{"id":334486,"date":"2021-12-03T15:50:40","date_gmt":"2021-12-03T14:50:40","guid":{"rendered":"https:\/\/www.scribbr.nl\/?p=334486"},"modified":"2023-06-22T10:27:45","modified_gmt":"2023-06-22T08:27:45","slug":"explanatory-research","status":"publish","type":"post","link":"https:\/\/www.scribbr.com\/methodology\/explanatory-research\/","title":{"rendered":"Explanatory Research | Definition, Guide, & Examples"},"content":{"rendered":"
Explanatory research<\/strong> is a research method that explores why something occurs when limited information is available. It can help you increase your understanding of a given topic, ascertain how or why a particular phenomenon is occurring, and predict future occurrences.<\/p>\n Explanatory research can also be explained as a \u201ccause and effect\u201d model, investigating patterns and trends in existing data that haven\u2019t been previously investigated. For this reason, it is often considered a type of causal research<\/a>.<\/p>\n <\/p>\n Explanatory research is used to investigate how or why a phenomenon takes place. Therefore, this type of research is often one of the first stages in the research process, serving as a jumping-off point for future research. While there is often data available about your topic, it’s possible the particular causal relationship<\/a> you are interested in has not been robustly studied.<\/p>\n Explanatory research helps you analyze these patterns, formulating hypotheses<\/a> that can guide future endeavors. If you are seeking a more complete understanding of a relationship between variables, explanatory research is a great place to start. However, keep in mind that it will likely not yield conclusive results.<\/p>\n You analyzed their final grades and noticed that the students who take your course in the first semester always obtain higher grades than students who take the same course in the second semester.<\/p>\n You are interested in discovering what causes this pattern.<\/figure>\n Explanatory research answers \u201cwhy\u201d and \u201chow\u201d questions, leading to an improved understanding of a previously unresolved problem or providing clarity for related future research initiatives.<\/p>\n Here are a few examples:<\/p>\n After choosing your research question, there is a variety of options for research and data collection methods to choose from.<\/p>\n A few of the most common research methods include:<\/p>\n The method you choose depends on several factors, including your timeline, budget, and the structure of your question. If there is already a body of research on your topic, a literature review is a great place to start. If you are interested in opinions and behavior, consider an interview<\/a> or focus group<\/a> format. If you have more time or funding available, an experiment or pilot study may be a good fit for you.<\/p>\n In order to ensure you are conducting your explanatory research correctly, be sure your analysis is definitively causal in nature, and not just correlated.<\/p>\n Always remember the phrase \u201ccorrelation doesn\u2019t mean causation.\u201d Correlated variables are merely associated with one another: when one variable changes, so does the other. However, this isn\u2019t necessarily due to a direct or indirect causal link.<\/p>\n Causation<\/a> means that changes in the independent variable<\/a> bring about changes in the dependent variable. In other words, there is a direct cause-and-effect relationship between variables.<\/p>\n Causal evidence must meet three criteria:<\/p>\n Correlation doesn\u2019t imply causation, but causation always implies correlation. In order to get conclusive causal results, you\u2019ll need to conduct a full experimental design<\/a>.<\/p>\n Your explanatory research design depends on the research method you choose to collect your data<\/a>. In most cases, you\u2019ll use an experiment to investigate potential causal relationships. We\u2019ll walk you through the steps using an example.<\/p>\n The first step in conducting explanatory research is getting familiar with the topic you\u2019re interested in, so that you can develop a research question<\/a>.<\/p>\n Let\u2019s say you\u2019re interested in language retention rates in adults.<\/p>\n You are interested in finding out how the duration of exposure to language influences language retention ability later in life.<\/p>\n You want to set up an experiment to answer the following research question: How does the duration of exposure to a language in infancy influence language retention in adults who were adopted from abroad as children?<\/strong><\/figure>\n The next step is to address your expectations. In some cases, there is literature available on your subject or on a closely related topic that you can use as a foundation for your hypothesis<\/a>. In other cases, the topic isn\u2019t well studied, and you\u2019ll have to develop your hypothesis based on your instincts or on existing literature on more distant topics.<\/p>\n You phrase your expectations in terms of a null (H0<\/sub>) and alternative hypothesis (H1<\/sub>):<\/p>\n Note:<\/strong> It is possible to add multiple hypotheses, but for this example we\u2019ll continue with just one.<\/figure>\n Next, decide what data collection<\/a> and data analysis methods you will use and write them up. After carefully designing your research, you can begin to collect your data.<\/p>\n You compare:<\/p>\n During the study, you test their Spanish language proficiency twice in a research design that has three stages:<\/p>\n You made sure to control for any confounding variables<\/a>, such as age, gender, proficiency in other languages, etc.<\/p>\n Since you have chosen a between-subjects<\/a> variable (different exposure duration) and a within-subjects variable<\/a> (pre-test vs. post-test), you decide to conduct a mixed ANOVA.<\/figure>\n After data collection is complete, proceed to analyze your data and report the results.<\/p>\n You notice that:<\/p>\n To determine whether these differences are significant, you conduct a mixed ANOVA. The ANOVA shows that all differences are not significant for the pre-test, but they are significant for the post-test.<\/p>\n You report your results in accordance with the guidelines from the citation style you use (e.g., APA<\/a>).<\/figure>\n As you interpret the results, try to come up with explanations for the results that you did not expect. In most cases, you want to provide suggestions for future research.<\/p>\n However, this difference is only significant after the intervention (the Spanish class.)<\/p>\n You decide it\u2019s worth it to further research the matter, and propose a few additional research ideas:<\/p>\n It can be easy to confuse explanatory<\/strong> research with exploratory<\/strong> research. If you\u2019re in doubt about the relationship between exploratory and explanatory research, just remember that exploratory research lays the groundwork for later explanatory research.<\/p>\n Exploratory research questions often begin with \u201cwhat”. They are designed to guide future research and do not usually have conclusive results. Exploratory research is often utilized as a first step in your research process, to help you focus your research question and fine-tune your hypotheses.<\/p>\n Explanatory research questions often start with “why” or “how”. They help you study why and how a previously studied phenomenon takes place.<\/p>\n Like any other research design<\/a>, explanatory research has its trade-offs: while it provides a unique set of benefits, it also has significant downsides:<\/p>\n If you want to know more about statistics<\/a>, methodology<\/a>, or research bias<\/a>, make sure to check out some of our other articles with explanations and examples.<\/p>\n <\/em>Statistics<\/strong><\/p>\n <\/em> Methodology<\/strong><\/p>\n <\/em> Research bias<\/strong><\/p>\n Explanatory research<\/a> 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. It can help you increase your understanding of a given topic.<\/p>\n\n <\/div>\n <\/dd>\n <\/div>\n Exploratory research<\/strong><\/a> aims to explore the main aspects of an under-researched problem, while explanatory research<\/strong><\/a> aims to explain the causes and consequences of a well-defined problem.<\/p>\n\n <\/div>\n <\/dd>\n <\/div>\n Explanatory research<\/a> is used to investigate how or why a phenomenon occurs. Therefore, this type of research is often one of the first stages in the research process<\/a>, serving as a jumping-off point for future research.<\/p>\n\n <\/div>\n <\/dd>\n <\/div>\n Quantitative research<\/strong><\/a> deals with numbers and statistics, while qualitative research<\/strong><\/a> deals with words and meanings.<\/p>\n Quantitative methods allow you to systematically measure variables<\/a> and test hypotheses<\/a>. Qualitative methods allow you to explore concepts and experiences in more detail.<\/p>\n\n <\/div>\n <\/dd>\n <\/div>\n <\/dl>\n","protected":false},"excerpt":{"rendered":" Explanatory research is a research method that explores why something occurs when limited information is available. It can help you increase your understanding of a given topic, ascertain how or why a particular phenomenon is occurring, and predict future occurrences. Explanatory research can also be explained as a \u201ccause and effect\u201d model, investigating patterns and […]<\/p>\n","protected":false},"author":133,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":""},"categories":[23650],"tags":[],"acf":[],"yoast_head":"When to use explanatory research<\/h2>\n
Explanatory research questions<\/h2>\n
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Explanatory research data collection<\/h2>\n
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Explanatory research data analysis<\/h2>\n
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Step-by-step example of explanatory research<\/h2>\n
Step 1: Develop the research question<\/h3>\n
Step 2: Formulate a hypothesis<\/h3>\n
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Step 3: Design your methodology and collect your data<\/h3>\n
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Step 4: Analyze your data and report results<\/h3>\n
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Step 5: Interpret your results and provide suggestions for future research<\/h3>\n
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Explanatory vs. exploratory research<\/h2>\n
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Advantages and disadvantages of explanatory research<\/h2>\n
Advantages<\/h3>\n
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Disadvantages<\/h3>\n
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Other interesting articles<\/h2>\n
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Frequently asked questions about explanatory research<\/h2>\n
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