how do you validate a research instrument

How to validate a research instrument/definition/importance

The  validation of a research instrument  refers to the process of assessing the survey questions to ensure reliability. How to validate a research instrument?

Because there are multiple hard-to-control factors that can influence the reliability of a question, this process is not a quick or easy task.

6 steps to validate a research instrument

Here are six steps for you to effectively validate a research instrument.

Step 1: Perform an Instrument Test

The first of the steps to validate a research instrument is divided into two parts. The first is to offer a survey to a group familiar with the research topic to assess whether the questions successfully capture it.

The second review should come from someone who is an expert in question construction, ensuring that your survey does not contain common mistakes, such as confusing or ambiguous questions .

Step 2: Run a pilot test

Another step in validating a research instrument is to select a subset of the survey participants and run a pilot survey . The suggested sample size varies, although around 10 percent of your total population is a solid number of participants . The more participants you can gather the better, although even a smaller sample can help you eliminate irrelevant questions . How to validate a research instrument?

Step 3: Clean the collected data

After going through the data collection process , you can export the raw data for curation. This greatly reduces the risk of error. Once they are entered, the next step is to reverse the code for the negatively asked questions .

If respondents have responded carefully, their responses to questions that were expressed negatively should be consistent with their responses to similar questions that were expressed positively. If that’s not the case, you can think about deleting that poll.

Also check the minimum and maximum values ​​for your general data set. For example, if you used a five-point scale and you see an answer that indicates the number six, you may have a data entry error.

Fortunately, there are software such as QuestionPro that have tools for quality control of survey data .

Step 4: Perform a Component Analysis

Another step to validate a research instrument is to perform a component analysis .

The goal of this stage is to determine what the items represent by looking for trends in the questions . You can combine the questions that are loaded into the same items by comparing them during their final analysis. How to validate a research instrument?

The number of item themes you can identify indicates the number of items your survey is measuring.

Step 5: Check the consistency of the questions

The next step in validating a research instrument is to check the consistency of the questions that are loaded in the same items.

Checking the correlation between the questions measures the reliability of the questions by ensuring that the survey responses are consistent.

Step 6: Review your survey

The last of the steps to validate a research instrument is the final review of the survey based on the information obtained from the data analysis . How to validate a research instrument?

If you come across a question that doesn’t relate to your survey items, you should delete it. If it is important, you can keep it and analyze it separately.

If only minor changes were made to the survey, you are likely ready to apply it after the final reviews. But if the changes are significant, another pilot survey and evaluation process will probably be needed.

Importance of validating a research instrument

Taking these steps to validate a research instrument is essential to ensure that the survey is truly reliable.

It is important to remember that you must include your instrument’s validation methods when submitting your research results report . =

Taking these steps to validate a research instrument not only strengthens its reliability, but also adds a title of quality and professionalism to your final product.

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• What is experimental research design/When to conduct/types September 24, 2023

Uncomplicated Reviews of Educational Research Methods

• Instrument, Validity, Reliability

.pdf version of this page

Part I: The Instrument

Instrument is the general term that researchers use for a measurement device (survey, test, questionnaire, etc.). To help distinguish between instrument and instrumentation, consider that the instrument is the device and instrumentation is the course of action (the process of developing, testing, and using the device).

Instruments fall into two broad categories, researcher-completed and subject-completed, distinguished by those instruments that researchers administer versus those that are completed by participants. Researchers chose which type of instrument, or instruments, to use based on the research question. Examples are listed below:

Usability refers to the ease with which an instrument can be administered, interpreted by the participant, and scored/interpreted by the researcher. Example usability problems include:

• Students are asked to rate a lesson immediately after class, but there are only a few minutes before the next class begins (problem with administration).
• Students are asked to keep self-checklists of their after school activities, but the directions are complicated and the item descriptions confusing (problem with interpretation).
• Teachers are asked about their attitudes regarding school policy, but some questions are worded poorly which results in low completion rates (problem with scoring/interpretation).

Validity and reliability concerns (discussed below) will help alleviate usability issues. For now, we can identify five usability considerations:

• How long will it take to administer?
• Are the directions clear?
• How easy is it to score?
• Do equivalent forms exist?
• Have any problems been reported by others who used it?

It is best to use an existing instrument, one that has been developed and tested numerous times, such as can be found in the Mental Measurements Yearbook . We will turn to why next.

Part II: Validity

Validity is the extent to which an instrument measures what it is supposed to measure and performs as it is designed to perform. It is rare, if nearly impossible, that an instrument be 100% valid, so validity is generally measured in degrees. As a process, validation involves collecting and analyzing data to assess the accuracy of an instrument. There are numerous statistical tests and measures to assess the validity of quantitative instruments, which generally involves pilot testing. The remainder of this discussion focuses on external validity and content validity.

External validity is the extent to which the results of a study can be generalized from a sample to a population. Establishing eternal validity for an instrument, then, follows directly from sampling. Recall that a sample should be an accurate representation of a population, because the total population may not be available. An instrument that is externally valid helps obtain population generalizability, or the degree to which a sample represents the population.

Content validity refers to the appropriateness of the content of an instrument. In other words, do the measures (questions, observation logs, etc.) accurately assess what you want to know? This is particularly important with achievement tests. Consider that a test developer wants to maximize the validity of a unit test for 7th grade mathematics. This would involve taking representative questions from each of the sections of the unit and evaluating them against the desired outcomes.

Part III: Reliability

Reliability can be thought of as consistency. Does the instrument consistently measure what it is intended to measure? It is not possible to calculate reliability; however, there are four general estimators that you may encounter in reading research:

• Inter-Rater/Observer Reliability : The degree to which different raters/observers give consistent answers or estimates.
• Test-Retest Reliability : The consistency of a measure evaluated over time.
• Parallel-Forms Reliability: The reliability of two tests constructed the same way, from the same content.
• Internal Consistency Reliability: The consistency of results across items, often measured with Cronbach’s Alpha.

Relating Reliability and Validity

Reliability is directly related to the validity of the measure. There are several important principles. First, a test can be considered reliable, but not valid. Consider the SAT, used as a predictor of success in college. It is a reliable test (high scores relate to high GPA), though only a moderately valid indicator of success (due to the lack of structured environment – class attendance, parent-regulated study, and sleeping habits – each holistically related to success).

Second, validity is more important than reliability. Using the above example, college admissions may consider the SAT a reliable test, but not necessarily a valid measure of other quantities colleges seek, such as leadership capability, altruism, and civic involvement. The combination of these aspects, alongside the SAT, is a more valid measure of the applicant’s potential for graduation, later social involvement, and generosity (alumni giving) toward the alma mater.

Finally, the most useful instrument is both valid and reliable. Proponents of the SAT argue that it is both. It is a moderately reliable predictor of future success and a moderately valid measure of a student’s knowledge in Mathematics, Critical Reading, and Writing.

Part IV: Validity and Reliability in Qualitative Research

Thus far, we have discussed Instrumentation as related to mostly quantitative measurement. Establishing validity and reliability in qualitative research can be less precise, though participant/member checks, peer evaluation (another researcher checks the researcher’s inferences based on the instrument ( Denzin & Lincoln, 2005 ), and multiple methods (keyword: triangulation ), are convincingly used. Some qualitative researchers reject the concept of validity due to the constructivist viewpoint that reality is unique to the individual, and cannot be generalized. These researchers argue for a different standard for judging research quality. For a more complete discussion of trustworthiness, see Lincoln and Guba’s (1985) chapter .

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About Research Rundowns

Research Rundowns was made possible by support from the Dewar College of Education at Valdosta State University .

• Experimental Design
• What is Educational Research?
• Writing Research Questions
• Mixed Methods Research Designs
• Qualitative Coding & Analysis
• Qualitative Research Design
• Correlation
• Effect Size
• Mean & Standard Deviation
• Significance Testing (t-tests)
• Steps 1-4: Finding Research
• Steps 5-6: Analyzing & Organizing
• Steps 7-9: Citing & Writing
• Writing a Research Report

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