What is a good example of a conceptual framework?

A well-designed study doesn’t just happen. Researchers work hard to ensure the studies they conduct will be scientifically valid and will advance understanding in their field.

One way they do this is by using a conceptual framework. This is a written or visual overview of the variables and concepts involved in the research question. Conceptual frameworks help guide the study’s creation and provide a roadmap for conducting it.

The main purpose of a conceptual framework is to improve the quality of a research study. A conceptual framework achieves this by identifying important information about the topic and providing a clear roadmap for researchers to study it.

Through the process of developing this information, researchers will be able to improve the quality of their studies in a few key ways.

Clarify research goals and objectives

A conceptual framework helps researchers create a clear research goal. Research projects often become vague and lose their focus, which makes them less useful. However, a well-designed conceptual framework helps researchers maintain focus. It reinforces the project’s scope, ensuring it stays on track and produces meaningful results.

Provide a theoretical basis for the study

Forming a hypothesis requires knowledge of the key variables and their relationship to each other. Researchers need to identify these variables early on to create a conceptual framework. This ensures researchers have developed a strong understanding of the topic before finalizing the study design. It also helps them select the most appropriate research and analysis methods.

Guide the research design

As they develop their conceptual framework, researchers often uncover information that can help them further refine their work.

Here are some examples:

• Confounding variables they hadn’t previously considered

• Sources of bias they will have to take into account when designing the project

• Whether or not the information they were going to study has already been covered—this allows them to pivot to a more meaningful goal that brings new and relevant information to their field

There are four major steps researchers will follow to develop a conceptual framework. Each step will be described in detail in the sections that follow. You’ll also find examples of how each might be applied in a range of fields.

Step 1: Choose the research question

The first step in creating a conceptual framework is choosing a research question. The goal of this step is to create a question that’s specific and focused.

By developing a clear question, researchers can more easily identify the variables they will need to account for and keep their research focused. Without it, the next steps will be more difficult and less effective.

Here are some examples of good research questions in a few common fields:

• Natural sciences: How does exposure to ultraviolet radiation affect the growth rate of a particular type of algae?

• Health sciences: What is the effectiveness of cognitive-behavioral therapy for treating depression in adolescents?

• Business: What factors contribute to the success of small businesses in a particular industry?

• Education: How does implementing technology in the classroom impact student learning outcomes?

Step 2: Select the independent and dependent variables

Once the research question has been chosen, it’s time to identify the dependent and independent variables.

The independent variable is the variable researchers think will affect the dependent variable. Without this information, researchers cannot develop a meaningful hypothesis or design a way to test it.

The dependent and independent variables for our example questions above are:

Natural sciences

• Independent variable: exposure to ultraviolet radiation

• Dependent variable: the growth rate of a particular type of algae

Health sciences

• Independent variable: cognitive-behavioral therapy

• Dependent variable: depression in adolescents

Business

• Independent variables: factors contributing to the business’s success

• Dependent variable: sales, return on investment (ROI), or another concrete metric

Education

• Independent variable: implementation of technology in the classroom

• Dependent variable: student learning outcomes, such as test scores, GPAs, or exam results

Step 3: Visualize the cause-and-effect relationship

This step is where researchers actually develop their hypothesis. They will predict how the independent variable will impact the dependent variable based on their knowledge of the field and their intuition.

With a hypothesis formed, researchers can more accurately determine what data to collect and how to analyze it. They will then visualize their hypothesis by creating a diagram. This visualization will serve as a framework to help guide their research.

The diagrams for our examples might be used as follows:

• Natural sciences: how exposure to radiation affects the biological processes in the algae that contribute to its growth rate

• Health sciences: how different aspects of cognitive behavioral therapy can affect how patients experience symptoms of depression

• Business: how factors such as market demand, managerial expertise, and financial resources influence a business’s success

• Education: how different types of technology interact with different aspects of the learning process and alter student learning outcomes

Step 4: Identify other influencing variables

The independent and dependent variables are only part of the equation. Moderating, mediating, and control variables are also important parts of a well-designed study. These variables can impact the relationship between the two main variables and must be accounted for.

A moderating variable is one that can change how the independent variable affects the dependent variable. A mediating variable explains the relationship between the two. Control variables are kept the same to eliminate their impact on the results. Examples of each are given below:

Natural sciences

• Moderating variable: water temperature (might impact how algae respond to radiation exposure)

• Mediating variable: chlorophyll production (might explain how radiation exposure affects algae growth rate)

• Control variable: nutrient levels in the water

Health sciences

• Moderating variable: the severity of depression symptoms at baseline might impact how effective the therapy is for different adolescents

• Mediating variable: social support might explain how cognitive-behavioral therapy leads to improvements in depression

• Control variable: other forms of treatment received before or during the study

Business

• Moderating variable: the size of the business (might impact how different factors contribute to market share, sales, ROI, and other key success metrics)

• Mediating variable: customer satisfaction (might explain how different factors impact business success)

• Control variable: industry competition

Education

• Moderating variable: student age (might impact how effective technology is for different students)

• Mediating variable: teacher training (might explain how technology leads to improvements in learning outcomes)

• Control variable: student learning style

Although they sound similar, conceptual and theoretical frameworks have different goals and are used in different contexts. Understanding which to use will help researchers craft better studies.

Conceptual frameworks describe a broad overview of the subject and outline key concepts, variables, and the relationships between them. They provide structure to studies that are more exploratory in nature, where the relationships between the variables are still being established. They are particularly helpful in studies that are complex or interdisciplinary because they help researchers better organize the factors involved in the study.

Theoretical frameworks, on the other hand, are used when the research question is more clearly defined and there’s an existing body of work to draw upon. They define the relationships between the variables and help researchers predict outcomes. They are particularly helpful when researchers want to refine the existing body of knowledge rather than establish it.