Reliability and Validity (2024)

Reliability and Validity (1)

EXPLORING RELIABILITY IN ACADEMIC ASSESSMENT

Written by Colin Phelan and Julie Wren, Graduate Assistants, UNI Office of Academic Assessment (2005-06)

Reliability is the degree to which an assessment tool produces stable and consistent results.

Types of Reliability

  1. Test-retest reliability is a measure of reliability obtained by administering the same test twice over a period of time to a group of individuals. The scores from Time 1 and Time 2 can then be correlated in order to evaluate the test for stability over time.

Example:A test designed to assess student learning in psychology could be given to a group of students twice, with the second administration perhaps coming a week after the first. The obtained correlation coefficient would indicate the stability of the scores.

  1. Parallel forms reliability is a measure of reliability obtained by administering different versions of an assessment tool (both versions must contain items that probe the same construct, skill, knowledge base, etc.) to the same group of individuals. The scores from the two versions can then be correlated in order to evaluate the consistency of results across alternate versions.

Example:If you wanted to evaluate the reliability of a critical thinking assessment, you might create a large set of items that all pertain to critical thinking and then randomly split the questions up into two sets, which would represent the parallel forms.

  1. Inter-rater reliability is a measure of reliability used to assess the degree to which different judges or raters agree in their assessment decisions. Inter-rater reliability is useful because human observers will not necessarily interpret answers the same way; raters may disagree as to how well certain responses or material demonstrate knowledge of the construct or skill being assessed.

Example:Inter-rater reliability might be employed when different judges are evaluating the degree to which art portfolios meet certain standards. Inter-rater reliability is especially useful when judgments can be considered relatively subjective. Thus, the use of this type of reliability would probably be more likely when evaluating artwork as opposed to math problems.

  1. Internal consistency reliability is a measure of reliability used to evaluate the degree to which different test items that probe the same construct produce similar results.
    1. Average inter-item correlation is a subtype of internal consistency reliability. It is obtained by taking all of the items on a test that probe the same construct (e.g., reading comprehension), determining the correlation coefficient for each pair of items, and finally taking the average of all of these correlation coefficients. This final step yields the average inter-item correlation.
    1. Split-half reliability is another subtype of internal consistency reliability. The process of obtaining split-half reliability is begun by “splitting in half” all items of a test that are intended to probe the same area of knowledge (e.g., World War II) in order to form two “sets” of items. The entire test is administered to a group of individuals, the total score for each “set” is computed, and finally the split-half reliability is obtained by determining the correlation between the two total “set” scores.

Validity refers to how well a test measures what it is purported to measure.

Why is it necessary?

While reliability is necessary, it alone is not sufficient. For a test to be reliable, it also needs to be valid. For example, if your scale is off by 5 lbs, it reads your weight every day with an excess of 5lbs. The scale is reliable because it consistently reports the same weight every day, but it is not valid because it adds 5lbs to your true weight. It is not a valid measure of your weight.

Types of Validity

Example: If a measure of art appreciation is created all of the items should be related to the different components and types of art. If the questions are regarding historical time periods, with no reference to any artistic movement, stakeholders may not be motivated to give their best effort or invest in this measure because they do not believe it is a true assessment of art appreciation.

2. Construct Validityis used to ensure that the measure is actually measure what it is intended to measure (i.e. the construct), and not other variables. Using a panel of “experts” familiar with the construct is a way in which this type of validity can be assessed. The experts can examine the items and decide what that specific item is intended to measure. Students can be involved in this process to obtain their feedback.

Example: A women’s studies program may design a cumulative assessment of learning throughout the major. The questions are written with complicated wording and phrasing. This can cause the test inadvertently becoming a test of reading comprehension, rather than a test of women’s studies. It is important that the measure is actually assessing the intended construct, rather than an extraneous factor.

3. Criterion-Related Validity is used to predict future or current performance - it correlates test results with another criterion of interest.

Example: If a physics program designed a measure to assess cumulative student learning throughout the major. The new measure could be correlated with a standardized measure of ability in this discipline, such as an ETS field test or the GRE subject test. The higher the correlation between the established measure and new measure, the more faith stakeholders can have in the new assessment tool.

Example: When designing a rubric for history one could assess student’s knowledge across the discipline. If the measure can provide information that students are lacking knowledge in a certain area, for instance the Civil Rights Movement, then that assessment tool is providing meaningful information that can be used to improve the course or program requirements.

5. Sampling Validity (similar to content validity) ensures that the measure covers the broad range of areas within the concept under study. Not everything can be covered, so items need to be sampled from all of the domains. This may need to be completed using a panel of “experts” to ensure that the content area is adequately sampled. Additionally, a panel can help limit “expert” bias (i.e. a test reflecting what an individual personally feels are the most important or relevant areas).

Example: When designing an assessment of learning in the theatre department, it would not be sufficient to only cover issues related to acting. Other areas of theatre such as lighting, sound, functions of stage managers should all be included. The assessment should reflect the content area in its entirety.

  1. Make sure your goals and objectives are clearly defined and operationalized. Expectations of students should be written down.
  2. Match your assessment measure to your goals and objectives. Additionally, have the test reviewed by faculty at other schools to obtain feedback from an outside party who is less invested in the instrument.
  3. Get students involved; have the students look over the assessment for troublesome wording, or other difficulties.
  4. If possible, compare your measure with other measures, or data that may be available.

References

American Educational Research Association, American Psychological Association, &

National Council on Measurement in Education. (1985). Standards for educational and psychological testing. Washington, DC: Authors.

Cozby, P.C. (2001). Measurement Concepts. Methods in Behavioral Research (7th ed.).

California: Mayfield Publishing Company.

Cronbach, L. J. (1971). Test validation. In R. L. Thorndike (Ed.). Educational

Measurement(2nd ed.). Washington, D. C.: American Council on Education.

Moskal, B.M., & Leydens, J.A. (2000). Scoring rubric development: Validity and

reliability. Practical Assessment, Research & Evaluation, 7(10). [Available online: http://pareonline.net/getvn.asp?v=7&n=10].

The Center for the Enhancement of Teaching. How to improve test reliability and

validity: Implications for grading. [Available online: http://oct.sfsu.edu/assessment/evaluating/htmls/improve_rel_val.html].

Reliability and Validity (2024)

FAQs

Reliability and Validity? ›

Reliability and validity are both about how well a method measures something: Reliability refers to the consistency of a measure (whether the results can be reproduced under the same conditions). Validity refers to the accuracy of a measure (whether the results really do represent what they are supposed to measure).

What is reliability and validity using any example? ›

For a test to be reliable, it also needs to be valid. For example, if your scale is off by 5 lbs, it reads your weight every day with an excess of 5lbs. The scale is reliable because it consistently reports the same weight every day, but it is not valid because it adds 5lbs to your true weight.

What is data validity and reliability in research? ›

Reliability refers to a study's replicability, while validity refers to a study's accuracy. A study can be repeated many times and give the same result each time, and yet the result could be wrong or inaccurate. This study would have high reliability, but low validity; and therefore, conclusions can't be drawn from it.

What is reliability vs validity for dummies? ›

Reliability is the degree to which a measuring instrument gives consistent results. The degree to which a measuring instrument can accurately measure that which it is designed to measure is called validity.

Is there a relationship between validity and reliability? ›

How do they relate? A reliable measurement is not always valid: the results might be reproducible, but they're not necessarily correct. A valid measurement is generally reliable: if a test produces accurate results, they should be reproducible.

How do you explain validity and reliability? ›

Reliability refers to the consistency of a measure (whether the results can be reproduced under the same conditions). Validity refers to the accuracy of a measure (whether the results really do represent what they are supposed to measure).

What is an example of reliability but not validity? ›

A measurement maybe valid but not reliable, or reliable but not valid. Suppose your bathroomscale was reset to read 10 pound lighter. The weight it reads will be reliable(the same every time you step on it) but will not be valid, since it is notreading your actual weight.

How to ensure data is reliable and valid? ›

9 Factors that influence data reliability
  1. Data source.
  2. Comprehensive coverage.
  3. Data collection methods.
  4. Data integrity.
  5. Time sensitivity.
  6. Consistency and repeatability.
  7. Data cleaning and preprocessing.
  8. Standardized metrics.
Aug 31, 2023

How to write reliability and validity in a research proposal? ›

Follow the steps below to address validity and reliability in your proposal:
  1. Define Reliability and Validity: ...
  2. Include a Subsection on Measurement Instruments: ...
  3. Discuss Face Validity: ...
  4. Address Content Validity: ...
  5. Discuss Construct Validity: ...
  6. Explain Criterion-Related Validity: ...
  7. Discuss Reliability: ...
  8. Mention Pilot Testing:

Can something be valid but not reliable? ›

Can a test be valid but not reliable? A valid test will always be reliable, but the opposite isn't true for reliability – a test may be reliable, but not valid. This is because a test could produce the same result each time, but it may not actually be measuring the thing it is designed to measure.

What makes research reliable and valid? ›

Reliability and validity are concepts used to evaluate the quality of research. They indicate how well a method, technique, or test measures something. Reliability is about the consistency of a measure, and validity is about the accuracy of a measure.

What is good reliability and validity? ›

Reliability is consistency across time (test-retest reliability), across items (internal consistency), and across researchers (interrater reliability). Validity is the extent to which the scores actually represent the variable they are intended to. Validity is a judgment based on various types of evidence.

What is the problem with reliability and validity? ›

Researcher's bias, effect of the researcher on the setting, theoretical assumptions influence the process and direction of research. These issues pose challenges to reliability and validity of the data, interpretations and conclusions.

How to check reliability and validity of questionnaire? ›

There are different ways to estimate the reliability of a questionnaire including: (1) Test-Retest reliability that is estimated by calculating the correlations between scores of two or more administrations of the questionnaire with the same participants; (2) Parallel-Forms reliability that is estimated by creating two ...

What is the difference between validity and accuracy and reliability? ›

It is different from validity, which focuses on whether the experiment actually measures what it is intended to measure. Accuracy is also separate from reliability, which refers to consistency of results when measurements are repeated.

What is an example of something that is reliable and valid? ›

Reliability implies consistency: if you take the ACT five times, you should get roughly the same results every time. A test is valid if it measures what it's supposed to. Tests that are valid are also reliable. The ACT is valid (and reliable) because it measures what a student learned in high school.

What reliability means examples? ›

For example, a quality vehicle that is safe, fuel efficient, and easy to operate may be considered high quality. If this car continues to meet this criterion for several years, and performs well and remains safe even when driven in inclement weather, it may be considered reliable.

What is an example of validity? ›

Validity refers to whether a test measures what it aims to measure. For example, a valid driving test should include a practical driving component and not just a theoretical test of the rules of driving.

What is an example of reliability and validity in research proposal? ›

For example, if an experiment produces same result every time then it is reliable. Validity: Validity denotes suitable and accurate measurements. For example, the valid instrument accomplishes a target accurately or without involving variable values. It makes sure the measurement needs.

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