Explanatory research, a vital part of research methodology, is dedicated to providing a deep understanding of a phenomenon through the explanation of causal relationships among variables. Unlike exploratory research that seeks to generate new insights or ideas, explanatory research dives deeper to identify why and how certain situations occur. This methodology is often employed when there is a clear understanding of the problem but the reasons behind it remain obscure, thereby necessitating a comprehensive explanation.
Inhaltsverzeichnis
- 1 Explanatory Research – In a Nutshell
- 2 Definition: Explanatory Research
- 3 The usage of explanatory research
- 4 Explanatory research questions
- 5 Explanatory research: Data collection
- 6 Explanatory research: Data analysis
- 7 The 5 Steps of explanatory research with examples
- 8 Explanatory vs. exploratory research
- 9 Advantages vs. disadvantages
- 10 FAQs
Explanatory Research – In a Nutshell
- Explanatory research is a cornerstone of other research.
- Without an explanatory study, your future research will be incomplete and inefficient.
- This research improves survey and study design and reduces unintended bias.
Definition: Explanatory Research
Explanatory research is a study method that investigates the causes of a phenomenon when only limited data is presented. It can help you better grasp a topic, determine why a phenomenon is happening, and forecast future events.
This research can be described as a “cause and effect” model, researching previously unexplored patterns and trends in current data. Consequently, it is sometimes considered a sort of causal research.
The usage of explanatory research
Explanatory research investigates how or why something happens. Therefore, this type of research is one of the first steps in the research process, serving as a beginning point for future work. Your topic may have data, but the causal relationship you’re interested in may not.
This research helps evaluate patterns and generate hypotheses for future work. An explanatory study can help you comprehend a variable’s relationship. However, don’t expect conclusive outcomes.
Explanatory research questions
This research answers “why” and “how” inquiries, resulting in a better knowledge of a previously unsolved topic or clarification for relevant future research.
Examples
- Why do bilingual individuals exhibit more risky behaviour than monolingual individuals during commercial negotiations?
- How does a child’s capacity to resist gratification predict their future success?
- Why are adolescents more prone to litter in highly littered areas than in clean areas?
Explanatory research: Data collection
After deciding on your research subject, you have numerous alternatives for research and data collection methods.
The following are some of the most prevalent research methods:
- Literature reviews
- Interviews and focus groups
- Pilot studies
- Observations
- Experiments
Explanatory research: Data analysis
Ensure that your explanatory research is conducted appropriately and that your analysis is causal and not merely correlative.
Correlated variables are merely linked: when one changes, so does the other. There is no direct or indirect causal relationship.
Causation means independent variable changes cause dependent variable changes. The link between variables is direct.
The requirements for causal evidence are:
- Temporal: Cause must precede effect.
- Variation: Independent and dependent variable intervention must be systematic.
- Non-spurious: Be sure no mitigating factors or third hidden variables contradict your results.
The 5 Steps of explanatory research with examples
The data collection approach determines your explanatory research design. In most circumstances, you’ll utilize an experiment to test causality. The steps are illustrated in the following.
Step 1 of explanatory research: Research question
The initial stage in the research is familiarising yourself with the topic of interest to formulate a research question.
Suppose you are interested in adult language retention rates.
Example
You’ve examined language retention in adoptees. People who learnt a foreign language as infants had an easier time learning it again than those who weren’t exposed.
You want to know how language exposure affects long-term retention. You’re designing an experiment to answer this question: How does early language exposure affect language retention in adoptees?
Step 2 of explanatory research: Hypothesis
Next, set your expectations. In some circumstances, you can use relevant literature to build your hypothesis. In other cases, the topic isn’t well-studied; therefore, you must create your theory based on instincts or literature on distant themes.
Example
You hypothesize that individuals exposed to a language in infancy for a shorter duration will be less likely to retain features of this language than adults exposed for a longer time.
You express your predictions in terms of the null (H0) and alternative (H1) hypotheses:
- H0: Infancy language exposure does not affect language retention in adopted adults.
- H1: Exposure to a language in infancy improves language retention in adult adoptees.
Step 3 of explanatory research: Methodology and data collection
Next, choose your data collecting and data analysis methodologies and document them. After meticulously planning your research, you can begin data collection.
Example
To test a causal relationship, you run an experiment. You gather a group of adults adopted from Colombia and raised in the U.S.
You compare:
- 0-6-month-old Colombian adoptees.
- 6-12 month-old Colombian adoptees
- 12-18-month-old Colombian adoptees.
- Unexposed monolingual adults.
Using a three-stage research design, you administer two tests of their Spanish language skills during the study:
- Pre-test: Several language proficiency tests are administered to identify group variations before instruction.
- Intervention: You deliver eight hours of Spanish lessons to each group.
- Post-test: After the intervention, you administer multiple language proficiency tests to determine whether there are any differences between the groups.
Step 4 of explanatory research: Analysis and results
After data collection, assess and report results.
Example
Results:
After experimenting, you examine the data and observe that:
- The pre-exposed adults demonstrated more excellent Spanish language skills than individuals who were not pre-exposed. The post-test reveals an even more significant disparity.
- Adults adopted between 12 and 18 months had higher Spanish competence than those adopted between 0 and 6 months or 6 and 12 months, but there was no difference between the latter two groups.
For significance, use a mixed ANOVA. ANOVA indicates that pre-test differences aren’t significant, while post-test differences are.
You report your findings following the criteria of your chosen citation style between the groups.
Step 5 of explanatory research: Interpretation and recommendation
Try to explain unexpected results as you interpret them. In most circumstances, you’ll need to provide recommendations for future research.
Example
Your findings were per your expectations. Adopted individuals who were pre-exposed to a language in infancy for a longer time have preserved more of this knowledge than people who weren’t pre-exposed.
After the intervention, this difference becomes large.
You decide to do more research and suggest some topics:
- Replicate the study with a larger sample
- Study other mother tongues (e.g., Korean, Lingala, Arabic)
- Study other linguistic features, like accent nativeness.
Explanatory vs. exploratory research
Explanatory and exploratory research are often confused. Remember, exploratory research establishes the framework for explanatory research.
Many exploratory research inquiries begin with “what.” They are intended to guide future studies and typically lack definite conclusions. The research is frequently employed as the initial step in the research process to assist you in refining your study topic and ideas.
Explanatory research questions begin with “why” or “how.” They assist you in understanding why and how something happens.
Advantages vs. disadvantages
As with any other study methodology, this research involves trade-offs: while it offers a unique set of benefits, it also has major drawbacks.
| ✔ Advantages | ✘ Disadvantages |
| • It clarifies previous studies. It fills gaps in previous studies and explains why things happen. • Internal validity is high when done correctly, making it flexible and replicable. • This research is frequently cost- and time-effective because you can use secondary sources to guide your work before conducting more extensive studies |
• While explanatory research helps you solidify your thoughts and assumptions, it rarely yields conclusive results. • Results are often skewed or unacceptable to a greater body of study and are not externally valid. You'll need to undertake additional robust (typically quantitative) research to support explanatory research conclusions. • Coincidences can be mistaken for causal links, and determining cause and effect can be difficult. |
FAQs
An explanatory study investigates how or why something happens with limited information. It helps you understand a topic.
The explanatory research model is a quantitative strategy used to examine a hypothesis by gathering evidence that either supports or contradicts it.
Explanatory research aims to explain a phenomenon. Consequently, this form of research is frequently one of the initial steps of the research process, acting as a springboard for subsequent analysis.
