dependent Variable be revised or even overturned by future discoveries. This is the beauty of science: it's It is the experimental variable that is measured open to new ideas and constantly striving for because it is believed to depend on the a more accurate understanding of the world. manipulated changes in the independent variable. CHAPTER 2.1: LAW, THEORY, AND HYPOTHESIS HYPOTHESIS It must be tested many times to examine the validity (truthfulness). It is a possible explanation or solution to a Many times written as an “if… then…” problem. A tentative answer. statement.  THEORY (INFORMATION) LAW (INFORMATION) It is an explanation that is consistent with all A scientific law is a general statement that existing tests and observations. explains how the natural world behaves under It explains why something occurs. certain conditions with no existing exceptions. It is valid as long as there is no evidence to Scientific laws do not explain why something dispute it. Therefore, a theory can be happens. disproved. CHAPTER 2.2: THE MYSTERY TUBE A scientific theory and law cannot become the other. This emphasizes that theories and laws serve different purposes in science. Theories: Explain why things happen. They are based on evidence and can be modified or replaced as new evidence emerges. Laws: Describe what happens under specific conditions. They are often expressed mathematically and are generally considered more certain than theories. The Nature of Scientific Knowledge: Scientific knowledge (including theories and laws) is evidence-based. This means that scientific claims are supported by empirical evidence and rigorous testing. All aspects of scientific work are creative. WHAT DOES THE MYSTERY TUBE TELL US This includes: ABOUT WHAT SCIENCE IS LIKE? Developing questions Designing experiments and procedures Distinguishing Between Theories and Laws: Problem-solving Interpreting data Developing models The Tentative Nature of Science: Both can have exceptions and can change (but don't have to change). This reflects the Neither theories nor laws are absolute. They dynamic nature of science, where new are subject to change as new evidence discoveries can lead to revisions or even the emerges. rejection of established theories or laws. CHAPTER 3: PSYCHOLOGICAL INVESTIGATION EXPERIMENTS Confounding Variable It is a variable that influences both the 3 Types of Experiments independent and dependent variable, making it difficult to determine the true relationship Laboratory Experiments These are highly controlled/artificial. between them. It can distort the results of the study if not Field Experiments controlled for. These include controlled variables in a natural Example, in a caffeine study, a confounding environment. variable could be the amount of sleep participants fot the night before. Quasi (Natural) Experiments There is no control over the independent Extraneous Variable variable. It is “naturally” occurring. It is a variable that is not directly related to the study but could potentially influence the Types of Variables dependent variable. While not as influential as confounding Independent Variable variables, they can still affect the results if It is the variable that is manipulated or not controlled for. changed by the researcher. Example, in a caffeine study, an extraneous Example, in a study on the effects of variable could be the room temperature or caffeine on alertness, the amount of the noise level in the testing environment. caffeine consumed would be the independent variable. EXTRANEOUS VARIABLES Dependent Variable It is the variable that is measured or Participant Variables observed. Independent Measures = Individual Differences Example, in a caffeine study, the level of alertness would be the independent variable. This refers to the fact that when different The same participants repeat the two participants are used in different conditions conditions. In this design, each participant of an experiment, their individual differences experiences both condition 1 and condition 2. can be a source of variation in the results. Counterbalancing Situational Variables It is a technique used in repeated measures designs to control for order effects. It Any feature that could influence a involves altering the order of the conditions participant’s behavior. for different participants to minimize the impact of practice effects and fatigue This includes factors like time of day, noise effects. level, temperature, and even the experimenter’s demeanor, which can affect Practice Effects Participants perform better in the second participants’ responses. condition simply because they have had practice with the task. This can artificially Controlling Extraneous variables inflate the differences between conditions. Single-Blind Participants do not know which condition they Fatigue Effects Participants may perform worse in the are in/ second condition due to boredom, tiredness, Double-Blind or a decline in motivation. Neither participants nor the experimenter know which condition participants are in. Matched Pairs Design Control Groups It is used to control for individual differences A group that does not receive experimental between participants. treatment, serving as a baseline for comparison. Researchers identify pairs of participants who are similar on one or more relevant EXPERIMENTAL DESIGNS variables. Independent Measures Design One member of each pair is randomly assigned to one condition of the experiment, Participants are only in one condition. Each while the other is assigned to the other participant is assigned to either condition 1 or condition. condition 2, but not both. EVALUATION OF EXPERIMENTAL DESIGNS Repeated Measures Design  Laboratory Experiments: Conducted in a controlled environment, allowing for precise control over variables. Field Experiments: Conducted in a natural setting, increasing ecological validity but reducing control over variables. Quasi-Experiments: EXPERIMENTAL METHODS Conducted in natural settings, but with less control over variables, often involving pre-existing groups. Experimental Methods: Independent Measures: Different participants are assigned to different conditions. Repeated Measures: The same participants are exposed to all conditions. Core Concepts: Matched Pairs: Pairs of participants are matched on relevant Independent & Dependent Variables variables and then assigned to different These are the fundamental variables in any conditions. experiment. The independent variable is manipulated by the researcher, and the Sampling Methods: dependent variable is measured to observe the effects of the manipulation. Opportunity: Participants are selected based on availability. Confounding & Extraneous Variables: These are variables that can influence the Random: Participants are selected randomly from a results of an experiment if not controlled. population. Confounding variables systematically affect the dependent variable, while extraneous Snowball: variables have a less predictable impact. Participants recruit other participants. Types of Experiments:  observable, such as "happiness," "intelligence," Stratified: or "social anxiety." Participants are selected from different subgroups within a population. Why is Operationalization Important? Self-Selected: Participants volunteer to participate. Clarity: It ensures that researchers and participants have a shared Ethics: understanding of the concepts being studied. Ecological Validity: Measurability: It allows for the The extent to which findings can be collection of data that can be generalized to real-world settings. analyzed statistically. Reliability: Replication: It enables other The consistency of measurement. researchers to replicate the study and verify the findings. Validity: The accuracy of measurement. NULL VS ALTERNATIVE HYPOTHESIS The image also highlights the importance of Null Hypothesis (H₀) Cause and Effect relationships in experimental research. By manipulating the independent Definition: A statement of no effect or no variable and measuring the effect on the relationship between variables. dependent variable, researchers can establish Assumption: It assumes that any observed causal relationships. difference or relationship is due to chance or random variation. Overall, the image provides a solid foundation for understanding the experimental method, its Alternative Hypothesis (H₁) key components, and the ethical considerations involved in conducting Definition: A statement that contradicts the research. null hypothesis. It proposes that there is a significant difference or relationship between OPERATIONALIZING HYPOTHESIS variables. Operationalization is the process of defining ONE=TAILED VS TWO=TAILED HYPOTHESIS abstract concepts into measurable variables. In simpler terms, it's about taking a vague idea A one-tailed test specifies a direction for the and making it concrete and quantifiable. alternative hypothesis. This is crucial in research, especially when Itt predicts that the effect will be either dealing with concepts that aren't directly greater than or less than a specific value. A two-tailed test does not specify a direction +1.0: Perfect positive correlation (as one for the alternative hypothesis. It simply variable increases, the other increases predicts that there will be a difference proportionally) between groups or conditions. +0.8: Strong positive correlation +0.2: Weak positive correlation When to use which? 0: No correlation -0.2: Weak negative correlation One-tailed Test: Use when you have a strong -0.8: Strong negative correlation prior hypothesis about the direction of the -1.0: Perfect negative correlation (as one effect. variable increases, the other decreases Two-tailed Test: Use when you are unsure proportionally) about the direction of the effect or when you want to be more cautious. Important Note: CORRELATIONS Correlation does not imply causation. Just because two variables are correlated, it Types of Correlation: doesn't mean that one causes the other. There could be other underlying factors Positive Correlation: As one variable influencing both variables. increases, the other variable also increases. For example, the more DATA ANALYSIS hours a student studies, the higher their grades tend to be. Descriptive Statistics Negative Correlation: As one variable It refers to the summary of data to illustrate increases, the other variable patterns and relationships but cannot infer decreases. For example, the more conclusions. time spent watching TV, the lower the grades tend to be. Inferential Statistics Zero Correlation: There is no Statistical tests that allow us to make relationship between the two variables. conclusion in relation to our hypothesis. Mann-Whitney U Test Correlation Coefficients: It tests whether the two groups come from the same population or different populations. Correlation coefficients are numerical values Spearman’s Rho that measure the strength and direction of a It tests whether there is a significant relationship between two variables. They correlation between the two variables. range from -1 to +1:  Qualitative Data It is describing meaning; difficult to analyze. It is more valid – no interpretation needed. Types of Questionnaires Levels of Measurement Open-ended Questions It is for gathering qualitative data. Nominal Data It deals with categorical data. Data is divided Closed Questions into categories without any inherent order. It is for gathering quantitative data. It usually Its measure of central tendency is mode. It involves a fixed choice or rating scales. dictates the most frequently occurring category. Types of Self-Reports Hand-Out Ordinal Data Face-toFace It deals with Ranked Data. Data is ranked in Phone order but the differences between ranks Internet/Email may not be equal. Postal Its measure of central tendency is median. It is when the middle value when data is ranked. Interviews Interval Data Structured vs. Unstructured Interviews: It deals with equidistant data. Data is measured Structured: Predetermined questions, on a scale with equal intervals between values. standardized format. Its measure of central tendency is mean. The Unstructured: Flexible, open-ended average value of the data. questions, allowing for more in-depth Its measure of dispersion is range, the exploration. difference between the highest and lowest Demand Characteristics and Social Desirability: values. Participants may provide answers they think the researcher wants to hear, rather than their true responses. SELF-REPORTS Reliability and Validity Data Types Reliability: Refers to the consistency of a measure. Quantitative Data Questionnaires: Split-Half Method It is numerical data. It is easy to analyze — no (dividing the questionnaire into two meaning. halves and comparing the scores)  Interviews: Replicating the interview OBSERVATION process to ensure consistent results. Types of Observation Validity: Refers to whether a measure actually 1. Participant Observations measures what it claims to measure. Take part in what you’re observing. Open Questions: Encourage more It provides first hand insights, deeper detailed and honest responses. understanding of the group’s culture and Observation of Behavior: Comparing behaviors. self-reported information with actual It has the potential for researcher bias, behavior to assess validity. difficulty maintaining objectivity, and ethical concerns about deception or invasion of SAMPLING privacy. 2. Non-Participant Observations Just observe – no interactions. Opportun People Quick, Not It reduces the risk of influencing the ity who are easy, represen available cheap tative behavior of the group, allowing for more at the objective observation. time. It may cause subtle nuances of behavior, and the researcher’s presence may still affect Random Each Represe Expensiv the group’s behavior. person in ntative e, the gen. time-con Populatio suming Observation Methods n has an equal 1. Disclosed (Overt) Observations chance Participants are aware of the observer. of being It is advantageous as it is more ethical, as chosen participants give informed consent. It is disadvantageous because of the Self-Sele Participa Not Quick, cted nts represen cheap,, Observer Effect wherein participants may volunteer tative easy alter their behavior due to the researcher’s to be in presence, leading to less natural and genuine the observations. sample 2. Undisclosed (Covert) Observations Participants are unaware of the observer Snowball One Allows to Time-con It is advantageous as the observer effect person collect suming tells difficult- cannot take place. others to-locate It is disadvantageous as it raises ethical who tell people concerns regarding privacy and consent. others Types of Observation Data Reliability It is difficult to replicate observation due to 1. Structured Observation confounding variables. Coding scheme is used in recording behavior. Check consistency within observations with A predefined set of categories or behaviors inter-rater reliability (> or = 0.8) are used to record observations. It allows Improve reliability by using good coding for quantitative data collection. scheme. Event Sampling focuses on specific behaviors or events, recording their frequency or Validity duration. If participants know, validity is low. Observer bias is equal to low validity. 2. Unstructured Observation It can be improved by using wider categories Open-ended recording is used when or single=blind technique. researchers focus on capturing the overall Check validity by asking participants context and nuances of the situation. (self-reports). Time Sampling is when an observer records behavior at prescribed intervals. ETHICS Data collected is often qualitative, such as Consent field notes, descriptions, and narratives. Withdrawal Debriefing 3. Controlled Observation Deception Researchers manipulate variables to observe Confidentiality the effects of specific changes. Observation Protection Reliability and Validity of Observations Advice Colleagues CHAPTER 4: RESEARCH DESIGN RESEARCH DESIGN structured framework of It is simply a research methods as well as techniques that It is a kind of blueprint that we prepare are utilized by a researcher. before actually carrying out research. It is the strategic plan of the project that Function and Purpose of Research Design sets out the broad structure of the research. Black and Champion (1976) have pointed out It is the framework of research methods the following 3 functions of research design: and techniques chosen by a researcher. 1. It provides a blueprint of operationalizing the research activity/  2. It defines the limit and scope of the Analyze the collected data using research. appropriate statistical techniques to 3. It provides an opportunity to the test the hypotheses. researcher to foresee possible areas of problems in the process, carrying 7. Interpret and Report: out the research. Interpret the results of the analysis, draw conclusions, and report the STEPS OF SCIENTIFIC METHOD findings in a clear and concise manner. Key Points: 1. Define the Research Problem: The scientific method is an iterative Clearly identify the research question process, meaning that findings from or problem that needs to be one study can lead to new research addressed. questions and further investigation. The steps are not always linear; 2. Review the Literature: researchers may need to revisit Conduct a thorough review of existing earlier steps as needed. research, theories, and concepts The goal of the scientific method is to related to the research problem. generate reliable and objective knowledge. 3. Formulate Hypotheses: By following these steps, researchers can Develop testable hypotheses that systematically investigate phenomena, draw predict the outcome of the research. valid conclusions, and contribute to the advancement of knowledge in their field. 4. Design Research: Create a detailed research plan, 10 STEPS IN RESEARCH DESIGN including the research design (e.g., experimental, correlational, survey), 1. Defining the Research Problem: data collection methods, and sample Clearly articulating the research selection. question or problem that needs to be 5. Collect Data: investigated. 2. Reviewing the Literature: Conducting Gather data through various methods, a thorough review of existing such as surveys, experiments, research, theories, and concepts observations, or interviews. related to the research problem. 3. Formulating Hypotheses and Identifying 6. Analyze Data: Variables: Developing testable  hypotheses and identifying the independent and dependent variables. 4. Identifying the Universe and Unit of Study: Defining the population to be studied and the specific units of analysis (e.g., individuals, groups, organizations). 5. Selection of Research Methods: Choosing appropriate research Based on Objectives: methods (e.g., surveys, experiments, case studies, etc.) based on the Fundamental Research: Aims to increase knowledge and understanding research question and the nature of of fundamental principles. It focuses the data to be collected. on theory development and testing. 6. Standardization of Research: Developing standardized procedures Applied Research: Aims to solve practical problems and apply for data collection and analysis to knowledge to real-world situations. It ensure consistency and reliability. focuses on finding solutions to 7. Pilot Study/Use of Other Methods: specific problems. Conducting a small-scale preliminary study to test the research design and Action Research: A collaborative approach involving researchers and identify potential issues. practitioners working together to 8. Collection of Data: Gathering data solve problems within a specific using the selected research methods. context. 9. Analyzing Data: Processing and analyzing the collected data using Based on Nature of Data: appropriate statistical techniques. 10. Interpretation and Report Writing: Qualitative Research: Involves Interpreting the findings, drawing collecting and analyzing non-numerical conclusions, and writing a research data, such as text, images, or report to communicate the results. observations. It focuses on understanding the meaning and This step-by-step approach ensures a interpretation of data. systematic and rigorous research process, Quantitative Research: Involves leading to reliable and valid findings. collecting and analyzing numerical data. It focuses on measuring variables and TYPES OF RESEARCH DESIGN testing hypotheses. Based on Nature of Findings: The choice of research design depends on the research question, the Explanatory Research: Aims to explain nature of the data to be collected, the causes of phenomena and the and the desired level of control. relationships between variables. Understanding these distinctions is Exploratory Research: Aims to essential for designing effective explore and investigate a topic or research studies. phenomenon in depth, often with the goal of developing new theories or TYPES OF SCIENTIFIC METHOD hypotheses. Descriptive Research: Aims to describe the characteristics of a population or phenomenon. Based on Experimental Manipulations: Experimental Research: Involves manipulating an independent variable to observe its effect on a dependent variable. It allows for the 3 APPROACHES OF RESEARCH establishment of cause-and-effect relationships. Non-Experimental Research: Does not 1. Qualitative Research: involve manipulating variables. It relies Focuses on understanding the meaning on observation or measurement of and interpretation of social existing variables. phenomena. Relies on data collection methods like Based on Approach Involved: interviews, observations, and Longitudinal Research: Involves document analysis. studying the same group of Generates rich, detailed, and participants over an extended period contextualized data. of time. Often used in fields like sociology, Cross-Sectional Research: Involves anthropology, and psychology. studying different groups of 2. Quantitative Research: participants at a single point in time. Emphasizes numerical data and Key Points: statistical analysis. Aims to test hypotheses and identify Different research studies can fall causal relationships between variables. into multiple categories based on these criteria.  Relies on methods like surveys, Design: experiments, and content analysis. Often used in fields like economics, Focus on Variables: Quantitative research involves examining various psychology, and education. variables and their relationships. 3. Mixed Methods Research: Numerical Data: It utilizes numbers and statistics to analyze data. Combines both qualitative and Data Collection: The primary methods quantitative research methods. of data collection are through Allows for a more comprehensive surveys, experiments, and understanding of a research problem observational studies. by integrating different perspectives. Can be used to validate or expand Visual Representation: upon findings from either qualitative or quantitative research alone. Graphics, Figures, and Pie Charts: These visual aids are used to Key Points: represent and interpret the numerical data collected. The choice of research approach Meta-Analysis: This involves combining depends on the research question, the the results of multiple studies to draw nature of the data to be collected, broader conclusions. and the desired level of depth and breadth of understanding. Key Points: Qualitative research is often used to Quantitative research aims to quantify explore new phenomena or generate phenomena and establish hypotheses, while quantitative cause-and-effect relationships. research is often used to test It relies on objective measurements hypotheses and generalize findings. and statistical analysis to draw Mixed methods research offers a conclusions. more flexible and comprehensive It is often used in fields like approach to research, allowing for psychology, sociology, economics, and triangulation of data and a deeper education. understanding of complex phenomena. By understanding the strengths and limitations Qualitative Research Design of each approach, researchers can select the most appropriate methods to address Design: their research questions and achieve their research goals. Explanatory Nature: Qualitative research seeks to understand the Quantitative Research Design "why" and "how" of phenomena.  Focus on Meaning: It focuses on understanding the meanings and interpretations that individuals ascribe to social and human experiences. In-Depth Exploration: It involves in-depth exploration of a research topic through various methods. Example: Case Studies: These are commonly used in qualitative research to study specific cases or individuals in detail. ALTERNATIVE RESEARCH DESIGNS Key Points: Qualitative research generates rich, detailed, and contextualized data. It is often used in fields like sociology, anthropology, and psychology. It emphasizes the subjective nature of human experience and seeks to understand the world from the participants' perspectives. FRAMEWORK FOR RESEARCH - THE By using qualitative research methods, INTERCONNECTION OF WORLDVIEWS, DESIGN, researchers can gain a deeper understanding AND METHODS of complex social phenomena and develop nuanced insights. Qualitative vs Quantitative Philosophical Worldviews:  Postpositivist: This worldview assumes research questions, hypotheses, data that reality exists objectively and can collection methods, and analysis be discovered through empirical techniques. research. It emphasizes quantitative methods and statistical analysis. Research Methods: Constructivist: This worldview These are the specific techniques suggests that reality is subjective and used to collect data, such as surveys, constructed through social interviews, experiments, and interactions. It emphasizes qualitative observations. methods, such as interviews and observations. Interconnections: Transformative: This worldview focuses on social justice and The image highlights the interconnectedness empowerment. It emphasizes of these components. The choice of participatory research methods and philosophical worldview influences the action research. research approach and design, which in turn Pragmatic: This worldview is flexible determines the appropriate research and pragmatic, drawing on multiple methods. philosophical perspectives to address Key Points: specific research questions. The choice of research approach Research Approaches: and methods should align with the Quantitative: Relies on numerical data research question and the and statistical analysis. It aims to test philosophical worldview of the hypotheses and identify causal researcher. relationships. A mixed methods approach can Qualitative: Relies on non-numerical provide a more comprehensive data, such as text, images, and understanding of complex phenomena. observations. It aims to understand the The research design should be meaning and interpretation of social carefully planned to ensure the validity phenomena. and reliability of the findings. Mixed Methods: Combines both By understanding these interconnections, quantitative and qualitative approaches researchers can make informed decisions to gain a more comprehensive about their research design and methods, understanding of a research problem. ultimately leading to more rigorous and Research Design: meaningful research. The research design outlines the 5 SUBTYPES OF RESEARCH DESIGN overall plan for a study, including the Descriptive Research: ○ Methods: In-depth analysis, case studies, and surveys. ○ Focus: Describes ○ Example: A study to identify characteristics of a the factors contributing to population or phenomenon. employee turnover in a ○ Methods: Surveys, interviews, company. observations. ○ Example: A study to determine Explanatory Research: the average age of students in a university. ○ Focus: Explains the reasons behind a phenomenon or event. Experimental Research: ○ Methods: Theories, hypotheses, and in-depth analysis. ○ Focus: Establishes ○ Example: A study to explain the cause-and-effect relationships reasons for the decline in a between variables. particular industry. ○ Methods: Manipulating independent variables and Key Points: measuring their impact on dependent variables. The choice of research design ○ Example: A study to determine depends on the research question and the effect of a new teaching the specific goals of the study. method on student Each design has its own strengths and performance. limitations, and researchers should carefully consider these factors Correlational Research: when selecting a design. A combination of different designs ○ Focus: Identifies relationships can often provide a more between variables. comprehensive understanding of a ○ Methods: Statistical analysis to research problem. measure the strength and direction of relationships. CHARACTERISTICS OF A GOOD RESEARCH ○ Example: A study to determine DESIGN the relationship between hours of study and exam scores. 1. Generalization: Diagnostic Research: The results of your research should ○ Focus: Diagnoses the causes be applicable to a larger population, of a specific problem or not just the specific sample you phenomenon. studied.  Your research design should ensure that your findings can be generalized Checklist In Designing a Survey Method to the broader population. Purpose and Design: 2. Neutrality: Purpose: Clearly state the purpose of The research should be objective and the survey. unbiased. Reasons for Choice: Explain why a Researchers should avoid personal particular survey design was chosen. opinions and biases influencing the Nature of Survey: Identify if it's a research process and findings. cross-sectional (one-time data collection) or longitudinal (data 3. Validity: collected over time) survey. The research design should Population and Sample: Define the target population and the sample size. accurately measure what it intends to measure. Sampling Procedure: Specify the sampling method (e.g., random, The tools and methods used should be stratified, convenience). appropriate and reliable. 4. Reliability: Instrument and Content: The research design should produce Survey Instrument: Describe the type of instrument (e.g., questionnaire, consistent results over time. interview). If the research is repeated under similar conditions, the results should be Content Areas: Outline the topics and variables to be covered. similar. Scales: Specify the measurement These characteristics are essential for scales used (e.g., Likert scale, conducting high-quality research. By ensuring semantic differential). that your research design meets these Pilot Testing: Indicate whether the criteria, you can increase the credibility and survey will be pilot-tested to identify impact of your findings. any issues. QUANTITATIVE RESEARCH DESIGN Timeline and Data Analysis: Timeline: Outline the timeline for Survey Research administering the survey and collecting data. A survey design provides a quantitative or Variables: Identify the key variables in numeric description of trends, attitudes, or the study. opinions of a population by studying a sample Data Analysis: Specify the steps of that population. involved in data analysis, including:  ○ Analyzing returns Different sampling techniques include ○ Checking for response bias random sampling, stratified sampling, ○ Conducting descriptive analysis cluster sampling, and convenience ○ Collapsing items into scales sampling. ○ Checking for reliability of scales 3. Instruments: ○ Running inferential statistics These are the tools used to collect ○ Interpreting results data, such as surveys, questionnaires, interviews, observations, or RESEARCH DESIGN ELEMENTS experiments. The choice of instrument depends on the research question and the type of data being collected. Interconnectedness: The image shows that these elements are interconnected and influence each other. For example: The choice of sampling technique can affect the generalizability of the findings. The research instrument should be appropriate for the type of data being collected and the research question. 1. Variables: The variables being studied will These are the factors or determine the appropriate sampling characteristics that are being studied technique and research instrument. in the research. They can be independent variables Key Points: (manipulated by the researcher) or A well-designed research study dependent variables (measured or involves careful consideration of observed). these elements. The choice of each element should be 2. Sampling Techniques: based on the research question and This refers to the process of the desired outcomes. selecting a sample from a larger population.  By understanding these elements, Normal: The data follows a normal researchers can design rigorous and distribution. effective research studies. Non-Normal: The data does not follow a normal distribution. SELECTING THE APPROPRIATE STATISTICAL TEST Statistical Test Nature of Question The table suggests appropriate statistical tests based on the nature of the question, Group Comparison: This is used when number of variables, type of score, and you want to compare the means or distribution of scores. Here are some of the proportions of two or more groups. common tests mentioned: Association Between Groups: This is used when you want to examine the t-test: Used to compare the means of relationship between two categorical two groups. variables. Analysis of Variance (ANOVA): Used to Relate Variables: This is used when you compare the means of more than want to examine the relationship two groups. between two or more continuous Analysis of Covariance (ANCOVA): variables. Used to compare the means of more than two groups while controlling for Number of Independent Variables covariates. 1: One independent variable is being Chi-Square Test: Used to analyze the association between two categorical manipulated or compared. variables. 1 or more: Multiple independent variables are being examined. Pearson Product-Moment Correlation: Used to measure the strength and Number of Dependent Variables direction of the linear relationship between two continuous variables. 1: One outcome variable is being Multiple Regression: Used to predict an measured. outcome variable based on multiple predictor variables. Type of Score/Dependent Variable Categorical: The dependent variable is Key Points: measured in categories (e.g., gender, The choice of statistical test depends race). on the specific research question and Continuous: The dependent variable is the nature of the data. measured on a continuous scale (e.g., It is important to consider the age, weight, income). assumptions of each statistical test, such as normality and homogeneity of Distribution of Scores variance.  Consulting with a statistician can help Independent Variable: Specify the you choose the appropriate statistical variable(s) you will manipulate. test for your research. Operationalization: Clearly define how the variables will be measured. EXPERIMENTAL RESEARCH Covariates: Consider any potential confounding variables and how they It is a scientific approach to research, where will be controlled. one or more independent variables are manipulated and applied to one or more Experimental Design and Procedure: dependent variables to measure their effect Design: Choose an appropriate on the latter. experimental design (e.g., between-subjects, within-subjects, Checklist for Designing an Experimental factorial). Procedure Instruments: Select reliable and valid instruments to measure the variables. Participant Considerations: Procedure: Outline the step-by-step procedure, including participant Who are the participants? Clearly recruitment, data collection, and data define the target population and the analysis. specific characteristics of the Threats to Validity: Identify potential participants you plan to include in your threats to internal and external validity study. and develop strategies to minimize Generalizability: Consider to whom them. your findings will be generalizable. Selection: Explain how participants will Data Analysis: be selected (e.g., random sampling, convenience sampling). Pilot Test: Consider conducting a pilot test to refine the procedure and Assignment: Describe how participants identify any issues. will be assigned to experimental and control groups (e.g., random Statistical Analysis: Determine the appropriate statistical tests to analyze assignment, matched pairs). the data (e.g., t-tests, ANOVA, Sample Size: Determine the regression). appropriate sample size for your study. Interpretation: Plan how you will interpret the results and draw Variables and Measurement: conclusions. Dependent Variable: Identify the Pre-Experimental Designs outcome variable(s) you will be measuring. Pre-experimental designs are the simplest form of research design. They lack a control group and random ○ Two groups are compared, assignment of participants, making it difficult one that receives a treatment to establish cause-and-effect relationships. and one that does not. ○ Example: Comparing the While they are less rigorous than true academic performance of experimental designs, they can be useful for students in a new curriculum exploratory research and generating to those in a traditional hypotheses. curriculum. ○ Limitation: Without random Common Types of Pre-Experimental Designs: assignment, it's difficult to 1. One-Shot Case Study Design: ensure that the groups are equivalent, which can affect ○ A single group is exposed to a the validity of the comparison. treatment, and then a 4. Posttest-Only with Nonequivalent measurement is taken. Groups Design ○ Example: A new teaching This is a quasi-experimental method is introduced in a design where two groups, a classroom, and students' test treatment group and a control scores are measured group, are compared on a afterward. dependent variable after the ○ Limitation: Lack of a control treatment has been group makes it difficult to administered to the treatment determine if the treatment group. caused the observed effect. Key Features: 2. One-Group Pretest-Posttest Design: ○ No Random Assignment: Participants are not ○ A single group is measured randomly assigned to before and after a treatment. groups, which can lead ○ Example: Students' math skills to potential biases and are assessed before and threats to internal after a math intervention validity. program. ○ Posttest Only: Data is ○ Limitation: While it allows for collected only after comparison within the same the treatment has group, it lacks a control been administered. group to rule out other ○ Nonequivalent Groups: factors that might have The groups are not influenced the change. equivalent at the start 3. Static-Group Comparison: of the study, which can affect the  comparability of the Non-Random Assignment: Participants results. are not randomly assigned to groups, which can lead to potential biases. Limitations of Pre-Experimental Designs: Manipulation of Independent Variable: The researcher manipulates the Lack of Control Group: The absence independent variable to observe its of a control group makes it difficult effect on the dependent variable. to isolate the effects of the treatment. Lack of Complete Control: There may be other factors that could Threats to Internal Validity: Factors influence the outcome, making it such as history, maturation, testing, difficult to isolate the effect of the instrumentation, and statistical independent variable. regression can influence the results. Limited Generalizability: The findings of Common Types of Quasi-Experimental Designs: pre-experimental studies may not be generalizable to other populations or 1. Nonequivalent Control Group Design: settings. ○ Two or more groups are compared, but participants While pre-experimental designs have limitations, are not randomly assigned. they can be useful for preliminary research ○ and generating hypotheses. However, for ○ Example: Comparing the more rigorous and conclusive research, it is academic performance of generally recommended to use true students in a new school experimental or quasi-experimental designs. curriculum to those in a traditional curriculum. Quasi-Experimental Designs 2. Pretest-Posttest Control Group Design: ○ Both a treatment group and a Quasi-experimental designs are research control group are measured designs that aim to establish a before and after the cause-and-effect relationship between an treatment. independent and dependent variable, but without the rigorous control of a true ○ Example: Measuring students' math skills before and after a experiment. They are often used in situations new math intervention where random assignment is not feasible or program, and comparing the ethical. results to a control group Key Characteristics of Quasi-Experimental that did not receive the Designs: intervention. 3. Time-Series Design: ○ A single group is measured repeatedly over time, with the  treatment introduced at some True Experimental Designs point. ○ Example: Measuring traffic accidents before and after a True experimental designs are considered the new speed limit is implemented. gold standard for establishing 4. Multiple-Time-Series Design: cause-and-effect relationships. They involve ○ Two or more groups are the manipulation of an independent variable and measured repeatedly over the random assignment of participants to time, with the treatment experimental and control groups. introduced to one group but Key Characteristics of True Experimental not the other. Designs: ○ Example: Comparing the crime rates in two cities, one of Random Assignment: Participants are which implements a new randomly assigned to experimental and policing strategy. control groups, ensuring that the groups are equivalent at the beginning Strengths of Quasi-Experimental Designs: of the study. Manipulation of Independent Variable: Practicality: Often more practical and The researcher actively manipulates feasible to implement than true the independent variable to observe its experiments. effect on the dependent variable. Real-World Settings: Can be used to Control Group: A control group is study real-world interventions and used to compare the effects of the programs. treatment to a group that does not Generalizability: Results may be more receive the treatment. generalizable to real-world settings. Types of True Experimental Designs: Limitations of Quasi-Experimental Designs: 1. Posttest-Only Control Group Design: Lack of Random Assignment: This can limit the ability to control for ○ Participants are randomly extraneous variables and establish assigned to either an causal relationships. experimental or control group. Threats to Internal Validity: Factors ○ The independent variable is such as history, maturation, testing, manipulated for the instrumentation, and regression to the experimental group. mean can affect the results. ○ Both groups are measured on Difficulty in Drawing Causal the dependent variable after Conclusions: While quasi-experimental the treatment. designs can provide strong evidence for a causal relationship, they cannot definitively establish causality.  2. Pretest-Posttest Control Group Artificiality: The controlled laboratory Design: setting may not always reflect real-world conditions. ○ Participants are randomly Ethical Considerations: Some research assigned to either an questions may not be ethically feasible experimental or control group. to study using experimental methods. ○ Both groups are measured on Practical Constraints: Random the dependent variable before assignment may not always be and after the treatment. practical or possible. ○ This design allows for the assessment of changes within Quasi-Experimental vs True Experimental each group and between groups. 3. Solomon Four-Group Design: Both quasi-experimental and true experimental designs are used to investigate causal ○ Combines the features of the relationships between variables. However, they posttest-only and differ in terms of how participants are pretest-posttest designs. assigned to groups and the level of control ○ It involves four groups: two over the research environment. experimental groups and two control groups. True Experimental Design ○ This design helps to control for the effects of pretesting 1. Random Assignment: Participants are randomly assigned to either the and the interaction between experimental or control group. This the treatment and pretesting. ensures that the groups are Advantages of True Experimental Designs: equivalent at the beginning of the study, minimizing the impact of Strong Internal Validity: Random extraneous variables. assignment helps to control for 2. Manipulation of Independent Variable: extraneous variables, making it easier The researcher actively manipulates to establish causal relationships. the independent variable to observe its Scientific Rigor: The controlled nature effect on the dependent variable. of true experiments allows for 3. Control Group: A control group is precise measurement and analysis. used to compare the effects of the Generalizability: Well-designed treatment to a group that does not experiments can lead to findings that receive the treatment. can be generalized to larger populations. Quasi-Experimental Design Limitations of True Experimental Designs:  1. Non-Random Assignment: Participants ○ To assess the impact of the are not randomly assigned to groups. treatment on individual Instead, they are assigned to groups participants. based on existing characteristics or ○ To control for initial group conditions. differences through statistical 2. Manipulation of Independent Variable: analysis (e.g., analysis of The researcher still manipulates the covariance). independent variable. 3. Comparison Group: A comparison Quasi-Experimental Design: group is used instead of a control Non-Random Assignment: Participants group. This group may not be are not randomly assigned to groups. equivalent to the treatment group due Pretest-Posttest Nonequivalent to the lack of random assignment. Control Group Design: Both groups are measured before and after the treatment, but the groups may not be equivalent at the start of the study. Purpose of Pretest: ○ To assess initial group differences. ○ To measure change within each group over time. ○ However, the lack of random Quasi-Experimental vs True Experimental: Pre-test and Post-Test assignment can limit the ability to draw causal inferences. True Experimental Design: Single-Subject Design