explain the difference between concept and construct in research method


Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents. For example, use triangulation to measure your variables using multiple methods; regularly calibrate instruments or procedures; use random sampling and random assignment; and apply masking (blinding) where possible. In matching, you match each of the subjects in your treatment group with a counterpart in the comparison group. However, in stratified sampling, you select some units of all groups and include them in your sample. Decide on your sample size and calculate your interval, You can control and standardize the process for high. Cluster sampling is more time- and cost-efficient than other probability sampling methods, particularly when it comes to large samples spread across a wide geographical area. An operational definition should identify how the variable is calculated or recorded as a numeric value. In this way, both methods can ensure that your sample is representative of the target population. (transitive) To build (a sentence, an argument, etc.) First, the author submits the manuscript to the editor. What are the pros and cons of a between-subjects design? Together, they help you evaluate whether a test measures the concept it was designed to measure. You are an experienced interviewer and have a very strong background in your research topic, since it is challenging to ask spontaneous, colloquial questions. Random sampling enhances the external validity or generalizability of your results, while random assignment improves the internal validity of your study. To design a controlled experiment, you need: When designing the experiment, you decide: Experimental design is essential to the internal and external validity of your experiment. In multistage sampling, you can use probability or non-probability sampling methods. The American Community Surveyis an example of simple random sampling. the methodological aspects of the study with these questions. Test-retest reliability can be used to assess how well a method resists these factors over time. In quota sampling you select a predetermined number or proportion of units, in a non-random manner (non-probability sampling). Its not a variable of interest in the study, but its controlled because it could influence the outcomes. Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys, and statistical tests). Youll also deal with any missing values, outliers, and duplicate values. If participants know whether they are in a control or treatment group, they may adjust their behavior in ways that affect the outcome that researchers are trying to measure. You focus on finding and resolving data points that dont agree or fit with the rest of your dataset. Clean data are valid, accurate, complete, consistent, unique, and uniform. 1. Construct validity is often considered the overarching type of measurement validity. You are constrained in terms of time or resources and need to analyze your data quickly and efficiently. Stratified and cluster sampling may look similar, but bear in mind that groups created in cluster sampling are heterogeneous, so the individual characteristics in the cluster vary. To ensure the internal validity of your research, you must consider the impact of confounding variables. What are the disadvantages of a cross-sectional study? Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. Whats the difference between quantitative and qualitative methods? The process of turning abstract concepts into measurable variables and indicators is called operationalization. What is a construct? Operationalization means turning abstract conceptual ideas into measurable observations. Differential attrition occurs when attrition or dropout rates differ systematically between the intervention and the control group. by arranging words or ideas. What does controlling for a variable mean? To ensure the internal validity of an experiment, you should only change one independent variable at a time. What is the difference between a control group and an experimental group? Its time-consuming and labor-intensive, often involving an interdisciplinary team. No, the steepness or slope of the line isnt related to the correlation coefficient value. But multistage sampling may not lead to a representative sample, and larger samples are needed for multistage samples to achieve the statistical properties of simple random samples. Construct validity. When its taken into account, the statistical correlation between the independent and dependent variables is higher than when it isnt considered. There are eight threats to internal validity: history, maturation, instrumentation, testing, selection bias, regression to the mean, social interaction and attrition. Reliability is consistency across time (test-retest reliability), across items (internal consistency), and across researchers (interrater reliability). Your research depends on forming connections with your participants and making them feel comfortable revealing deeper emotions, lived experiences, or thoughts. What types of documents are usually peer-reviewed? A hypothesis states your predictions about what your research will find. Inductive reasoning is also called inductive logic or bottom-up reasoning. All questions are standardized so that all respondents receive the same questions with identical wording. You can think of independent and dependent variables in terms of cause and effect: an. The difference is that face validity is subjective, and assesses content at surface level. Causation means that changes in one variable brings about changes in the other; there is a cause-and-effect relationship between variables. The correlation coefficient only tells you how closely your data fit on a line, so two datasets with the same correlation coefficient can have very different slopes. Using stratified sampling, you can ensure you obtain a large enough sample from each racial group, allowing you to draw more precise conclusions. If you dont control relevant extraneous variables, they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable. The research process varies according to fields of knowledge. What are the pros and cons of a within-subjects design? Conceptual research is defined as a methodology wherein research is conducted by observing and analyzing already present information on a given topic. Whats the difference between inductive and deductive reasoning? These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication. Triangulation is mainly used in qualitative research, but its also commonly applied in quantitative research. 1.3 Concepts as abstract objects. Before collecting data, its important to consider how you will operationalize the variables that you want to measure. A measure with high construct validity accurately reflects the abstract concept that the researcher wants to study. In contrast, a mediator is the mechanism of a relationship between two variables: it explains the process by which they are related. One type of data is secondary to the other. When should you use a structured interview? Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants from a population. Whats the difference between exploratory and explanatory research? You test convergent validity and discriminant validity with correlations to see if results from your test are positively or negatively related to those of other established tests. What do I need to include in my research design? The main difference is that in stratified sampling, you draw a random sample from each subgroup (probability sampling). Definition of Concept Here is a standard textbook definition of the term, taken from LeRoy and Corbet, Research Methods in Political Science (Belmont, California: Wadsworth Thompson, 2006, p.25). Whats the difference between a mediator and a moderator? If you dont have construct validity, you may inadvertently measure unrelated or distinct constructs and lose precision in your research. But you can use some methods even before collecting data. What are the pros and cons of multistage sampling? This type of validity is concerned with whether a measure seems relevant and appropriate for what its assessing only on the surface. In general, correlational research is high in external validity while experimental research is high in internal validity. In stratified sampling, researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment). If you want to analyze a large amount of readily-available data, use secondary data. The validity of your experiment depends on your experimental design. In a within-subjects design, each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions. In multistage sampling, or multistage cluster sampling, you draw a sample from a population using smaller and smaller groups at each stage. Convenience sampling and quota sampling are both non-probability sampling methods. What is the difference between single-blind, double-blind and triple-blind studies? Action research is conducted in order to solve a particular issue immediately, while case studies are often conducted over a longer period of time and focus more on observing and analyzing a particular ongoing phenomenon. Sampling means selecting the group that you will actually collect data from in your research. Then, you can use a random number generator or a lottery method to randomly assign each number to a control or experimental group. In statistics, dependent variables are also called: An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. Longitudinal studies are better to establish the correct sequence of events, identify changes over time, and provide insight into cause-and-effect relationships, but they also tend to be more expensive and time-consuming than other types of studies. Methodology refers to the overarching strategy and rationale of your research project. What are independent and dependent variables? Concept - A concept is a generally accepted collection of meanings or characteristics that are concrete whereas a construct . In scientific research, concepts are the abstract ideas or phenomena that are being studied (e.g., educational achievement). Why are reproducibility and replicability important? It is less focused on contributing theoretical input, instead producing actionable input. Whats the difference between random and systematic error? Our team helps students graduate by offering: Scribbr specializes in editing study-related documents. Populations are used when a research question requires data from every member of the population. Is the correlation coefficient the same as the slope of the line? Constructs are broad concepts or topics for a study. A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires. Is snowball sampling quantitative or qualitative? For example, say you want to investigate how income differs based on educational attainment, but you know that this relationship can vary based on race. What are the pros and cons of a longitudinal study? Individual differences may be an alternative explanation for results. Its one of four types of measurement validity, which includes construct validity, face validity, and criterion validity. When should you use an unstructured interview? Discrete and continuous variables are two types of quantitative variables: Quantitative variables are any variables where the data represent amounts (e.g. You need to know what type of variables you are working with to choose the right statistical test for your data and interpret your results. Attrition refers to participants leaving a study. A confounding variable is a type of extraneous variable that not only affects the dependent variable, but is also related to the independent variable. Whats the difference between extraneous and confounding variables? As such, a snowball sample is not representative of the target population and is usually a better fit for qualitative research. In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section. Its called independent because its not influenced by any other variables in the study. A hypothesis is not just a guess it should be based on existing theories and knowledge. The key difference between observational studies and experimental designs is that a well-done observational study does not influence the responses of participants, while experiments do have some sort of treatment condition applied to at least some participants by random assignment. What is an example of simple random sampling? It also represents an excellent opportunity to get feedback from renowned experts in your field. Qualitative data is collected and analyzed first, followed by quantitative data. The difference between temperatures of 20C and 25C is precisely 5, but a temperature of 0C does not mean that there is a complete absence of heat. Its a form of academic fraud. A concept is "an abstraction based on characteristics of perceived reality." Wow--that is pretty abstract itself. For example, you might use a ruler to measure the length of an object or a thermometer to measure its temperature. You can avoid systematic error through careful design of your sampling, data collection, and analysis procedures. This is usually only feasible when the population is small and easily accessible. However, it provides less statistical certainty than other methods, such as simple random sampling, because it is difficult to ensure that your clusters properly represent the population as a whole. A control variable is any variable thats held constant in a research study. Such patterns of relationships are called propositions. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable. knowledge on the meaning of each of these concepts, and more importantly to distinguish between them in a study of Research Methods, and in particular as they relate to designing a research proposal and a thesis for a higher degree. Constructs are conceptualized at the theoretical (abstract) plane, while variables are operationalized and measured at the empirical (observational) plane. It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives. A correlation coefficient is a single number that describes the strength and direction of the relationship between your variables. Systematic error is a consistent or proportional difference between the observed and true values of something (e.g., a miscalibrated scale consistently records weights as higher than they actually are). Because of this, not every member of the population has an equal chance of being included in the sample, giving rise to sampling bias. Illustrates how research methodology and research method relate to . How do you randomly assign participants to groups? A quasi-experiment is a type of research design that attempts to establish a cause-and-effect relationship. What are the main qualitative research approaches? It defines your overall approach and determines how you will collect and analyze data. We proofread: The Scribbr Plagiarism Checker is powered by elements of Turnitins Similarity Checker, namely the plagiarism detection software and the Internet Archive and Premium Scholarly Publications content databases. A correlational research design investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them. A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. To implement random assignment, assign a unique number to every member of your studys sample. Multistage sampling can simplify data collection when you have large, geographically spread samples, and you can obtain a probability sample without a complete sampling frame. What is an example of an independent and a dependent variable? You are seeking descriptive data, and are ready to ask questions that will deepen and contextualize your initial thoughts and hypotheses. Are Likert scales ordinal or interval scales? It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data). Spontaneous questions are deceptively challenging, and its easy to accidentally ask a leading question or make a participant uncomfortable. For example, looking at a 4th grade math test consisting of problems in which students have to add and multiply, most people would agree that it has strong face validity (i.e., it looks like a math test). What are the types of extraneous variables? In research, you might have come across something called the hypothetico-deductive method. While a between-subjects design has fewer threats to internal validity, it also requires more participants for high statistical power than a within-subjects design. Data cleaning is necessary for valid and appropriate analyses. Yes, but including more than one of either type requires multiple research questions. While construct validity is the degree to which a test or other measurement method measures what it claims to measure, criterion validity is the degree to which a test can predictively (in the future) or concurrently (in the present) measure something. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. The research methods you use depend on the type of data you need to answer your research question. Snowball sampling relies on the use of referrals. Data cleaning involves spotting and resolving potential data inconsistencies or errors to improve your data quality. For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Deductive reasoning is also called deductive logic. It is made up of 4 or more questions that measure a single attitude or trait when response scores are combined. The theoretical framework is the structure that can hold or support a theory of a research study. Face validity is important because its a simple first step to measuring the overall validity of a test or technique. Samples are easier to collect data from because they are practical, cost-effective, convenient, and manageable. Explanatory research is a research method used to investigate how or why something occurs when only a small amount of information is available pertaining to that topic. Mixed methods research always uses triangulation. There are three key steps in systematic sampling: Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval for example, by selecting every 15th person on a list of the population. Quantitative data is collected and analyzed first, followed by qualitative data. Face validity is about whether a test appears to measure what its supposed to measure. In this article, the authors set out to clarify the meaning of these terms and to describe how they are used in 2 approaches to research commonly used in HPE: the objectivist deductive approach (from . You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals. They might alter their behavior accordingly. If your response variable is categorical, use a scatterplot or a line graph. The downsides of naturalistic observation include its lack of scientific control, ethical considerations, and potential for bias from observers and subjects. Correlation describes an association between variables: when one variable changes, so does the other. Action research is particularly popular with educators as a form of systematic inquiry because it prioritizes reflection and bridges the gap between theory and practice. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable. In a cross-sectional study you collect data from a population at a specific point in time; in a longitudinal study you repeatedly collect data from the same sample over an extended period of time. Experimental design means planning a set of procedures to investigate a relationship between variables. Explanatory research is used to investigate how or why a phenomenon occurs. The purpose in both cases is to select a representative sample and/or to allow comparisons between subgroups. Different types of correlation coefficients might be appropriate for your data based on their levels of measurement and distributions. A correlation reflects the strength and/or direction of the association between two or more variables. Constructs are abstract concepts specified at a high level of abstraction that are chosen specifically to explain the phenomenon of interest. There are many different types of inductive reasoning that people use formally or informally. In your research design, its important to identify potential confounding variables and plan how you will reduce their impact. Moderators usually help you judge the external validity of your study by identifying the limitations of when the relationship between variables holds. A confounding variable is closely related to both the independent and dependent variables in a study. For example, if you were stratifying by location with three subgroups (urban, rural, or suburban) and marital status with five subgroups (single, divorced, widowed, married, or partnered), you would have 3 x 5 = 15 subgroups. Theories are formulated to explain, predict, and understand phenomena and, in many cases, to challenge and extend existing knowledge, within the limits of the critical bounding assumptions. Validity is a judgment based on various types of evidence. Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports). It is used in many different contexts by academics, governments, businesses, and other organizations. Reproducibility and replicability are related terms. You already have a very clear understanding of your topic. Pearson product-moment correlation coefficient (Pearsons, population parameter and a sample statistic, Internet Archive and Premium Scholarly Publications content databases. What is the difference between stratified and cluster sampling? It is a tentative answer to your research question that has not yet been tested. These questions are easier to answer quickly. However, peer review is also common in non-academic settings. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered. Then you can start your data collection, using convenience sampling to recruit participants, until the proportions in each subgroup coincide with the estimated proportions in the population. Weare always here for you. To make quantitative observations, you need to use instruments that are capable of measuring the quantity you want to observe. In a mixed factorial design, one variable is altered between subjects and another is altered within subjects. Be careful to avoid leading questions, which can bias your responses. The directionality problem is when two variables correlate and might actually have a causal relationship, but its impossible to conclude which variable causes changes in the other. Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports). This Internal validity is the degree of confidence that the causal relationship you are testing is not influenced by other factors or variables. Recall from Chapter 2 that constructs may be unidimensional (i.e., embody a single concept), such as weight or age, or multi-dimensional (i.e., embody multiple underlying concepts), such as personality or . A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources. Random selection, or random sampling, is a way of selecting members of a population for your studys sample. While you cant eradicate it completely, you can reduce random error by taking repeated measurements, using a large sample, and controlling extraneous variables. There are five common approaches to qualitative research: Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. The word between means that youre comparing different conditions between groups, while the word within means youre comparing different conditions within the same group. This means that you cannot use inferential statistics and make generalizationsoften the goal of quantitative research. They input the edits, and resubmit it to the editor for publication. Educators are able to simultaneously investigate an issue as they solve it, and the method is very iterative and flexible. Explain what a psychological construct is and give several examples. Data validation at the time of data entry or collection helps you minimize the amount of data cleaning youll need to do. Measure more than once. If your explanatory variable is categorical, use a bar graph. A correlation is usually tested for two variables at a time, but you can test correlations between three or more variables. Constructs: Constructs are measured with multiple variables. How to measure it To measure test-retest reliability, you conduct the same test on the same group of people at two different points in time. Here, the researcher recruits one or more initial participants, who then recruit the next ones. External validity is the extent to which your results can be generalized to other contexts. Its the same technology used by dozens of other popular citation tools, including Mendeley and Zotero. Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. Chapter 6 Measurement of Constructs. These considerations protect the rights of research participants, enhance research validity, and maintain scientific integrity. Whats the difference between method and methodology? But triangulation can also pose problems: There are four main types of triangulation: Many academic fields use peer review, largely to determine whether a manuscript is suitable for publication. In what ways are content and face validity similar? What is the definition of construct validity? They can provide useful insights into a populations characteristics and identify correlations for further research. influences the responses given by the interviewee. (plural, phenomena) is a general result that has been observed reliably in systematic empirical research. In other words, they both show you how accurately a method measures something. Systematic errors are much more problematic because they can skew your data away from the true value. Stratified sampling and quota sampling both involve dividing the population into subgroups and selecting units from each subgroup. Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Perhaps significant research has already been conducted, or you have done some prior research yourself, but you already possess a baseline for designing strong structured questions. concepts. You can use this design if you think the quantitative data will confirm or validate your qualitative findings. But, strictly speaking, both terms are not exactly the same. The clusters should ideally each be mini-representations of the population as a whole. In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

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