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Empirical Research: Definition, Methods, Types and Examples

What is Empirical Research

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Empirical research: Definition

Empirical research: origin, quantitative research methods, qualitative research methods, steps for conducting empirical research, empirical research methodology cycle, advantages of empirical research, disadvantages of empirical research, why is there a need for empirical research.

Empirical research is defined as any research where conclusions of the study is strictly drawn from concretely empirical evidence, and therefore “verifiable” evidence.

This empirical evidence can be gathered using quantitative market research and  qualitative market research  methods.

For example: A research is being conducted to find out if listening to happy music in the workplace while working may promote creativity? An experiment is conducted by using a music website survey on a set of audience who are exposed to happy music and another set who are not listening to music at all, and the subjects are then observed. The results derived from such a research will give empirical evidence if it does promote creativity or not.

LEARN ABOUT: Behavioral Research

You must have heard the quote” I will not believe it unless I see it”. This came from the ancient empiricists, a fundamental understanding that powered the emergence of medieval science during the renaissance period and laid the foundation of modern science, as we know it today. The word itself has its roots in greek. It is derived from the greek word empeirikos which means “experienced”.

In today’s world, the word empirical refers to collection of data using evidence that is collected through observation or experience or by using calibrated scientific instruments. All of the above origins have one thing in common which is dependence of observation and experiments to collect data and test them to come up with conclusions.

LEARN ABOUT: Causal Research

Types and methodologies of empirical research

Empirical research can be conducted and analysed using qualitative or quantitative methods.

  • Quantitative research : Quantitative research methods are used to gather information through numerical data. It is used to quantify opinions, behaviors or other defined variables . These are predetermined and are in a more structured format. Some of the commonly used methods are survey, longitudinal studies, polls, etc
  • Qualitative research:   Qualitative research methods are used to gather non numerical data.  It is used to find meanings, opinions, or the underlying reasons from its subjects. These methods are unstructured or semi structured. The sample size for such a research is usually small and it is a conversational type of method to provide more insight or in-depth information about the problem Some of the most popular forms of methods are focus groups, experiments, interviews, etc.

Data collected from these will need to be analysed. Empirical evidence can also be analysed either quantitatively and qualitatively. Using this, the researcher can answer empirical questions which have to be clearly defined and answerable with the findings he has got. The type of research design used will vary depending on the field in which it is going to be used. Many of them might choose to do a collective research involving quantitative and qualitative method to better answer questions which cannot be studied in a laboratory setting.

LEARN ABOUT: Qualitative Research Questions and Questionnaires

Quantitative research methods aid in analyzing the empirical evidence gathered. By using these a researcher can find out if his hypothesis is supported or not.

  • Survey research: Survey research generally involves a large audience to collect a large amount of data. This is a quantitative method having a predetermined set of closed questions which are pretty easy to answer. Because of the simplicity of such a method, high responses are achieved. It is one of the most commonly used methods for all kinds of research in today’s world.

Previously, surveys were taken face to face only with maybe a recorder. However, with advancement in technology and for ease, new mediums such as emails , or social media have emerged.

For example: Depletion of energy resources is a growing concern and hence there is a need for awareness about renewable energy. According to recent studies, fossil fuels still account for around 80% of energy consumption in the United States. Even though there is a rise in the use of green energy every year, there are certain parameters because of which the general population is still not opting for green energy. In order to understand why, a survey can be conducted to gather opinions of the general population about green energy and the factors that influence their choice of switching to renewable energy. Such a survey can help institutions or governing bodies to promote appropriate awareness and incentive schemes to push the use of greener energy.

Learn more: Renewable Energy Survey Template Descriptive Research vs Correlational Research

  • Experimental research: In experimental research , an experiment is set up and a hypothesis is tested by creating a situation in which one of the variable is manipulated. This is also used to check cause and effect. It is tested to see what happens to the independent variable if the other one is removed or altered. The process for such a method is usually proposing a hypothesis, experimenting on it, analyzing the findings and reporting the findings to understand if it supports the theory or not.

For example: A particular product company is trying to find what is the reason for them to not be able to capture the market. So the organisation makes changes in each one of the processes like manufacturing, marketing, sales and operations. Through the experiment they understand that sales training directly impacts the market coverage for their product. If the person is trained well, then the product will have better coverage.

  • Correlational research: Correlational research is used to find relation between two set of variables . Regression analysis is generally used to predict outcomes of such a method. It can be positive, negative or neutral correlation.

LEARN ABOUT: Level of Analysis

For example: Higher educated individuals will get higher paying jobs. This means higher education enables the individual to high paying job and less education will lead to lower paying jobs.

  • Longitudinal study: Longitudinal study is used to understand the traits or behavior of a subject under observation after repeatedly testing the subject over a period of time. Data collected from such a method can be qualitative or quantitative in nature.

For example: A research to find out benefits of exercise. The target is asked to exercise everyday for a particular period of time and the results show higher endurance, stamina, and muscle growth. This supports the fact that exercise benefits an individual body.

  • Cross sectional: Cross sectional study is an observational type of method, in which a set of audience is observed at a given point in time. In this type, the set of people are chosen in a fashion which depicts similarity in all the variables except the one which is being researched. This type does not enable the researcher to establish a cause and effect relationship as it is not observed for a continuous time period. It is majorly used by healthcare sector or the retail industry.

For example: A medical study to find the prevalence of under-nutrition disorders in kids of a given population. This will involve looking at a wide range of parameters like age, ethnicity, location, incomes  and social backgrounds. If a significant number of kids coming from poor families show under-nutrition disorders, the researcher can further investigate into it. Usually a cross sectional study is followed by a longitudinal study to find out the exact reason.

  • Causal-Comparative research : This method is based on comparison. It is mainly used to find out cause-effect relationship between two variables or even multiple variables.

For example: A researcher measured the productivity of employees in a company which gave breaks to the employees during work and compared that to the employees of the company which did not give breaks at all.

LEARN ABOUT: Action Research

Some research questions need to be analysed qualitatively, as quantitative methods are not applicable there. In many cases, in-depth information is needed or a researcher may need to observe a target audience behavior, hence the results needed are in a descriptive analysis form. Qualitative research results will be descriptive rather than predictive. It enables the researcher to build or support theories for future potential quantitative research. In such a situation qualitative research methods are used to derive a conclusion to support the theory or hypothesis being studied.

LEARN ABOUT: Qualitative Interview

  • Case study: Case study method is used to find more information through carefully analyzing existing cases. It is very often used for business research or to gather empirical evidence for investigation purpose. It is a method to investigate a problem within its real life context through existing cases. The researcher has to carefully analyse making sure the parameter and variables in the existing case are the same as to the case that is being investigated. Using the findings from the case study, conclusions can be drawn regarding the topic that is being studied.

For example: A report mentioning the solution provided by a company to its client. The challenges they faced during initiation and deployment, the findings of the case and solutions they offered for the problems. Such case studies are used by most companies as it forms an empirical evidence for the company to promote in order to get more business.

  • Observational method:   Observational method is a process to observe and gather data from its target. Since it is a qualitative method it is time consuming and very personal. It can be said that observational research method is a part of ethnographic research which is also used to gather empirical evidence. This is usually a qualitative form of research, however in some cases it can be quantitative as well depending on what is being studied.

For example: setting up a research to observe a particular animal in the rain-forests of amazon. Such a research usually take a lot of time as observation has to be done for a set amount of time to study patterns or behavior of the subject. Another example used widely nowadays is to observe people shopping in a mall to figure out buying behavior of consumers.

  • One-on-one interview: Such a method is purely qualitative and one of the most widely used. The reason being it enables a researcher get precise meaningful data if the right questions are asked. It is a conversational method where in-depth data can be gathered depending on where the conversation leads.

For example: A one-on-one interview with the finance minister to gather data on financial policies of the country and its implications on the public.

  • Focus groups: Focus groups are used when a researcher wants to find answers to why, what and how questions. A small group is generally chosen for such a method and it is not necessary to interact with the group in person. A moderator is generally needed in case the group is being addressed in person. This is widely used by product companies to collect data about their brands and the product.

For example: A mobile phone manufacturer wanting to have a feedback on the dimensions of one of their models which is yet to be launched. Such studies help the company meet the demand of the customer and position their model appropriately in the market.

  • Text analysis: Text analysis method is a little new compared to the other types. Such a method is used to analyse social life by going through images or words used by the individual. In today’s world, with social media playing a major part of everyone’s life, such a method enables the research to follow the pattern that relates to his study.

For example: A lot of companies ask for feedback from the customer in detail mentioning how satisfied are they with their customer support team. Such data enables the researcher to take appropriate decisions to make their support team better.

Sometimes a combination of the methods is also needed for some questions that cannot be answered using only one type of method especially when a researcher needs to gain a complete understanding of complex subject matter.

We recently published a blog that talks about examples of qualitative data in education ; why don’t you check it out for more ideas?

Since empirical research is based on observation and capturing experiences, it is important to plan the steps to conduct the experiment and how to analyse it. This will enable the researcher to resolve problems or obstacles which can occur during the experiment.

Step #1: Define the purpose of the research

This is the step where the researcher has to answer questions like what exactly do I want to find out? What is the problem statement? Are there any issues in terms of the availability of knowledge, data, time or resources. Will this research be more beneficial than what it will cost.

Before going ahead, a researcher has to clearly define his purpose for the research and set up a plan to carry out further tasks.

Step #2 : Supporting theories and relevant literature

The researcher needs to find out if there are theories which can be linked to his research problem . He has to figure out if any theory can help him support his findings. All kind of relevant literature will help the researcher to find if there are others who have researched this before, or what are the problems faced during this research. The researcher will also have to set up assumptions and also find out if there is any history regarding his research problem

Step #3: Creation of Hypothesis and measurement

Before beginning the actual research he needs to provide himself a working hypothesis or guess what will be the probable result. Researcher has to set up variables, decide the environment for the research and find out how can he relate between the variables.

Researcher will also need to define the units of measurements, tolerable degree for errors, and find out if the measurement chosen will be acceptable by others.

Step #4: Methodology, research design and data collection

In this step, the researcher has to define a strategy for conducting his research. He has to set up experiments to collect data which will enable him to propose the hypothesis. The researcher will decide whether he will need experimental or non experimental method for conducting the research. The type of research design will vary depending on the field in which the research is being conducted. Last but not the least, the researcher will have to find out parameters that will affect the validity of the research design. Data collection will need to be done by choosing appropriate samples depending on the research question. To carry out the research, he can use one of the many sampling techniques. Once data collection is complete, researcher will have empirical data which needs to be analysed.

LEARN ABOUT: Best Data Collection Tools

Step #5: Data Analysis and result

Data analysis can be done in two ways, qualitatively and quantitatively. Researcher will need to find out what qualitative method or quantitative method will be needed or will he need a combination of both. Depending on the unit of analysis of his data, he will know if his hypothesis is supported or rejected. Analyzing this data is the most important part to support his hypothesis.

Step #6: Conclusion

A report will need to be made with the findings of the research. The researcher can give the theories and literature that support his research. He can make suggestions or recommendations for further research on his topic.

Empirical research methodology cycle

A.D. de Groot, a famous dutch psychologist and a chess expert conducted some of the most notable experiments using chess in the 1940’s. During his study, he came up with a cycle which is consistent and now widely used to conduct empirical research. It consists of 5 phases with each phase being as important as the next one. The empirical cycle captures the process of coming up with hypothesis about how certain subjects work or behave and then testing these hypothesis against empirical data in a systematic and rigorous approach. It can be said that it characterizes the deductive approach to science. Following is the empirical cycle.

  • Observation: At this phase an idea is sparked for proposing a hypothesis. During this phase empirical data is gathered using observation. For example: a particular species of flower bloom in a different color only during a specific season.
  • Induction: Inductive reasoning is then carried out to form a general conclusion from the data gathered through observation. For example: As stated above it is observed that the species of flower blooms in a different color during a specific season. A researcher may ask a question “does the temperature in the season cause the color change in the flower?” He can assume that is the case, however it is a mere conjecture and hence an experiment needs to be set up to support this hypothesis. So he tags a few set of flowers kept at a different temperature and observes if they still change the color?
  • Deduction: This phase helps the researcher to deduce a conclusion out of his experiment. This has to be based on logic and rationality to come up with specific unbiased results.For example: In the experiment, if the tagged flowers in a different temperature environment do not change the color then it can be concluded that temperature plays a role in changing the color of the bloom.
  • Testing: This phase involves the researcher to return to empirical methods to put his hypothesis to the test. The researcher now needs to make sense of his data and hence needs to use statistical analysis plans to determine the temperature and bloom color relationship. If the researcher finds out that most flowers bloom a different color when exposed to the certain temperature and the others do not when the temperature is different, he has found support to his hypothesis. Please note this not proof but just a support to his hypothesis.
  • Evaluation: This phase is generally forgotten by most but is an important one to keep gaining knowledge. During this phase the researcher puts forth the data he has collected, the support argument and his conclusion. The researcher also states the limitations for the experiment and his hypothesis and suggests tips for others to pick it up and continue a more in-depth research for others in the future. LEARN MORE: Population vs Sample

LEARN MORE: Population vs Sample

There is a reason why empirical research is one of the most widely used method. There are a few advantages associated with it. Following are a few of them.

  • It is used to authenticate traditional research through various experiments and observations.
  • This research methodology makes the research being conducted more competent and authentic.
  • It enables a researcher understand the dynamic changes that can happen and change his strategy accordingly.
  • The level of control in such a research is high so the researcher can control multiple variables.
  • It plays a vital role in increasing internal validity .

Even though empirical research makes the research more competent and authentic, it does have a few disadvantages. Following are a few of them.

  • Such a research needs patience as it can be very time consuming. The researcher has to collect data from multiple sources and the parameters involved are quite a few, which will lead to a time consuming research.
  • Most of the time, a researcher will need to conduct research at different locations or in different environments, this can lead to an expensive affair.
  • There are a few rules in which experiments can be performed and hence permissions are needed. Many a times, it is very difficult to get certain permissions to carry out different methods of this research.
  • Collection of data can be a problem sometimes, as it has to be collected from a variety of sources through different methods.

LEARN ABOUT:  Social Communication Questionnaire

Empirical research is important in today’s world because most people believe in something only that they can see, hear or experience. It is used to validate multiple hypothesis and increase human knowledge and continue doing it to keep advancing in various fields.

For example: Pharmaceutical companies use empirical research to try out a specific drug on controlled groups or random groups to study the effect and cause. This way, they prove certain theories they had proposed for the specific drug. Such research is very important as sometimes it can lead to finding a cure for a disease that has existed for many years. It is useful in science and many other fields like history, social sciences, business, etc.

LEARN ABOUT: 12 Best Tools for Researchers

With the advancement in today’s world, empirical research has become critical and a norm in many fields to support their hypothesis and gain more knowledge. The methods mentioned above are very useful for carrying out such research. However, a number of new methods will keep coming up as the nature of new investigative questions keeps getting unique or changing.

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Introduction: What is Empirical Research?

Empirical research is based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief. 

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology."  Ask yourself: Could I recreate this study and test these results?

Key characteristics to look for:

  • Specific research questions to be answered
  • Definition of the population, behavior, or   phenomena being studied
  • Description of the process used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys)

Another hint: some scholarly journals use a specific layout, called the "IMRaD" format, to communicate empirical research findings. Such articles typically have 4 components:

  • Introduction : sometimes called "literature review" -- what is currently known about the topic -- usually includes a theoretical framework and/or discussion of previous studies
  • Methodology: sometimes called "research design" -- how to recreate the study -- usually describes the population, research process, and analytical tools used in the present study
  • Results : sometimes called "findings" -- what was learned through the study -- usually appears as statistical data or as substantial quotations from research participants
  • Discussion : sometimes called "conclusion" or "implications" -- why the study is important -- usually describes how the research results influence professional practices or future studies

Reading and Evaluating Scholarly Materials

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  • CRAAP Checklist A frequently-used checklist that helps you examine the currency, relevance, authority, accuracy, and purpose of an information source.
  • IF I APPLY A newer model of evaluating sources which encourages you to think about your own biases as a reader, as well as concerns about the item you are reading.
  • Credo Video: How to Read Scholarly Materials (4 min.)
  • Credo Tutorial: How to Read Scholarly Materials
  • Credo Tutorial: Evaluating Information
  • Credo Video: Evaluating Statistics (4 min.)
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  • What is Empirical Research Study? [Examples & Method]

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The bulk of human decisions relies on evidence, that is, what can be measured or proven as valid. In choosing between plausible alternatives, individuals are more likely to tilt towards the option that is proven to work, and this is the same approach adopted in empirical research. 

In empirical research, the researcher arrives at outcomes by testing his or her empirical evidence using qualitative or quantitative methods of observation, as determined by the nature of the research. An empirical research study is set apart from other research approaches by its methodology and features hence; it is important for every researcher to know what constitutes this investigation method. 

What is Empirical Research? 

Empirical research is a type of research methodology that makes use of verifiable evidence in order to arrive at research outcomes. In other words, this  type of research relies solely on evidence obtained through observation or scientific data collection methods. 

Empirical research can be carried out using qualitative or quantitative observation methods , depending on the data sample, that is, quantifiable data or non-numerical data . Unlike theoretical research that depends on preconceived notions about the research variables, empirical research carries a scientific investigation to measure the experimental probability of the research variables 

Characteristics of Empirical Research

  • Research Questions

An empirical research begins with a set of research questions that guide the investigation. In many cases, these research questions constitute the research hypothesis which is tested using qualitative and quantitative methods as dictated by the nature of the research.

In an empirical research study, the research questions are built around the core of the research, that is, the central issue which the research seeks to resolve. They also determine the course of the research by highlighting the specific objectives and aims of the systematic investigation. 

  • Definition of the Research Variables

The research variables are clearly defined in terms of their population, types, characteristics, and behaviors. In other words, the data sample is clearly delimited and placed within the context of the research. 

  • Description of the Research Methodology

 An empirical research also clearly outlines the methods adopted in the systematic investigation. Here, the research process is described in detail including the selection criteria for the data sample, qualitative or quantitative research methods plus testing instruments. 

An empirical research is usually divided into 4 parts which are the introduction, methodology, findings, and discussions. The introduction provides a background of the empirical study while the methodology describes the research design, processes, and tools for the systematic investigation. 

The findings refer to the research outcomes and they can be outlined as statistical data or in the form of information obtained through the qualitative observation of research variables. The discussions highlight the significance of the study and its contributions to knowledge. 

Uses of Empirical Research

Without any doubt, empirical research is one of the most useful methods of systematic investigation. It can be used for validating multiple research hypotheses in different fields including Law, Medicine, and Anthropology. 

  • Empirical Research in Law : In Law, empirical research is used to study institutions, rules, procedures, and personnel of the law, with a view to understanding how they operate and what effects they have. It makes use of direct methods rather than secondary sources, and this helps you to arrive at more valid conclusions.
  • Empirical Research in Medicine : In medicine, empirical research is used to test and validate multiple hypotheses and increase human knowledge.
  • Empirical Research in Anthropology : In anthropology, empirical research is used as an evidence-based systematic method of inquiry into patterns of human behaviors and cultures. This helps to validate and advance human knowledge.
Discover how Extrapolation Powers statistical research: Definition, examples, types, and applications explained.

The Empirical Research Cycle

The empirical research cycle is a 5-phase cycle that outlines the systematic processes for conducting and empirical research. It was developed by Dutch psychologist, A.D. de Groot in the 1940s and it aligns 5 important stages that can be viewed as deductive approaches to empirical research. 

In the empirical research methodological cycle, all processes are interconnected and none of the processes is more important than the other. This cycle clearly outlines the different phases involved in generating the research hypotheses and testing these hypotheses systematically using the empirical data. 

  • Observation: This is the process of gathering empirical data for the research. At this stage, the researcher gathers relevant empirical data using qualitative or quantitative observation methods, and this goes ahead to inform the research hypotheses.
  • Induction: At this stage, the researcher makes use of inductive reasoning in order to arrive at a general probable research conclusion based on his or her observation. The researcher generates a general assumption that attempts to explain the empirical data and s/he goes on to observe the empirical data in line with this assumption.
  • Deduction: This is the deductive reasoning stage. This is where the researcher generates hypotheses by applying logic and rationality to his or her observation.
  • Testing: Here, the researcher puts the hypotheses to test using qualitative or quantitative research methods. In the testing stage, the researcher combines relevant instruments of systematic investigation with empirical methods in order to arrive at objective results that support or negate the research hypotheses.
  • Evaluation: The evaluation research is the final stage in an empirical research study. Here, the research outlines the empirical data, the research findings and the supporting arguments plus any challenges encountered during the research process.

This information is useful for further research. 

Learn about qualitative data: uncover its types and examples here.

Examples of Empirical Research 

  • An empirical research study can be carried out to determine if listening to happy music improves the mood of individuals. The researcher may need to conduct an experiment that involves exposing individuals to happy music to see if this improves their moods.

The findings from such an experiment will provide empirical evidence that confirms or refutes the hypotheses. 

  • An empirical research study can also be carried out to determine the effects of a new drug on specific groups of people. The researcher may expose the research subjects to controlled quantities of the drug and observe research subjects to controlled quantities of the drug and observe the effects over a specific period of time to gather empirical data.
  • Another example of empirical research is measuring the levels of noise pollution found in an urban area to determine the average levels of sound exposure experienced by its inhabitants. Here, the researcher may have to administer questionnaires or carry out a survey in order to gather relevant data based on the experiences of the research subjects.
  • Empirical research can also be carried out to determine the relationship between seasonal migration and the body mass of flying birds. A researcher may need to observe the birds and carry out necessary observation and experimentation in order to arrive at objective outcomes that answer the research question.

Empirical Research Data Collection Methods

Empirical data can be gathered using qualitative and quantitative data collection methods. Quantitative data collection methods are used for numerical data gathering while qualitative data collection processes are used to gather empirical data that cannot be quantified, that is, non-numerical data. 

The following are common methods of gathering data in empirical research

  • Survey/ Questionnaire

A survey is a method of data gathering that is typically employed by researchers to gather large sets of data from a specific number of respondents with regards to a research subject. This method of data gathering is often used for quantitative data collection , although it can also be deployed during quantitative research.

A survey contains a set of questions that can range from close-ended to open-ended questions together with other question types that revolve around the research subject. A survey can be administered physically or with the use of online data-gathering platforms like Formplus. 

Empirical data can also be collected by carrying out an experiment. An experiment is a controlled simulation in which one or more of the research variables is manipulated using a set of interconnected processes in order to confirm or refute the research hypotheses.

An experiment is a useful method of measuring causality; that is cause and effect between dependent and independent variables in a research environment. It is an integral data gathering method in an empirical research study because it involves testing calculated assumptions in order to arrive at the most valid data and research outcomes. 

T he case study method is another common data gathering method in an empirical research study. It involves sifting through and analyzing relevant cases and real-life experiences about the research subject or research variables in order to discover in-depth information that can serve as empirical data.

  • Observation

The observational method is a method of qualitative data gathering that requires the researcher to study the behaviors of research variables in their natural environments in order to gather relevant information that can serve as empirical data.

How to collect Empirical Research Data with Questionnaire

With Formplus, you can create a survey or questionnaire for collecting empirical data from your research subjects. Formplus also offers multiple form sharing options so that you can share your empirical research survey to research subjects via a variety of methods.

Here is a step-by-step guide of how to collect empirical data using Formplus:

Sign in to Formplus

empirical-research-data-collection

In the Formplus builder, you can easily create your empirical research survey by dragging and dropping preferred fields into your form. To access the Formplus builder, you will need to create an account on Formplus. 

Once you do this, sign in to your account and click on “Create Form ” to begin. 

Unlock the secrets of Quantitative Data: Click here to explore the types and examples.

Edit Form Title

Click on the field provided to input your form title, for example, “Empirical Research Survey”.

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Edit Form  

  • Click on the edit button to edit the form.
  • Add Fields: Drag and drop preferred form fields into your form in the Formplus builder inputs column. There are several field input options for survey forms in the Formplus builder.
  • Edit fields
  • Click on “Save”
  • Preview form.

empirical-research-survey

Customize Form

Formplus allows you to add unique features to your empirical research survey form. You can personalize your survey using various customization options. Here, you can add background images, your organization’s logo, and use other styling options. You can also change the display theme of your form. 

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  • Share your Form Link with Respondents

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Empirical vs Non-Empirical Research

Empirical and non-empirical research are common methods of systematic investigation employed by researchers. Unlike empirical research that tests hypotheses in order to arrive at valid research outcomes, non-empirical research theorizes the logical assumptions of research variables. 

Definition: Empirical research is a research approach that makes use of evidence-based data while non-empirical research is a research approach that makes use of theoretical data. 

Method: In empirical research, the researcher arrives at valid outcomes by mainly observing research variables, creating a hypothesis and experimenting on research variables to confirm or refute the hypothesis. In non-empirical research, the researcher relies on inductive and deductive reasoning to theorize logical assumptions about the research subjects.

The major difference between the research methodology of empirical and non-empirical research is while the assumptions are tested in empirical research, they are entirely theorized in non-empirical research. 

Data Sample: Empirical research makes use of empirical data while non-empirical research does not make use of empirical data. Empirical data refers to information that is gathered through experience or observation. 

Unlike empirical research, theoretical or non-empirical research does not rely on data gathered through evidence. Rather, it works with logical assumptions and beliefs about the research subject. 

Data Collection Methods : Empirical research makes use of quantitative and qualitative data gathering methods which may include surveys, experiments, and methods of observation. This helps the researcher to gather empirical data, that is, data backed by evidence.  

Non-empirical research, on the other hand, does not make use of qualitative or quantitative methods of data collection . Instead, the researcher gathers relevant data through critical studies, systematic review and meta-analysis. 

Advantages of Empirical Research 

  • Empirical research is flexible. In this type of systematic investigation, the researcher can adjust the research methodology including the data sample size, data gathering methods plus the data analysis methods as necessitated by the research process.
  • It helps the research to understand how the research outcomes can be influenced by different research environments.
  • Empirical research study helps the researcher to develop relevant analytical and observation skills that can be useful in dynamic research contexts.
  • This type of research approach allows the researcher to control multiple research variables in order to arrive at the most relevant research outcomes.
  • Empirical research is widely considered as one of the most authentic and competent research designs.
  • It improves the internal validity of traditional research using a variety of experiments and research observation methods.

Disadvantages of Empirical Research 

  • An empirical research study is time-consuming because the researcher needs to gather the empirical data from multiple resources which typically takes a lot of time.
  • It is not a cost-effective research approach. Usually, this method of research incurs a lot of cost because of the monetary demands of the field research.
  • It may be difficult to gather the needed empirical data sample because of the multiple data gathering methods employed in an empirical research study.
  • It may be difficult to gain access to some communities and firms during the data gathering process and this can affect the validity of the research.
  • The report from an empirical research study is intensive and can be very lengthy in nature.

Conclusion 

Empirical research is an important method of systematic investigation because it gives the researcher the opportunity to test the validity of different assumptions, in the form of hypotheses, before arriving at any findings. Hence, it is a more research approach. 

There are different quantitative and qualitative methods of data gathering employed during an empirical research study based on the purpose of the research which include surveys, experiments, and various observatory methods. Surveys are one of the most common methods or empirical data collection and they can be administered online or physically. 

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empirical evidence

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  • National Center for Biotechnology Information - PubMed Central - Expert opinion vs. empirical evidence
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empirical evidence , information gathered directly or indirectly through observation or experimentation that may be used to confirm or disconfirm a scientific theory or to help justify, or establish as reasonable, a person’s belief in a given proposition. A belief may be said to be justified if there is sufficient evidence to make holding the belief reasonable.

The concept of evidence is the basis of philosophical evidentialism, an epistemological thesis according to which a person is justified in believing a given proposition p if and only if the person’s evidence for p is proper or sufficient. In this context , the Scottish Enlightenment philosopher David Hume (1711–76) famously asserted that the “wise man…proportions his belief to the evidence.” In a similar vein, the American astronomer Carl Sagan popularized the statement, “Extraordinary claims require extraordinary evidence.”

Foundationalists , however, defend the view that certain basic, or foundational, beliefs are either inherently justified or justified by something other than another belief (e.g., a sensation or perception) and that all other beliefs may be justified only if they are directly or indirectly supported by at least one foundational belief (that is, only if they are either supported by at least one foundational belief or supported by other beliefs that are themselves supported by at least one foundational belief). The most influential foundationalist of the modern period was the French philosopher and mathematician René Descartes (1596–1650), who attempted to establish a foundation for justified beliefs regarding an external world in his intuition that, for as long as he is thinking, he exists (“I think, therefore I am”; see cogito, ergo sum ). A traditional argument in favour of foundationalism asserts that no other account of inferential justification—the act of justifying a given belief by inferring it from another belief that itself is justified—is possible. Thus, assume that one belief, Belief 1, is justified by another belief, Belief 2. How is Belief 2 justified? It cannot be justified by Belief 1, because the inference from Belief 2 to Belief 1 would then be circular and invalid. It cannot be justified by a third nonfoundational Belief 3, because the same question would then apply to that belief, leading to an infinite regress. And one cannot simply assume that Belief 2 is not justified, for then Belief 1 would not be justified through the inference from Belief 2. Accordingly, there must be some beliefs whose justification does not depend on other beliefs, and those justified beliefs must function as a foundation for the inferential justification of other beliefs.

Empirical evidence can be quantitative or qualitative. Typically, numerical quantitative evidence can be represented visually by means of diagrams, graphs, or charts, reflecting the use of statistical or mathematical data and the researcher’s neutral noninteractive role. It can be obtained by methods such as experiments, surveys, correlational research (to study the relationship between variables), cross-sectional research (to compare different groups), causal-comparative research (to explore cause-effect relationships), and longitudinal studies (to test a subject during a given time period).

Qualitative evidence, on the other hand, can foster a deeper understanding of behaviour and related factors and is not typically expressed by using numbers. Often subjective and resulting from interaction between the researcher and participants, it can stem from the use of methods such as interviews (based on verbal interaction), observation (informing ethnographic research design), textual analysis (involving the description and interpretation of texts), focus groups (planned group discussions), and case studies (in-depth analyses of individuals or groups).

Empirical evidence is subject to assessments of its validity. Validity can be internal, involving the soundness of an experiment’s design and execution and the accuracy of subsequent data analysis , or external, involving generalizability to other research contexts ( see ecological validity ).

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empirical research

Empirical research relies on gathering and studying real, observable data. The term ’empirical’ comes from the Greek word ’empeirikos,’ meaning ‘experienced’ or ‘based on experience.’ So, what is empirical research? Instead of using theories or opinions, empirical research depends on real data obtained through direct observation or experimentation. 

Why Empirical Research?

Empirical research plays a key role in checking or improving current theories, providing a systematic way to grow knowledge across different areas. By focusing on objectivity, it makes research findings more trustworthy, which is critical in research fields like medicine, psychology, economics, and public policy. In the end, the strengths of empirical research lie in deepening our awareness of the world and improving our capacity to tackle problems wisely. 1,2  

Qualitative and Quantitative Methods

There are two main types of empirical research methods – qualitative and quantitative. 3,4 Qualitative research delves into intricate phenomena using non-numerical data, such as interviews or observations, to offer in-depth insights into human experiences. In contrast, quantitative research analyzes numerical data to spot patterns and relationships, aiming for objectivity and the ability to apply findings to a wider context. 

Steps for Conducting Empirical Research

When it comes to conducting research, there are some simple steps that researchers can follow. 5,6  

  • Create Research Hypothesis:  Clearly state the specific question you want to answer or the hypothesis you want to explore in your study. 
  • Examine Existing Research:  Read and study existing research on your topic. Understand what’s already known, identify existing gaps in knowledge, and create a framework for your own study based on what you learn. 
  • Plan Your Study:  Decide how you’ll conduct your research—whether through qualitative methods, quantitative methods, or a mix of both. Choose suitable techniques like surveys, experiments, interviews, or observations based on your research question. 
  • Develop Research Instruments:  Create reliable research collection tools, such as surveys or questionnaires, to help you collate data. Ensure these tools are well-designed and effective. 
  • Collect Data:  Systematically gather the information you need for your research according to your study design and protocols using the chosen research methods. 
  • Data Analysis:  Analyze the collected data using suitable statistical or qualitative methods that align with your research question and objectives. 
  • Interpret Results:  Understand and explain the significance of your analysis results in the context of your research question or hypothesis. 
  • Draw Conclusions:  Summarize your findings and draw conclusions based on the evidence. Acknowledge any study limitations and propose areas for future research. 

Advantages of Empirical Research

Empirical research is valuable because it stays objective by relying on observable data, lessening the impact of personal biases. This objectivity boosts the trustworthiness of research findings. Also, using precise quantitative methods helps in accurate measurement and statistical analysis. This precision ensures researchers can draw reliable conclusions from numerical data, strengthening our understanding of the studied phenomena. 4  

Disadvantages of Empirical Research

While empirical research has notable strengths, researchers must also be aware of its limitations when deciding on the right research method for their study.4 One significant drawback of empirical research is the risk of oversimplifying complex phenomena, especially when relying solely on quantitative methods. These methods may struggle to capture the richness and nuances present in certain social, cultural, or psychological contexts. Another challenge is the potential for confounding variables or biases during data collection, impacting result accuracy.  

Tips for Empirical Writing

In empirical research, the writing is usually done in research papers, articles, or reports. The empirical writing follows a set structure, and each section has a specific role. Here are some tips for your empirical writing. 7   

  • Define Your Objectives:  When you write about your research, start by making your goals clear. Explain what you want to find out or prove in a simple and direct way. This helps guide your research and lets others know what you have set out to achieve. 
  • Be Specific in Your Literature Review:  In the part where you talk about what others have studied before you, focus on research that directly relates to your research question. Keep it short and pick studies that help explain why your research is important. This part sets the stage for your work. 
  • Explain Your Methods Clearly : When you talk about how you did your research (Methods), explain it in detail. Be clear about your research plan, who took part, and what you did; this helps others understand and trust your study. Also, be honest about any rules you follow to make sure your study is ethical and reproducible. 
  • Share Your Results Clearly : After doing your empirical research, share what you found in a simple way. Use tables or graphs to make it easier for your audience to understand your research. Also, talk about any numbers you found and clearly state if they are important or not. Ensure that others can see why your research findings matter. 
  • Talk About What Your Findings Mean:  In the part where you discuss your research results, explain what they mean. Discuss why your findings are important and if they connect to what others have found before. Be honest about any problems with your study and suggest ideas for more research in the future. 
  • Wrap It Up Clearly:  Finally, end your empirical research paper by summarizing what you found and why it’s important. Remind everyone why your study matters. Keep your writing clear and fix any mistakes before you share it. Ask someone you trust to read it and give you feedback before you finish. 

References:  

  • Empirical Research in the Social Sciences and Education, Penn State University Libraries. Available online at  https://guides.libraries.psu.edu/emp  
  • How to conduct empirical research, Emerald Publishing. Available online at  https://www.emeraldgrouppublishing.com/how-to/research-methods/conduct-empirical-research  
  • Empirical Research: Quantitative & Qualitative, Arrendale Library, Piedmont University. Available online at  https://library.piedmont.edu/empirical-research  
  • Bouchrika, I.  What Is Empirical Research? Definition, Types & Samples  in 2024. Research.com, January 2024. Available online at  https://research.com/research/what-is-empirical-research  
  • Quantitative and Empirical Research vs. Other Types of Research. California State University, April 2023. Available online at  https://libguides.csusb.edu/quantitative  
  • Empirical Research, Definitions, Methods, Types and Examples, Studocu.com website. Available online at  https://www.studocu.com/row/document/uganda-christian-university/it-research-methods/emperical-research-definitions-methods-types-and-examples/55333816  
  • Writing an Empirical Paper in APA Style. Psychology Writing Center, University of Washington. Available online at  https://psych.uw.edu/storage/writing_center/APApaper.pdf  

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Empirical research  is based on phenomena that can be observed and measured. Empirical research derives knowledge from actual experience rather than from theory or belief. 

Key characteristics of empirical research include:

  • Specific research questions to be answered;
  • Definitions of the population, behavior, or phenomena being studied;
  • Description of the methodology or research design used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys);
  • Two basic research processes or methods in empirical research: quantitative methods and qualitative methods (see the rest of the guide for more about these methods).

(based on the original from the Connelly LIbrary of LaSalle University)

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Quantitative Research

A quantitative research project is characterized by having a population about which the researcher wants to draw conclusions, but it is not possible to collect data on the entire population.

  • For an observational study, it is necessary to select a proper, statistical random sample and to use methods of statistical inference to draw conclusions about the population. 
  • For an experimental study, it is necessary to have a random assignment of subjects to experimental and control groups in order to use methods of statistical inference.

Statistical methods are used in all three stages of a quantitative research project.

For observational studies, the data are collected using statistical sampling theory. Then, the sample data are analyzed using descriptive statistical analysis. Finally, generalizations are made from the sample data to the entire population using statistical inference.

For experimental studies, the subjects are allocated to experimental and control group using randomizing methods. Then, the experimental data are analyzed using descriptive statistical analysis. Finally, just as for observational data, generalizations are made to a larger population.

Iversen, G. (2004). Quantitative research . In M. Lewis-Beck, A. Bryman, & T. Liao (Eds.), Encyclopedia of social science research methods . (pp. 897-898). Thousand Oaks, CA: SAGE Publications, Inc.

Qualitative Research

What makes a work deserving of the label qualitative research is the demonstrable effort to produce richly and relevantly detailed descriptions and particularized interpretations of people and the social, linguistic, material, and other practices and events that shape and are shaped by them.

Qualitative research typically includes, but is not limited to, discerning the perspectives of these people, or what is often referred to as the actor’s point of view. Although both philosophically and methodologically a highly diverse entity, qualitative research is marked by certain defining imperatives that include its case (as opposed to its variable) orientation, sensitivity to cultural and historical context, and reflexivity. 

In its many guises, qualitative research is a form of empirical inquiry that typically entails some form of purposive sampling for information-rich cases; in-depth interviews and open-ended interviews, lengthy participant/field observations, and/or document or artifact study; and techniques for analysis and interpretation of data that move beyond the data generated and their surface appearances. 

Sandelowski, M. (2004).  Qualitative research . In M. Lewis-Beck, A. Bryman, & T. Liao (Eds.),  Encyclopedia of social science research methods . (pp. 893-894). Thousand Oaks, CA: SAGE Publications, Inc.

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What is Empirical Research? Definition, Methods, Examples

Appinio Research · 09.02.2024 · 36min read

What is Empirical Research Definition Methods Examples

Ever wondered how we gather the facts, unveil hidden truths, and make informed decisions in a world filled with questions? Empirical research holds the key.

In this guide, we'll delve deep into the art and science of empirical research, unraveling its methods, mysteries, and manifold applications. From defining the core principles to mastering data analysis and reporting findings, we're here to equip you with the knowledge and tools to navigate the empirical landscape.

What is Empirical Research?

Empirical research is the cornerstone of scientific inquiry, providing a systematic and structured approach to investigating the world around us. It is the process of gathering and analyzing empirical or observable data to test hypotheses, answer research questions, or gain insights into various phenomena. This form of research relies on evidence derived from direct observation or experimentation, allowing researchers to draw conclusions based on real-world data rather than purely theoretical or speculative reasoning.

Characteristics of Empirical Research

Empirical research is characterized by several key features:

  • Observation and Measurement : It involves the systematic observation or measurement of variables, events, or behaviors.
  • Data Collection : Researchers collect data through various methods, such as surveys, experiments, observations, or interviews.
  • Testable Hypotheses : Empirical research often starts with testable hypotheses that are evaluated using collected data.
  • Quantitative or Qualitative Data : Data can be quantitative (numerical) or qualitative (non-numerical), depending on the research design.
  • Statistical Analysis : Quantitative data often undergo statistical analysis to determine patterns , relationships, or significance.
  • Objectivity and Replicability : Empirical research strives for objectivity, minimizing researcher bias . It should be replicable, allowing other researchers to conduct the same study to verify results.
  • Conclusions and Generalizations : Empirical research generates findings based on data and aims to make generalizations about larger populations or phenomena.

Importance of Empirical Research

Empirical research plays a pivotal role in advancing knowledge across various disciplines. Its importance extends to academia, industry, and society as a whole. Here are several reasons why empirical research is essential:

  • Evidence-Based Knowledge : Empirical research provides a solid foundation of evidence-based knowledge. It enables us to test hypotheses, confirm or refute theories, and build a robust understanding of the world.
  • Scientific Progress : In the scientific community, empirical research fuels progress by expanding the boundaries of existing knowledge. It contributes to the development of theories and the formulation of new research questions.
  • Problem Solving : Empirical research is instrumental in addressing real-world problems and challenges. It offers insights and data-driven solutions to complex issues in fields like healthcare, economics, and environmental science.
  • Informed Decision-Making : In policymaking, business, and healthcare, empirical research informs decision-makers by providing data-driven insights. It guides strategies, investments, and policies for optimal outcomes.
  • Quality Assurance : Empirical research is essential for quality assurance and validation in various industries, including pharmaceuticals, manufacturing, and technology. It ensures that products and processes meet established standards.
  • Continuous Improvement : Businesses and organizations use empirical research to evaluate performance, customer satisfaction, and product effectiveness. This data-driven approach fosters continuous improvement and innovation.
  • Human Advancement : Empirical research in fields like medicine and psychology contributes to the betterment of human health and well-being. It leads to medical breakthroughs, improved therapies, and enhanced psychological interventions.
  • Critical Thinking and Problem Solving : Engaging in empirical research fosters critical thinking skills, problem-solving abilities, and a deep appreciation for evidence-based decision-making.

Empirical research empowers us to explore, understand, and improve the world around us. It forms the bedrock of scientific inquiry and drives progress in countless domains, shaping our understanding of both the natural and social sciences.

How to Conduct Empirical Research?

So, you've decided to dive into the world of empirical research. Let's begin by exploring the crucial steps involved in getting started with your research project.

1. Select a Research Topic

Selecting the right research topic is the cornerstone of a successful empirical study. It's essential to choose a topic that not only piques your interest but also aligns with your research goals and objectives. Here's how to go about it:

  • Identify Your Interests : Start by reflecting on your passions and interests. What topics fascinate you the most? Your enthusiasm will be your driving force throughout the research process.
  • Brainstorm Ideas : Engage in brainstorming sessions to generate potential research topics. Consider the questions you've always wanted to answer or the issues that intrigue you.
  • Relevance and Significance : Assess the relevance and significance of your chosen topic. Does it contribute to existing knowledge? Is it a pressing issue in your field of study or the broader community?
  • Feasibility : Evaluate the feasibility of your research topic. Do you have access to the necessary resources, data, and participants (if applicable)?

2. Formulate Research Questions

Once you've narrowed down your research topic, the next step is to formulate clear and precise research questions . These questions will guide your entire research process and shape your study's direction. To create effective research questions:

  • Specificity : Ensure that your research questions are specific and focused. Vague or overly broad questions can lead to inconclusive results.
  • Relevance : Your research questions should directly relate to your chosen topic. They should address gaps in knowledge or contribute to solving a particular problem.
  • Testability : Ensure that your questions are testable through empirical methods. You should be able to gather data and analyze it to answer these questions.
  • Avoid Bias : Craft your questions in a way that avoids leading or biased language. Maintain neutrality to uphold the integrity of your research.

3. Review Existing Literature

Before you embark on your empirical research journey, it's essential to immerse yourself in the existing body of literature related to your chosen topic. This step, often referred to as a literature review, serves several purposes:

  • Contextualization : Understand the historical context and current state of research in your field. What have previous studies found, and what questions remain unanswered?
  • Identifying Gaps : Identify gaps or areas where existing research falls short. These gaps will help you formulate meaningful research questions and hypotheses.
  • Theory Development : If your study is theoretical, consider how existing theories apply to your topic. If it's empirical, understand how previous studies have approached data collection and analysis.
  • Methodological Insights : Learn from the methodologies employed in previous research. What methods were successful, and what challenges did researchers face?

4. Define Variables

Variables are fundamental components of empirical research. They are the factors or characteristics that can change or be manipulated during your study. Properly defining and categorizing variables is crucial for the clarity and validity of your research. Here's what you need to know:

  • Independent Variables : These are the variables that you, as the researcher, manipulate or control. They are the "cause" in cause-and-effect relationships.
  • Dependent Variables : Dependent variables are the outcomes or responses that you measure or observe. They are the "effect" influenced by changes in independent variables.
  • Operational Definitions : To ensure consistency and clarity, provide operational definitions for your variables. Specify how you will measure or manipulate each variable.
  • Control Variables : In some studies, controlling for other variables that may influence your dependent variable is essential. These are known as control variables.

Understanding these foundational aspects of empirical research will set a solid foundation for the rest of your journey. Now that you've grasped the essentials of getting started, let's delve deeper into the intricacies of research design.

Empirical Research Design

Now that you've selected your research topic, formulated research questions, and defined your variables, it's time to delve into the heart of your empirical research journey – research design . This pivotal step determines how you will collect data and what methods you'll employ to answer your research questions. Let's explore the various facets of research design in detail.

Types of Empirical Research

Empirical research can take on several forms, each with its own unique approach and methodologies. Understanding the different types of empirical research will help you choose the most suitable design for your study. Here are some common types:

  • Experimental Research : In this type, researchers manipulate one or more independent variables to observe their impact on dependent variables. It's highly controlled and often conducted in a laboratory setting.
  • Observational Research : Observational research involves the systematic observation of subjects or phenomena without intervention. Researchers are passive observers, documenting behaviors, events, or patterns.
  • Survey Research : Surveys are used to collect data through structured questionnaires or interviews. This method is efficient for gathering information from a large number of participants.
  • Case Study Research : Case studies focus on in-depth exploration of one or a few cases. Researchers gather detailed information through various sources such as interviews, documents, and observations.
  • Qualitative Research : Qualitative research aims to understand behaviors, experiences, and opinions in depth. It often involves open-ended questions, interviews, and thematic analysis.
  • Quantitative Research : Quantitative research collects numerical data and relies on statistical analysis to draw conclusions. It involves structured questionnaires, experiments, and surveys.

Your choice of research type should align with your research questions and objectives. Experimental research, for example, is ideal for testing cause-and-effect relationships, while qualitative research is more suitable for exploring complex phenomena.

Experimental Design

Experimental research is a systematic approach to studying causal relationships. It's characterized by the manipulation of one or more independent variables while controlling for other factors. Here are some key aspects of experimental design:

  • Control and Experimental Groups : Participants are randomly assigned to either a control group or an experimental group. The independent variable is manipulated for the experimental group but not for the control group.
  • Randomization : Randomization is crucial to eliminate bias in group assignment. It ensures that each participant has an equal chance of being in either group.
  • Hypothesis Testing : Experimental research often involves hypothesis testing. Researchers formulate hypotheses about the expected effects of the independent variable and use statistical analysis to test these hypotheses.

Observational Design

Observational research entails careful and systematic observation of subjects or phenomena. It's advantageous when you want to understand natural behaviors or events. Key aspects of observational design include:

  • Participant Observation : Researchers immerse themselves in the environment they are studying. They become part of the group being observed, allowing for a deep understanding of behaviors.
  • Non-Participant Observation : In non-participant observation, researchers remain separate from the subjects. They observe and document behaviors without direct involvement.
  • Data Collection Methods : Observational research can involve various data collection methods, such as field notes, video recordings, photographs, or coding of observed behaviors.

Survey Design

Surveys are a popular choice for collecting data from a large number of participants. Effective survey design is essential to ensure the validity and reliability of your data. Consider the following:

  • Questionnaire Design : Create clear and concise questions that are easy for participants to understand. Avoid leading or biased questions.
  • Sampling Methods : Decide on the appropriate sampling method for your study, whether it's random, stratified, or convenience sampling.
  • Data Collection Tools : Choose the right tools for data collection, whether it's paper surveys, online questionnaires, or face-to-face interviews.

Case Study Design

Case studies are an in-depth exploration of one or a few cases to gain a deep understanding of a particular phenomenon. Key aspects of case study design include:

  • Single Case vs. Multiple Case Studies : Decide whether you'll focus on a single case or multiple cases. Single case studies are intensive and allow for detailed examination, while multiple case studies provide comparative insights.
  • Data Collection Methods : Gather data through interviews, observations, document analysis, or a combination of these methods.

Qualitative vs. Quantitative Research

In empirical research, you'll often encounter the distinction between qualitative and quantitative research . Here's a closer look at these two approaches:

  • Qualitative Research : Qualitative research seeks an in-depth understanding of human behavior, experiences, and perspectives. It involves open-ended questions, interviews, and the analysis of textual or narrative data. Qualitative research is exploratory and often used when the research question is complex and requires a nuanced understanding.
  • Quantitative Research : Quantitative research collects numerical data and employs statistical analysis to draw conclusions. It involves structured questionnaires, experiments, and surveys. Quantitative research is ideal for testing hypotheses and establishing cause-and-effect relationships.

Understanding the various research design options is crucial in determining the most appropriate approach for your study. Your choice should align with your research questions, objectives, and the nature of the phenomenon you're investigating.

Data Collection for Empirical Research

Now that you've established your research design, it's time to roll up your sleeves and collect the data that will fuel your empirical research. Effective data collection is essential for obtaining accurate and reliable results.

Sampling Methods

Sampling methods are critical in empirical research, as they determine the subset of individuals or elements from your target population that you will study. Here are some standard sampling methods:

  • Random Sampling : Random sampling ensures that every member of the population has an equal chance of being selected. It minimizes bias and is often used in quantitative research.
  • Stratified Sampling : Stratified sampling involves dividing the population into subgroups or strata based on specific characteristics (e.g., age, gender, location). Samples are then randomly selected from each stratum, ensuring representation of all subgroups.
  • Convenience Sampling : Convenience sampling involves selecting participants who are readily available or easily accessible. While it's convenient, it may introduce bias and limit the generalizability of results.
  • Snowball Sampling : Snowball sampling is instrumental when studying hard-to-reach or hidden populations. One participant leads you to another, creating a "snowball" effect. This method is common in qualitative research.
  • Purposive Sampling : In purposive sampling, researchers deliberately select participants who meet specific criteria relevant to their research questions. It's often used in qualitative studies to gather in-depth information.

The choice of sampling method depends on the nature of your research, available resources, and the degree of precision required. It's crucial to carefully consider your sampling strategy to ensure that your sample accurately represents your target population.

Data Collection Instruments

Data collection instruments are the tools you use to gather information from your participants or sources. These instruments should be designed to capture the data you need accurately. Here are some popular data collection instruments:

  • Questionnaires : Questionnaires consist of structured questions with predefined response options. When designing questionnaires, consider the clarity of questions, the order of questions, and the response format (e.g., Likert scale , multiple-choice).
  • Interviews : Interviews involve direct communication between the researcher and participants. They can be structured (with predetermined questions) or unstructured (open-ended). Effective interviews require active listening and probing for deeper insights.
  • Observations : Observations entail systematically and objectively recording behaviors, events, or phenomena. Researchers must establish clear criteria for what to observe, how to record observations, and when to observe.
  • Surveys : Surveys are a common data collection instrument for quantitative research. They can be administered through various means, including online surveys, paper surveys, and telephone surveys.
  • Documents and Archives : In some cases, data may be collected from existing documents, records, or archives. Ensure that the sources are reliable, relevant, and properly documented.

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Data Collection Procedures

Data collection procedures outline the step-by-step process for gathering data. These procedures should be meticulously planned and executed to maintain the integrity of your research.

  • Training : If you have a research team, ensure that they are trained in data collection methods and protocols. Consistency in data collection is crucial.
  • Pilot Testing : Before launching your data collection, conduct a pilot test with a small group to identify any potential problems with your instruments or procedures. Make necessary adjustments based on feedback.
  • Data Recording : Establish a systematic method for recording data. This may include timestamps, codes, or identifiers for each data point.
  • Data Security : Safeguard the confidentiality and security of collected data. Ensure that only authorized individuals have access to the data.
  • Data Storage : Properly organize and store your data in a secure location, whether in physical or digital form. Back up data to prevent loss.

Ethical Considerations

Ethical considerations are paramount in empirical research, as they ensure the well-being and rights of participants are protected.

  • Informed Consent : Obtain informed consent from participants, providing clear information about the research purpose, procedures, risks, and their right to withdraw at any time.
  • Privacy and Confidentiality : Protect the privacy and confidentiality of participants. Ensure that data is anonymized and sensitive information is kept confidential.
  • Beneficence : Ensure that your research benefits participants and society while minimizing harm. Consider the potential risks and benefits of your study.
  • Honesty and Integrity : Conduct research with honesty and integrity. Report findings accurately and transparently, even if they are not what you expected.
  • Respect for Participants : Treat participants with respect, dignity, and sensitivity to cultural differences. Avoid any form of coercion or manipulation.
  • Institutional Review Board (IRB) : If required, seek approval from an IRB or ethics committee before conducting your research, particularly when working with human participants.

Adhering to ethical guidelines is not only essential for the ethical conduct of research but also crucial for the credibility and validity of your study. Ethical research practices build trust between researchers and participants and contribute to the advancement of knowledge with integrity.

With a solid understanding of data collection, including sampling methods, instruments, procedures, and ethical considerations, you are now well-equipped to gather the data needed to answer your research questions.

Empirical Research Data Analysis

Now comes the exciting phase of data analysis, where the raw data you've diligently collected starts to yield insights and answers to your research questions. We will explore the various aspects of data analysis, from preparing your data to drawing meaningful conclusions through statistics and visualization.

Data Preparation

Data preparation is the crucial first step in data analysis. It involves cleaning, organizing, and transforming your raw data into a format that is ready for analysis. Effective data preparation ensures the accuracy and reliability of your results.

  • Data Cleaning : Identify and rectify errors, missing values, and inconsistencies in your dataset. This may involve correcting typos, removing outliers, and imputing missing data.
  • Data Coding : Assign numerical values or codes to categorical variables to make them suitable for statistical analysis. For example, converting "Yes" and "No" to 1 and 0.
  • Data Transformation : Transform variables as needed to meet the assumptions of the statistical tests you plan to use. Common transformations include logarithmic or square root transformations.
  • Data Integration : If your data comes from multiple sources, integrate it into a unified dataset, ensuring that variables match and align.
  • Data Documentation : Maintain clear documentation of all data preparation steps, as well as the rationale behind each decision. This transparency is essential for replicability.

Effective data preparation lays the foundation for accurate and meaningful analysis. It allows you to trust the results that will follow in the subsequent stages.

Descriptive Statistics

Descriptive statistics help you summarize and make sense of your data by providing a clear overview of its key characteristics. These statistics are essential for understanding the central tendencies, variability, and distribution of your variables. Descriptive statistics include:

  • Measures of Central Tendency : These include the mean (average), median (middle value), and mode (most frequent value). They help you understand the typical or central value of your data.
  • Measures of Dispersion : Measures like the range, variance, and standard deviation provide insights into the spread or variability of your data points.
  • Frequency Distributions : Creating frequency distributions or histograms allows you to visualize the distribution of your data across different values or categories.

Descriptive statistics provide the initial insights needed to understand your data's basic characteristics, which can inform further analysis.

Inferential Statistics

Inferential statistics take your analysis to the next level by allowing you to make inferences or predictions about a larger population based on your sample data. These methods help you test hypotheses and draw meaningful conclusions. Key concepts in inferential statistics include:

  • Hypothesis Testing : Hypothesis tests (e.g., t-tests , chi-squared tests ) help you determine whether observed differences or associations in your data are statistically significant or occurred by chance.
  • Confidence Intervals : Confidence intervals provide a range within which population parameters (e.g., population mean) are likely to fall based on your sample data.
  • Regression Analysis : Regression models (linear, logistic, etc.) help you explore relationships between variables and make predictions.
  • Analysis of Variance (ANOVA) : ANOVA tests are used to compare means between multiple groups, allowing you to assess whether differences are statistically significant.

Inferential statistics are powerful tools for drawing conclusions from your data and assessing the generalizability of your findings to the broader population.

Qualitative Data Analysis

Qualitative data analysis is employed when working with non-numerical data, such as text, interviews, or open-ended survey responses. It focuses on understanding the underlying themes, patterns, and meanings within qualitative data. Qualitative analysis techniques include:

  • Thematic Analysis : Identifying and analyzing recurring themes or patterns within textual data.
  • Content Analysis : Categorizing and coding qualitative data to extract meaningful insights.
  • Grounded Theory : Developing theories or frameworks based on emergent themes from the data.
  • Narrative Analysis : Examining the structure and content of narratives to uncover meaning.

Qualitative data analysis provides a rich and nuanced understanding of complex phenomena and human experiences.

Data Visualization

Data visualization is the art of representing data graphically to make complex information more understandable and accessible. Effective data visualization can reveal patterns, trends, and outliers in your data. Common types of data visualization include:

  • Bar Charts and Histograms : Used to display the distribution of categorical data or discrete data .
  • Line Charts : Ideal for showing trends and changes in data over time.
  • Scatter Plots : Visualize relationships and correlations between two variables.
  • Pie Charts : Display the composition of a whole in terms of its parts.
  • Heatmaps : Depict patterns and relationships in multidimensional data through color-coding.
  • Box Plots : Provide a summary of the data distribution, including outliers.
  • Interactive Dashboards : Create dynamic visualizations that allow users to explore data interactively.

Data visualization not only enhances your understanding of the data but also serves as a powerful communication tool to convey your findings to others.

As you embark on the data analysis phase of your empirical research, remember that the specific methods and techniques you choose will depend on your research questions, data type, and objectives. Effective data analysis transforms raw data into valuable insights, bringing you closer to the answers you seek.

How to Report Empirical Research Results?

At this stage, you get to share your empirical research findings with the world. Effective reporting and presentation of your results are crucial for communicating your research's impact and insights.

1. Write the Research Paper

Writing a research paper is the culmination of your empirical research journey. It's where you synthesize your findings, provide context, and contribute to the body of knowledge in your field.

  • Title and Abstract : Craft a clear and concise title that reflects your research's essence. The abstract should provide a brief summary of your research objectives, methods, findings, and implications.
  • Introduction : In the introduction, introduce your research topic, state your research questions or hypotheses, and explain the significance of your study. Provide context by discussing relevant literature.
  • Methods : Describe your research design, data collection methods, and sampling procedures. Be precise and transparent, allowing readers to understand how you conducted your study.
  • Results : Present your findings in a clear and organized manner. Use tables, graphs, and statistical analyses to support your results. Avoid interpreting your findings in this section; focus on the presentation of raw data.
  • Discussion : Interpret your findings and discuss their implications. Relate your results to your research questions and the existing literature. Address any limitations of your study and suggest avenues for future research.
  • Conclusion : Summarize the key points of your research and its significance. Restate your main findings and their implications.
  • References : Cite all sources used in your research following a specific citation style (e.g., APA, MLA, Chicago). Ensure accuracy and consistency in your citations.
  • Appendices : Include any supplementary material, such as questionnaires, data coding sheets, or additional analyses, in the appendices.

Writing a research paper is a skill that improves with practice. Ensure clarity, coherence, and conciseness in your writing to make your research accessible to a broader audience.

2. Create Visuals and Tables

Visuals and tables are powerful tools for presenting complex data in an accessible and understandable manner.

  • Clarity : Ensure that your visuals and tables are clear and easy to interpret. Use descriptive titles and labels.
  • Consistency : Maintain consistency in formatting, such as font size and style, across all visuals and tables.
  • Appropriateness : Choose the most suitable visual representation for your data. Bar charts, line graphs, and scatter plots work well for different types of data.
  • Simplicity : Avoid clutter and unnecessary details. Focus on conveying the main points.
  • Accessibility : Make sure your visuals and tables are accessible to a broad audience, including those with visual impairments.
  • Captions : Include informative captions that explain the significance of each visual or table.

Compelling visuals and tables enhance the reader's understanding of your research and can be the key to conveying complex information efficiently.

3. Interpret Findings

Interpreting your findings is where you bridge the gap between data and meaning. It's your opportunity to provide context, discuss implications, and offer insights. When interpreting your findings:

  • Relate to Research Questions : Discuss how your findings directly address your research questions or hypotheses.
  • Compare with Literature : Analyze how your results align with or deviate from previous research in your field. What insights can you draw from these comparisons?
  • Discuss Limitations : Be transparent about the limitations of your study. Address any constraints, biases, or potential sources of error.
  • Practical Implications : Explore the real-world implications of your findings. How can they be applied or inform decision-making?
  • Future Research Directions : Suggest areas for future research based on the gaps or unanswered questions that emerged from your study.

Interpreting findings goes beyond simply presenting data; it's about weaving a narrative that helps readers grasp the significance of your research in the broader context.

With your research paper written, structured, and enriched with visuals, and your findings expertly interpreted, you are now prepared to communicate your research effectively. Sharing your insights and contributing to the body of knowledge in your field is a significant accomplishment in empirical research.

Examples of Empirical Research

To solidify your understanding of empirical research, let's delve into some real-world examples across different fields. These examples will illustrate how empirical research is applied to gather data, analyze findings, and draw conclusions.

Social Sciences

In the realm of social sciences, consider a sociological study exploring the impact of socioeconomic status on educational attainment. Researchers gather data from a diverse group of individuals, including their family backgrounds, income levels, and academic achievements.

Through statistical analysis, they can identify correlations and trends, revealing whether individuals from lower socioeconomic backgrounds are less likely to attain higher levels of education. This empirical research helps shed light on societal inequalities and informs policymakers on potential interventions to address disparities in educational access.

Environmental Science

Environmental scientists often employ empirical research to assess the effects of environmental changes. For instance, researchers studying the impact of climate change on wildlife might collect data on animal populations, weather patterns, and habitat conditions over an extended period.

By analyzing this empirical data, they can identify correlations between climate fluctuations and changes in wildlife behavior, migration patterns, or population sizes. This empirical research is crucial for understanding the ecological consequences of climate change and informing conservation efforts.

Business and Economics

In the business world, empirical research is essential for making data-driven decisions. Consider a market research study conducted by a business seeking to launch a new product. They collect data through surveys , focus groups , and consumer behavior analysis.

By examining this empirical data, the company can gauge consumer preferences, demand, and potential market size. Empirical research in business helps guide product development, pricing strategies, and marketing campaigns, increasing the likelihood of a successful product launch.

Psychological studies frequently rely on empirical research to understand human behavior and cognition. For instance, a psychologist interested in examining the impact of stress on memory might design an experiment. Participants are exposed to stress-inducing situations, and their memory performance is assessed through various tasks.

By analyzing the data collected, the psychologist can determine whether stress has a significant effect on memory recall. This empirical research contributes to our understanding of the complex interplay between psychological factors and cognitive processes.

These examples highlight the versatility and applicability of empirical research across diverse fields. Whether in medicine, social sciences, environmental science, business, or psychology, empirical research serves as a fundamental tool for gaining insights, testing hypotheses, and driving advancements in knowledge and practice.

Conclusion for Empirical Research

Empirical research is a powerful tool for gaining insights, testing hypotheses, and making informed decisions. By following the steps outlined in this guide, you've learned how to select research topics, collect data, analyze findings, and effectively communicate your research to the world. Remember, empirical research is a journey of discovery, and each step you take brings you closer to a deeper understanding of the world around you. Whether you're a scientist, a student, or someone curious about the process, the principles of empirical research empower you to explore, learn, and contribute to the ever-expanding realm of knowledge.

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Research Guides

Empirical Research: What is empirical research?

What is empirical research.

  • How do I find empirical research in databases?
  • What does empirical research look like?
  • How is empirical research conducted?
  • What is Empirical Research?
  • How do I Find Empirical Research in Databases?
  • How is Empirical Research Conducted?

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Empirical research  is based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief. 

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology."  Ask yourself: Could I recreate this study and test these results?

Key characteristics to look for:

  • Specific research questions  to be answered
  • Definition of the  population, behavior, or   phenomena  being studied
  • Description of the  process  used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys)

Another hint: some scholarly journals use a specific layout, called the "IMRaD" format, to communicate empirical research findings. Such articles typically have 4 components:

  • Introduction : sometimes called "literature review" -- what is currently known about the topic -- usually includes a theoretical framework and/or discussion of previous studies
  • Methodology:  sometimes called "research design" --  how to recreate the study -- usually describes the population, research process, and analytical tools
  • Results : sometimes called "findings"  --  what was learned through the study -- usually appears as statistical data or as substantial quotations from research participants
  • Discussion : sometimes called "conclusion" or "implications" -- why the study is important -- usually describes how the research results influence professional practices or future studies

What about when research is not empirical?

Many humanities scholars do not use empirical methods. if you are looking for empirical articles in one of these subject areas, try including keywords like:.

  • quantitative
  • qualitative

Also, look for opportunities to narrow your search to scholarly, academic, or peer-reviewed journals articles in the database.

Adapted from " Research Methods: Finding Empirical Articles " by Jill Anderson at Georgia State University Library.

See the complete A-Z databases list for more resources

The primary content of this guide was originally created by  Ellysa  Cahoy at Penn State Libraries .

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Sometimes you may be asked to find and use empirical research. If you aren't sure what is and is not empirical research, this might seem scary. We are here to help. 

Note:  while this guide is designed to help you understand and find empirical research, you should always default to your instructor's definition if they provide one and direct any specific questions about whether a source fits that definition to your instructor. 

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  • How to identify the characteristics of empirical research quickly when reading an article.
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  • What is empirical research: Methods, types & examples

What is empirical research: Methods, types & examples

Defne Çobanoğlu

Having opinions on matters based on observation is okay sometimes. Same as having theories on the subject you want to solve. However, some theories need to be tested. Just like Robert Oppenheimer says, “Theory will take you only so far .” 

In that case, when you have your research question ready and you want to make sure it is correct, the next step would be experimentation. Because only then you can test your ideas and collect tangible information. Now, let us start with the empirical research definition:

  • What is empirical research?

Empirical research is a research type where the aim of the study is based on finding concrete and provable evidence . The researcher using this method to draw conclusions can use both quantitative and qualitative methods. Different than theoretical research, empirical research uses scientific experimentation and investigation. 

Using experimentation makes sense when you need to have tangible evidence to act on whatever you are planning to do. As the researcher, you can be a marketer who is planning on creating a new ad for the target audience, or you can be an educator who wants the best for the students. No matter how big or small, data gathered from the real world using this research helps break down the question at hand. 

  • When to use empirical research?

Empirical research methods are used when the researcher needs to gather data analysis on direct, observable, and measurable data. Research findings are a great way to make grounded ideas. Here are some situations when one may need to do empirical research:

1. When quantitative or qualitative data is needed

There are times when a researcher, marketer, or producer needs to gather data on specific research questions to make an informed decision. And the concrete data gathered in the research process gives a good starting point.

2. When you need to test a hypothesis

When you have a hypothesis on a subject, you can test the hypothesis through observation or experiment. Making a planned study is a great way to collect information and test whether or not your hypothesis is correct.

3. When you want to establish causality

Experimental research is a good way to explore whether or not there is any correlation between two variables. Researchers usually establish causality by changing a variable and observing if the independent variable changes accordingly.

  • Types of empirical research

The aim of empirical research is to collect information about a subject from the people by doing experimentation and other data collection methods. However, the methods and data collected are divided into two groups: one collects numerical data, and the other one collects opinion-like data. Let us see the difference between these two types:

Quantitative research

Quantitative research methods are used to collect data in a numerical way. Therefore, the results gathered by these methods will be numbers, statistics, charts, etc. The results can be used to quantify behaviors, opinions, and other variables. Quantitative research methods are surveys, questionnaires, and experimental research.

Qualitiative research

Qualitative research methods are not used to collect numerical answers, instead, they are used to collect the participants’ reasons, opinions, and other meaningful aspects. Qualitative research methods include case studies, observations, interviews, focus groups, and text analysis.

  • 5 steps to conduct empirical research

Necessary steps for empirical research

Necessary steps for empirical research

When you want to collect direct and concrete data on a subject, empirical research is a great way to go. And, just like every other project and research, it is best to have a clear structure in mind. This is even more important in studies that may take a long time, such as experiments that take years. Let us look at a clear plan on how to do empirical research:

1. Define the research question

The very first step of every study is to have the question you will explore ready. Because you do not want to change your mind in the middle of the study after investing and spending time on the experimentation.

2. Go through relevant literature

This is the step where you sit down and do a desk research where you gather relevant data and see if other researchers have tried to explore similar research questions. If so, you can see how well they were able to answer the question or what kind of difficulties they faced during the research process.

3. Decide on the methodology

Once you are done going through the relevant literature, you can decide on which method or methods you can use. The appropriate methods are observation, experimentation, surveys, interviews, focus groups, etc.

4. Do data analysis

When you get to this step, it means you have successfully gathered enough data to make a data analysis. Now, all you need to do is look at the data you collected and make an informed analysis.

5. Conclusion

This is the last step, where you are finished with the experimentation and data analysis process. Now, it is time to decide what to do with this information. You can publish a paper and make informed decisions about whatever your goal is.

  • Empirical research methodologies

Some essential methodologies to conduct empirical research

Some essential methodologies to conduct empirical research

The aim of this type of research is to explore brand-new evidence and facts. Therefore, the methods should be primary and gathered in real life, directly from the people. There is more than one method for this goal, and it is up to the researcher to use which one(s). Let us see the methods of empirical research: 

  • Observation

The method of observation is a great way to collect information on people without the effect of interference. The researcher can choose the appropriate area, time, or situation and observe the people and their interactions with one another. The researcher can be just an outside observer or can be a participant as an observer or a full participant.

  • Experimentation

The experimentation process can be done in the real world by intervening in some elements to unify the environment for all participants. This method can also be done in a laboratory environment. The experimentation process is good for being able to change the variables according to the aim of the study.

The case study method is done by making an in-depth analysis of already existing cases. When the parameters and variables are similar to the research question at hand, it is wise to go through what was researched before.

  • Focus groups

The case study method is done by using a group of individuals or multiple groups and using their opinions, characteristics, and responses. The scientists gather the data from this group and generalize it to the whole population.

Surveys are an effective way to gather data directly from people. It is a systematic approach to collecting information. If it is done in an online setting as an online survey , it would be even easier to reach out to people and ask their opinions in open-ended or close-ended questions.

Interviews are similar to surveys as you are using questions to collect information and opinions of the people. Unlike a survey, this process is done face-to-face, as a phone call, or as a video call.

  • Advantages of empirical research

Empirical research is effective for many reasons, and helps researchers from numerous fields. Here are some advantages of empirical research to have in mind for your next research:

  • Empirical research improves the internal validity of the study.
  • Empirical evidence gathered from the study is used to authenticate the research question.
  • Collecting provable evidence is important for the success of the study.
  • The researcher is able to make informed decisions based on the data collected using empirical research.
  • Disadvantages of empirical research

After learning about the positive aspects of empirical research, it is time to mention the negative aspects. Because this type may not be suitable for everyone and the researcher should be mindful of the disadvantages of empirical research. Here are the disadvantages of empirical research:

  • As it is similar to other research types, a case study where experimentation is included will be time-consuming no matter what. It has more steps and variables than concluding a secondary research.
  • There are a lot of variables that need to be controlled and considered. Therefore, it may be a challenging task to be mindful of all the details.
  • Doing evidence-based research can be expensive if you need to complete it on a large scale.
  • When you are conducting an experiment, you may need some waivers and permissions.
  • Frequently asked questions about empirical research

Empirical research is one of the many research types, and there may be some questions in mind about its similarities and differences to other research types.

Is empirical research qualitative or quantitative?

The data collected by empirical research can be qualitative, quantitative, or a mix of both. It is up to the aim of researcher to what kind of data is needed and searched for.

Is empirical research the same as quantitative research?

As quantitative research heavily relies on data collection methods of observation and experimentation, it is, in nature, an empirical study. Some professors may even use the terms interchangeably. However, that does not mean that empirical research is only a quantitative one.

What is the difference between theoretical and empirical research?

Empirical studies are based on data collection to prove theories or answer questions, and it is done by using methods such as observation and experimentation. Therefore, empirical research relies on finding evidence that backs up theories. On the other hand, theoretical research relies on theorizing on empirical research data and trying to make connections and correlations.

What is the difference between conceptual and empirical research?

Conceptual research is about thoughts and ideas and does not involve any kind of experimentation. Empirical research, on the other hand, works with provable data and hard evidence.

What is the difference between empirical vs applied research?

Some scientists may use these two terms interchangeably however, there is a difference between them. Applied research involves applying theories to solve real-life problems. On the other hand, empirical research involves the obtaining and analysis of data to test hypotheses and theories.

  • Final words

Empirical research is a good means when the goal of your study is to find concrete data to go with. You may need to do empirical research when you need to test a theory, establish causality, or need qualitative/quantitative data. For example, you are a scientist and want to know if certain colors have an effect on people’s moods, or you are a marketer and want to test your theory on ad places on websites. 

In both scenarios, you can collect information by using empirical research methods and make informed decisions afterward. These are just the two of empirical research examples. This research type can be applied to many areas of work life and social sciences. Lastly, for all your research needs, you can visit forms.app to use its many useful features and over 1000 form and survey templates!

Defne is a content writer at forms.app. She is also a translator specializing in literary translation. Defne loves reading, writing, and translating professionally and as a hobby. Her expertise lies in survey research, research methodologies, content writing, and translation.

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What is Empirical Research? Definition, Types, and More

Navigate data's complexities with empirical research, distinguishing truth from speculation. Explore types, methods, and more.

Godi Yeshaswi

January 12, 2024

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In this Article

Research is crucial in many fields, involving a systematic exploration to confirm facts or draw specific conclusions. Empirical research, widely applied in different areas, aims to validate new facts. Grasping the significance of empirical research and knowing how to carry it out can aid in making decisions backed by a thorough investigation. 

What Do You Mean by Empirical Research?

The empirical research method is a study based on observation and direct experience to understand phenomena and draw conclusions based on real-world observations.

Empirical Research Examples

Consider a scenario where a study aims to determine if people add a product to their online cart due to product ratings. To investigate this, an experiment is carried out using an online shopping attitude survey . One group of participants is exposed to ratings, while another group is not exposed to any product ratings. The researchers then observe the behavior of these groups. The findings from this research will provide concrete evidence on whether product ratings impact the decision to purchase.

Types of Methodologies for Empirical Research

Quantitative research.

Quantitative research collects numerical data to analyze specific behaviors, opinions, or defined variables . Here are some methods used in quantitative empirical research:

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This calls for collecting information from a group of people using a questionnaire. When conducting surveys, it's essential to pose straightforward, brief, and easy questions for participants to respond to. Survey participants can provide their answers through various channels, whether it be on paper, online through emails, or on social media. Administering surveys is generally a straightforward approach to obtaining information, whether from the general public or a specific audience.

Experimental Research

This process includes forming an idea and checking it through experimentation. Researchers can change one variable and see how it impacts other variables, helping them figure out if there's a clear connection. They can then examine the findings to confirm if their initial idea is correct.

Longitudinal Study

A longitudinal study involves observing a subject's characteristics or actions by testing them repeatedly over a period. The data collected from this method can be either qualitative or quantitative. For instance, marketers could track the buying patterns of a particular demographic, such as young adults, over several years. By repeatedly collecting data on their product design preferences, brand loyalty, and spending habits, researchers can gain insights into how these factors evolve over time. 

Cross-Sectional Research

Cross-sectional research is a way of studying people by looking at them during a particular time. In this method, researchers pick a group of individuals with similar characteristics, excluding the ones they are studying. This helps ensure that any findings are likely caused by the variable under investigation. For instance, researchers assess consumer preferences for different packaging designs at a specific time. Participants from the target market evaluate various options, providing immediate feedback. This approach offers a quick snapshot of consumer opinions on packaging, helping companies make informed decisions based on current preferences.

Correlational Research

Correlational research is a method used to find connections and prevalence among different factors. It often uses regression as a statistical tool to predict outcomes, showing whether there's a negative, neutral, or positive correlation between variables. For example, researchers might explore the relationship between how much time individuals spend watching television and their overall well-being. By collecting data on both variables from a diverse group of participants, the researchers can analyze whether there is a correlation between the time spent watching TV and factors like happiness or stress levels.

Qualitative Research

Qualitative research is useful for collecting information that isn't in numbers or can't be measured easily. It usually involves semi-structured or unstructured approaches, letting researchers uncover personal meanings, reasons, and opinions from participants. Qualitative empirical research often involves a small group of people and conversational methods to get detailed information and deeper insights into a problem. Examples of methods used in qualitative research include:

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Observational Method

It involves watching and collecting descriptive information about a subject. The observational method gives researchers personal insights, helping them form detailed opinions about their studies. It's commonly used in ethnographic research, which looks at the culture of different groups of people.

One-on-One Interview

This is an entirely qualitative method that includes directly talking to a subject. Researchers often use it to get accurate and meaningful information about a subject. It's a conversational approach where specific questions are asked to guide the discussion. 

Focus Group

Focus groups are employed when researchers seek answers to questions of why, what, and how. A small group is typically chosen, and in-person interaction may not be necessary. If an in-person discussion is involved, a moderator is usually required. This method is commonly utilized by product companies to gather information about their brands and products.

For instance, in media/ad testing with focus groups, a company may evaluate a new soft drink advertisement. A small group views different ad versions and discusses their impressions, preferences, and memorable elements. This feedback helps the company refine its advertising strategy before a wider campaign launch.

Text Analysis

This qualitative empirical research method enables the analysis of an individual's social life . It's a contemporary approach leveraging the growing importance of social media and technology. Researchers can examine the specific words and images an individual uses to draw meaningful conclusions.

How to Conduct Empirical Research?

Empirical research relies on observation and experiences, so planning and analysis are crucial. Let’s take an example of media/ad/shopper testing as the research base to understand the steps to conduct empirical research - 

Step 1: Define the Research Objective

Clearly outline the study's goal, such as evaluating the effectiveness of a new packaging design for a consumer product or an advertisement of a new series. Consider potential issues with the resources schedule and ensure the study's benefits justify the costs.

Step 2: Review Relevant Literature and Theories

Identify theories or previous studies on consumer responses to packaging changes or new series ad releases. Understand how these insights can inform the study's outcomes.

Step 3: Formulate Hypothesis and Measurements

Develop an initial hypothesis, considering variables like consumer perception, brand appeal, and market competitiveness. Define units of measurement, such as consumer preferences and purchasing behavior, ensuring they align with industry standards.

Step 4: Define Research Design, Methodology, and Data Collection Techniques

Choose an appropriate research approach, whether qualitative research or quantitative research , to assess consumer reactions to the new packaging. Consider using focus groups and one-on-one interviews for in-depth insights and gather data on consumer reactions.

Step #5: Conduct Data Analysis and Frame the Results

Analyze the collected data, considering both quantitative metrics and qualitative feedback from focus groups and interviews. Assess whether the new packaging positively influences consumer perceptions and purchasing decisions. 

Evaluate consumer research tools powered by Insights AI that are powered by AI to give you unbiased feedback considering the emotions and behaviour of the respondent. 

Step 6: Draw Conclusions

Prepare a comprehensive report presenting the findings, including the impact of the new packaging or advertisement on consumer behavior. If sharing the results widely, convert the report into an article for publication and recommend further research areas in the packaging and media testing domain. Use a plagiarism checker to ensure the originality and credibility of the research.

You can also utilize the Gen AI feature in Decode to draw conclusions from your studies by just asking the Decode co-pilot, a virtual assistant. 

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Empirical Research Cycle

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Observation

A media researcher observes audience reactions to a new television show by monitoring social media comments, ratings, and viewership numbers. This initial data collection serves as the basis for forming hypotheses about the show's popularity.

Based on the observations, the researcher may induce a hypothesis that suggests the show's popularity is linked to its engaging storyline and relatable characters. This assumption is then examined and tested against the collected data.

Using deductive reasoning, the researcher concludes that if the show's popularity is consistently associated with positive audience engagement and high ratings, it can be inferred that engaging content is a significant factor.

To test the hypothesis, the researcher designs a survey asking viewers about their reasons for liking the show and analyzes the responses. Statistical methods are employed to determine if there's a significant correlation between positive viewer feedback and the show's popularity.

In the final stage, the researcher evaluates the survey results, considering the empirical data, viewer comments, and any challenges encountered during the research. The findings are used to draw conclusions about the factors contributing to the show's success, and this information becomes the basis for further media testing or content development.

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Advantages and Disadvantages of Empirical Research

Advantages of empirical research.

Empirical research is widely used for several reasons, and here are some of its advantages:

  • Authentication of Traditional Research: It validates traditional research through experiments and observations.
  • Enhanced Competence and Authenticity: This methodology enhances the competency and authenticity of the conducted research.
  • Adaptability to Dynamic Changes: Researchers can understand and adapt to dynamic changes by utilizing empirical research and adjusting their strategies accordingly.
  • High Control Level: Empirical research offers a high level of control, allowing researchers to manage multiple variables.
  • Increased Internal Validity: It plays a crucial role in boosting internal validity, ensuring the accuracy of the research outcomes.

Disadvantages of Empirical Research

While empirical research brings competency and authenticity, it also has some drawbacks:

  • Time-Consuming Nature: Collecting data from various sources and dealing with numerous parameters can make this research time-consuming requiring patience.
  • Costly Endeavor: Conducting research in different locations or environments may lead to increased expenses.
  • Permission Challenges: Obtaining consent for certain experimental methods can be difficult, as there are strict rules governing their execution.
  • Data Collection Challenges: Collecting data from various sources through different methods can be problematic at times.

Bottom Line

In a world full of data, empirical research is crucial for finding out what's true. It involves carefully observing and experiencing things to draw conclusions based on real-world evidence. This type of research uses both numbers (quantitative) and descriptions (qualitative) to understand various topics.

To conduct empirical research, you need a step-by-step plan. This includes setting clear goals, looking at existing research, making educated guesses (hypotheses), picking the right methods, analyzing data, and reaching sensible conclusions.

The research cycle involves watching, making guesses, drawing logical conclusions, testing those guesses, and finally evaluating everything.

While empirical research has benefits like proving traditional research, increasing competence, and adapting to changes, it also has challenges like being time-consuming, expensive, and dealing with permission and data collection issues.

In summary, understanding and using empirical research helps us make informed decisions in different fields by carefully studying and validating information through a systematic process.

Frequently Asked Questions

What do you mean by empirical research.

Empirical research is a type of study that relies on observing and measuring real-life phenomena as directly witnessed by the researcher. The collected data can be analyzed in relation to a theory or hypothesis, but the conclusions are grounded in actual experiences.

Theoretical vs Empirical Research

Empirical refers to information derived from observations or personal experiences, while theoretical is associated with ideas and hypotheses. In research contexts, these terms are commonly used to describe data, methods, or probabilities.

What are the benefits of Empirical Research?

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Empirical research strives to understand the significance of a specific phenomenon. In simpler terms, it seeks to uncover how and why something operates the way it does. By pinpointing the reasons behind occurrences, it becomes feasible to reproduce or avoid similar events.

Is Empirical quantitative or qualitative?

Empirical research is often thought of as the same as quantitative research, but to be precise, it's any research that relies on direct observation.

Empirical Method Psychology Example

Suppose a researcher aims to investigate the impact of listening to happy music on promoting prosocial behavior. In this scenario, an empirical analysis could involve conducting an experiment where one group of participants is exposed to happy music while another group is not exposed to any music at all.

Yeshaswi is a dedicated and enthusiastic individual with a strong affinity for tech and all things content. When he's not at work, he channels his passion into his love for football, especially for F.C. Barcelona and the GOAT, Lionel Messi. Instead of hitting the town for parties, he prefers to spend quality time cuddling with his Golden Retriever, Oreo.

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Empirical research  is based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief. 

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology." Ask yourself: Could I recreate this study and test these results?

Key characteristics to look for:

  • Specific research questions  to be answered
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  • Description of the  process  used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys)

Another hint: some scholarly journals use a specific layout, called the "IMRaD" format, to communicate empirical research findings. Such articles typically have 4 components:

  • Introduction : sometimes called "literature review" -- what is currently known about the topic -- usually includes a theoretical framework and/or discussion of previous studies
  • Methodology:  sometimes called "research design" -- how to recreate the study -- usually describes the population, research process, and analytical tools
  • Results : sometimes called "findings"  --  what was learned through the study -- usually appears as statistical data or as substantial quotations from research participants
  • Discussion : sometimes called "conclusion" or "implications" -- why the study is important -- usually describes how the research results influence professional practices or future studies

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Empirical research is based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief. 

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology."  Ask yourself: Could I recreate this study and test these results?

Key characteristics to look for:

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  • Description of the process used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys)

Another hint: some scholarly journals use a specific layout, called the "IMRaD" format, to communicate empirical research findings. Such articles typically have 4 components:

  • Introduction : sometimes called "literature review" -- what is currently known about the topic -- usually includes a theoretical framework and/or discussion of previous studies
  • Methodology: sometimes called "research design" -- how to recreate the study -- usually describes the population, research process, and analytical tools
  • Results : sometimes called "findings" -- what was learned through the study -- usually appears as statistical data or as substantial quotations from research participants
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New perspectives on curriculum and democracy: conceptual and empirical tools for democratic curriculum

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There is an increasingly complex array of global crises facing young people in contemporary societies, including climate change and ecological collapse, increasing inequality, rising authoritarianism and the de-democratisation and privatisation of public institutions. As such, it is imperative to consider the ways in which curriculum can move beyond questions regarding the knowledge, skills and attitudes being taught in classrooms, to broader questions of how curriculum can work towards more democratic futures for all young people. Part I of the two-part special issue on new perspectives on curriculum and democracy addresses this challenge through papers that provide a range of innovative theoretical, conceptual and empirical responses to the question of how curriculum can be for democracy in a context of de-democratisation. In doing so, the papers promote innovative approaches to curriculum thinking, multiple ways of knowing and understanding, and encourage critical and creative curriculum research and scholarship in the pursuit of more equitable, democratic and socially just futures.

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In the opening chapter of Re-imagining Education for Democracy (Riddle & Apple, 2019a ), we claimed that contemporary liberal democracy was:

Rapidly being replaced by hyper-evangelical, neo-conservative and populist movements that are built on platforms of hate, segregation and fear of the Other. All over the world, there is a tilt to fascist, racist and misogynist forms of tyranny and oppression. This is to say nothing of the collapsing environmental ecosystems on which our very existence depends. We are living in dangerous times. (Riddle & Apple, 2019a , p. 1)

The five years since we published those words have seen an acceleration of the effects of global de-democratisation, alongside rapidly intensifying economic inequality, civil unrest, fear and social division. Each time a new climate report is published, the evidence alarmingly confirms a simple, yet confronting truth: we have entered a period of climate catastrophe. These complex set of social, economic, political and environmental crises have coalesced to form a set of urgent, undeniable challenges, which will confront the young people who are currently in schools and other education contexts in the years to come (Riddle, 2022 ). However, this is not the time to lose hope. Indeed, I am convinced that schooling, through its curriculum and pedagogical structures, has a critical role to play in helping young people to become critical and creative agents of democratic change, who will be able to collectively and sustainably respond to these existential challenges (Aly et al., 2022 ; Apple et al., 2022 ; Riddle, 2022 ; Riddle et al., 2022 ).

Curriculum is at the very heart of education, yet is often given scant attention by education policymakers, systems and leaders within contemporary data-driven and highly marketised education contexts across the globe. The emphasis is instead given to assessment, with a particularly narrow view of what constitutes assessment practices (i.e., standardised and reductive forms of literacy and numeracy skills and knowledge), which feeds into the broader neoliberal narratives of privatisation, choice, competition and consumption in the educational marketplace (Apple, 2004 , 2006 ; Morley et al., 2014 ; Verger et al., 2016 ; Windle, 2014 ).

At the turn of the century, Reid and Thomson ( 2003 ) argued that ‘one of the primary purposes of schools is to develop citizens for democracy and thus to make democratic publics. This is a pre-eminent public purpose of education in a democracy, irrespective of the ways in which that democracy organizes its educational provision or on what scale that democracy operates’ (p. xiv). This is an important consideration, which moves beyond debates about school choice and public versus private schooling, to get to the democratic impulse of curriculum-making in schools and other education contexts. As Pinar ( 2012 ) argued, considerations of curriculum need to be framed by questions of the kind of future we want for young people and the challenges they will face. The struggle for socially just education must include curriculum that is built upon principles of justice and democratic agency as a central tenet (Connell, 1993 , 2012 ; Mills et al., 2022 ; Riddle et al., 2023 ).

We have long known that ‘school curriculum, like other aspects of social life, is formed and shaped ideologically. Thus, the dominant forms of school curriculum reflect the dominant ideological forms in society’ (Kemmis, 1986 , p. 103). In other words, the politics and ethics of curriculum cannot be separated from the conditions under which it is created and experienced. The hopes and fears of teachers, students and the communities within which they live are absolutely imbricated with curriculum. However, the ‘tangled relationship between curriculum and democracy means that curriculum cannot be understood in isolation from the political, economic, social and cultural conditions in which it is produced and practised’ (Reid & Thomson, 2003 , p. xiv). The papers in this first part of the special issue on new perspectives on curriculum and democracy provide rich theorisations of how curriculum can nurture democratic participation and students’ civic agency, while also paying careful attention to the complex political, economic, social and cultural contexts within which schools and other sites of education exist.

It is clear that we need new conceptual and empirical tools for curriculum, which bring theory and practice together in ways that support the democratic possibilities of curriculum-making in schools and other sites of education. Further, it is imperative to consider the ways in which curriculum can move beyond questions regarding the knowledge, skills and attitudes being taught in classrooms, to broader questions of how curriculum can work towards more democratic futures for all young people.

This special issue on new perspectives on curriculum and democracy addresses this challenge through papers that provide a range of innovative theoretical, conceptual and empirical responses to the question of how curriculum can be for democracy in a context of de-democratisation. In doing so, the papers promote innovative approaches to curriculum thinking, multiple ways of knowing and understanding, and encourage critical and creative curriculum research and scholarship in the pursuit of more equitable, democratic and socially just futures.

Overview of papers in part I

This first part of the special issue contains 12 papers, which provide a range of new conceptual and empirical approaches to curriculum infused with a democratic ethos and commitment to civic virtue and the public good. While each paper presents a unique perspective—which can be read as a stand-alone contribution to the curriculum literature—when taken together, point to some generative ways of rethinking the possibilities of more democratic modalities of curriculum-making.

The opening contribution is a rich dialogue generated by members of the Pedagogies for Social Justice Research Group at the University of South Australia, including Katie Maher, Lester-Irabinna Rigney, Mikayla King, Robyne Garrett, Joel Windle, Nadeem Memon, Alison Wrench, Jenni Carter, Kathryn Paige, Lisa O’Keeffe, Margaret Lovell, Samantha Schulz, Hannah Soong, Jill Colton, Sarah McDonald and Robert Hattam. They consider the interplay between curriculum, pedagogy and democracy through several lenses, including rights-based approaches, religious identities in post-secular schools, culturally responsive curriculum, racial literacy and gender equity. In doing so, the authors provide a generative set of considerations for more democratic modes of curriculum and pedagogy for contemporary schooling, which traverse the conceptual and empirical.

R. S. Webster’s paper examines our moment of ‘post-democracy’ through the democratic theorisations of Mouffe, Rancière, Crouch and Dewey. In doing so, Webster provides a set of conceptual approaches to curriculum as being agonistic and built from dissensus, rather than the assumptions of consensus democracy. Further, by drawing on Deweyean principles of experiential education, Webster is able to generate provocative lines of thought for a more confrontational curriculum, which works to counter the de-democratisation of contemporary late capitalist neoliberal societies.

Drawing on Lefebvre’s ( 1991 ) notion of the ‘production of space’, Tanya Davies considers the tensions between education policy agendas that espouse social justice virtues, which adhering to neoliberal forms of compliance and conformity, standardisation, accountability and performativity. Davies establishes a clear set of tensions that teachers face when engaging in the practical and ethical work of curriculum-making, and considers the ways in which conceived, perceived and lived spatial accounts of curriculum can work as countermeasures against the performative compliance and conformity of contemporary schooling systems.

In their paper, Rebecca English, Chris Krogh and Giuliana Liberto focus on the ways in which young people’s democratic engagement and agency is expressed in the unschooling movement. They suggest that ‘unschooling is a philosophy of life, more than of schooling, because it posits that education cannot be separated from life’. English and colleagues argue that the biggest threat to the democratic curriculum experiences of unschooling students come from regulatory overreach and control by governments. To have a truly democratic curriculum requires less, not more, intervention by regulators and education systems.

Elsa Estrela and Louise Lima consider the potential of a more viscous curriculum, which emerges from narrative learning that nurtures and extends communication and educational inclusivity. Their paper explores various curriculum paradigms to demonstrate how embracing the viscosity of curriculum-making might better support the collaborative generation of knowledge, which is connected to the cultural and social worlds of students, and which generates and promotes more democratic modes of engagement.

With a focus on the authoritarian education policies within the Polish context, Joanna Leek and Boguslaw Sliwerski examine how the International Baccalaureate curriculum provides the opportunity to have more autonomy, professional collaboration and development of skills and knowledge that promote resilience and resistance for students and teachers. There are important considerations for the future of democratic education, given the rising influence of authoritarianism across many parts of the world, in which education becomes more centrally controlled, autonomy and academic freedom curtailed, suppression of dissent and alternative perspectives, and direct political interference in curriculum.

Keith Heggart, Naomi Barnes, Steven Kolber, Tom Mahoney and Cameron Malcher use the officially mandated Australian Curriculum, with an emphasis on history and civics and citizenship education, as a site of inquiry to determine the influence of third-party actors on curriculum development. They argue that, rather than democratic modes of community engagement and participation by educators, students and communities, curriculum-making is affected by ideology borrowing, laundering and acquisition activities undertaken by political actors, mediated through social media campaigns. In doing so, curriculum becomes less about what is taught in schools and more as a social and cultural weapon used to further particular policy and political aims.

In their paper, Saba Hussain, Jorge Knijnik and Rohini Balram extend the notion of curriculum wars and the influence of social media to consider the ways in which young people’s values and actions have been shaped through different modes of political education, including online radicalisation regarding race, religion and gender. They argue that schools need to respond to the challenges of the curriculum wars by ensuing that curriculum-making with students is collaborative, activist and built through action research design. In doing so, young people become curriculum-makers and knowledge workers in partnership with teachers and schools, rather than passive recipients of curriculum reform.

Katrina Thorpe, Linda ten Kate and Cathie Burgess provide a rich conceptual framing of Learning from Country, in which Aboriginal knowledges and Country disrupt the Eurocentric, settler–colonial, monocultural curriculum-making practices of contemporary schooling in Australia. They provide empirical accounts of how teachers and teacher educators can learn from Country and Aboriginal community-based educators how to engage in participatory democratic approaches through curriculum that engages with localised, relational and contextual elements of diverse communities. In doing so, Thorpe and colleagues bring together Learning from Country with democratic education as a means to activate a decolonising agenda for education that is ethical and culturally respectful.

In his paper, Steven Kolber brings together the philosophic traditions of the Socratic method with contemporary video-based social media platforms, such as TikTok and YouTube, to consider some of the ways in which these might combine to produce different experiences and democratic modalities of student engagement, participation and agency in curriculum. Kolber brings together conceptual and practical considerations that traverse assistive technologies, generative artificial intelligence and flipped learning as sites for potential curriculum and democratic disruption and transformation.

David Nally’s paper examines the emergence of post-truth as a catch-all for various factors of cultural, social and political disruption, and considers the implications for schooling that promotes civic participation and fosters an inclusive society. Nally suggests that Deep Collaboration (Martin et al., 2020 ) is one productive model of democratic education, which could counter the effects of a post-truth world through the use of constructive dialogue and collective commitment to building the cultural capital of communities.

Finally, Lew Zipin’s paper conceptually channels Antonio Gramsci to diagnose the perils of populist curriculum, which generate ideological messages in support of the interests of those in power, designed to create and sustain cultural hegemony. In response, Zipin argues that school curriculum should activate young people’s agency and knowledge through working on ‘problems that matter’, and which proactively and collaboratively engage in building more sustainable and socially just futures.

The papers in this first of the two-part special issue on new perspectives on curriculum and democracy provide a richly diverse set of conceptual and empirical tools for rethinking curriculum-making and the role of curriculum in democratic education. Taken collectively, these papers generate rich ideas for curriculum and democracy in the twenty-first century, emphasising the need for young people to be given opportunities to critically engage in active democratic participation, cultivating civic values of belonging, collaboration and commitment to the collective good, and to resist and reclaim curriculum that oppresses, promotes monocultural and colonialist knowledges, and which contributes to the ongoing crises of de-democratisation, growing inequality and ecological systems collapse.

There are generative ways forward proposed by the authors of these papers, including ways in which we might reconsider the interplay of social and cultural identities within democratic modalities of education, the affordances of dissensus and agonism, the spatiality of social justice, the dangers of overregulation, inclusive and collaborative knowledge generation, resisting authoritarian forms of control and compliance, understanding the ways in which old and new ideas and technologies might productively work together, engaging in collaborative acts of civic participation and community building, and working together on problems that really matter.

Forty years ago, Ashenden et al. ( 1984 ) in their Manifesto for a Democratic Curriculum , argued that curriculum needs to be common and publicly available, based on cooperation rather than competition, relevant to the lives of students, developed in a coherent and systematic fashion, while also engaging with issues of reflective practice, moral and ethical judgement, practicality and applicability, and to be accessible and inclusive for all. While the world has become more complex and challenging over the intervening years, the basic premise and promise of a more democratic curriculum remains: that is, providing young people with the tools needed to build a future that is more sustainable, inclusive and socially just. The papers in this first part of the special issue point the way towards such a future through radically reframing curriculum and democracy at the heart of education.

Aly, A., Blackmore, J., Bright, D., Hayes, D., Heffernan, A., Lingard, B., Riddle, S., & Takayama, K. (2022). Reflections on how education can be for democracy in the twenty-first century. Journal of Educational Administration and History , 54 (3), 357–372. https://doi.org/10.1080/00220620.2022.2084052 .

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Riddle, S. New perspectives on curriculum and democracy: conceptual and empirical tools for democratic curriculum. Curric Perspect (2024). https://doi.org/10.1007/s41297-024-00256-9

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Empirical assessment of the assumptions of ComBat with diffusion tensor imaging

landmaba

Jun 20, 2024, 5:40 PM

Michael E. Kim, Chenyu Gao, Leon Y. Cai, Qi Yang, Nancy R. Newlin, Karthik Ramadass, Angela Jefferson, Derek Archer, Niranjana Shashikumar, Kimberly R. Pechman, Katherine A. Gifford, Timothy J. Hohman, Lori L. Beason-Held, Susan M. Resnick, Stefan Winzeck, Kurt G. Schilling, Panpan Zhang, Daniel Moyer, and Bennett A. Landman. “ Empirical Assessment of the Assumptions of ComBat with Diffusion Tensor Imaging .” Journal of Medical Imaging (Bellingham), vol. 11, no. 2, 024011, March 2024. doi:10.1117/1.JMI.11.2.024011.

Diffusion tensor imaging (DTI) is a magnetic resonance imaging technique that provides unique insights into white matter microstructure in the brain. However, it is susceptible to confounding effects introduced by scanner or acquisition differences. ComBat is a leading approach for addressing these site biases. Despite its frequent use for harmonization, ComBat’s robustness towards site dissimilarities and overall cohort size has not yet been evaluated in the context of DTI.

To address this, we matched 358 participants from two sites to create a “silver standard” cohort for multi-site harmonization. We harmonized mean fractional anisotropy (FA) and mean diffusivity (MD) calculated from participant DTI data for regions of interest defined by the JHU EVE-Type III atlas. To quantify the reliability of ComBat, we performed bootstrapping over 10 iterations at 19 levels of total sample size, 10 levels of sample size imbalance between sites, and 6 levels of mean age difference between sites. We measured three key metrics: (i) β_AGE, the linear regression coefficient of the relationship between FA and age; (ii) γ _sf, the ComBat-estimated site-shift; and (iii) δ _sf, the ComBat-estimated site-scaling. We evaluated the reliability of ComBat by calculating the root mean squared error (RMSE) in these metrics and examined the correlation between the reliability of ComBat and the violation of model assumptions.

Our results indicate that ComBat performs reliably for β_AGE when the total sample size is greater than 162 and the mean age difference between sites is less than 4 years. The assumptions of the ComBat model regarding the normality of residual distributions are not violated as the model becomes unstable.

In conclusion, before harmonizing DTI data with ComBat, it is crucial to examine the input cohort for size and covariate distributions at each site. Direct assessment of residual distributions is less informative on stability than bootstrap analysis. We advise caution when using ComBat in situations that do not conform to the identified thresholds.

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Title: an empirical study of mamba-based language models.

Abstract: Selective state-space models (SSMs) like Mamba overcome some of the shortcomings of Transformers, such as quadratic computational complexity with sequence length and large inference-time memory requirements from the key-value cache. Moreover, recent studies have shown that SSMs can match or exceed the language modeling capabilities of Transformers, making them an attractive alternative. In a controlled setting (e.g., same data), however, studies so far have only presented small scale experiments comparing SSMs to Transformers. To understand the strengths and weaknesses of these architectures at larger scales, we present a direct comparison between 8B-parameter Mamba, Mamba-2, and Transformer models trained on the same datasets of up to 3.5T tokens. We also compare these models to a hybrid architecture consisting of 43% Mamba-2, 7% attention, and 50% MLP layers (Mamba-2-Hybrid). Using a diverse set of tasks, we answer the question of whether Mamba models can match Transformers at larger training budgets. Our results show that while pure SSMs match or exceed Transformers on many tasks, they lag behind Transformers on tasks which require strong copying or in-context learning abilities (e.g., 5-shot MMLU, Phonebook) or long-context reasoning. In contrast, we find that the 8B Mamba-2-Hybrid exceeds the 8B Transformer on all 12 standard tasks we evaluated (+2.65 points on average) and is predicted to be up to 8x faster when generating tokens at inference time. To validate long-context capabilities, we provide additional experiments evaluating variants of the Mamba-2-Hybrid and Transformer extended to support 16K, 32K, and 128K sequences. On an additional 23 long-context tasks, the hybrid model continues to closely match or exceed the Transformer on average. To enable further study, we release the checkpoints as well as the code used to train our models as part of NVIDIA's Megatron-LM project.
Subjects: Machine Learning (cs.LG); Computation and Language (cs.CL)
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