Free Report Example on Assessing Validity & Reliability of Tests: Content Validity

Introduction

Validity refers to the degree to which a test can measure what is was designed to measure. On the other hand, reliability refers to the consistently measuring test. There has to be a strong positive correlation between the findings of the same test if the same instrument is replicated or used in different participants.

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Assessment of Validity

Content validity is mainly concerned with the assessment of the oral test representativeness of the aspects of a construct. In this case, a construct refers to an idea or a third that contains several conceptual elements. A construct is usually subjective that is why it has to be proven to be valued. To produce a valid result, the content of the test used or the measurement method has to comprehensively cover all aspects of the constructs. Missing some aspects of the construct will threaten the validity of the measurement. For example, in case a math teacher creates a geometry test for his class. It is expected to cover all forms of topics of geometry that was taught in their class. In case, some topics on geometry are left out, then the test has failed in content validity assessment does not measure student’s understand if OD all topics in geometry. The results are not valid. The test should measure content validity by measuring the knowledge of the content domain that the test was created to measure.

Assessment of Reliability

Reliability may be internal or external reliably. The internal reliability will measure the consistency of the results across items in the test. On the other hand, the external reliability is concerned with the degree to which a measure can vary from one user to the other.

Split-Half Method

The split-half method will measure the internal consistency of the measurement instruments. The results of two half are of the instrument why it is split into two. If the two can provide the same result, then the test has achieved internal reliability. In case the instrument has a low correlation (r<0.25) then it shield be eliminated or improved.

Test-Retest

The test-retest method is used to determine the external conscience of the test. For example, when using the psychometrics tests or administering a questionnaire, it is I point to assess whether the test can principle the same results over time or on two different occasions. A high correlation between the two test results should high test- rests reliability if the correlation is higher than 0.5. It is, however, important to understand that there are chances of recalls, which contributes to recall bias. That is what the period green tests should be longer.

Inter-Rater Reliability

Inter-rater reliability is concerned with the results givens by deferent raters. If two rates unknown to each other can produce similar results, then the test can be said to have high interrater reliability. If not, the reliability of the instrument can be improved by operationalizing the behaviors and objectively defined the constructs.

Scenario

In this case, the manager was considering selecting a team of employees. The HR manager was thinking of using an expensive election system that will relatively affect the company adversely. The multiple rating tool is selected because it is assumed to have higher validity despite being costly. The main argument is that using a less costly tool for making hiring decisions could be costly to the company in the end.

The first test will involve administering the tool on the first group of samples (groups A), followed by group B. A regression and correlation analysis will be conducted to determine the relationship between groups A and group B. the results of the regression analysis will be used to determine the reliability. If the two groups or tests produce a higher correlation (R=0.50 and above), then the instrument is said to be reliable. If the correlation coefficient is lower than 50%, then it can be concluded that the item has poor validity and reliability score.

Item Development Process

Content validation involves the development of a new instrument and can provide evidence about the content validity of the item as it assesses the degree to which the item measures the selected construct. The validation makes the instrument appropriate for making meaningful inferences and organizational decisions based on the scores given the purpose of the assessment. Some of the key element of thaw instrument under consideration include items, the stimuli the codes, the company’s instruction, the response formats as well as the overall scoring.

To administer the test, it is important to first pilot test the instrument. This means selecting a randomly selected sample to which the test is administered on a small scale. The test sample should not be a subset of the targeted test sample. Any deficiency in the test instrument is then amended before it is tested on the actual population or sample (Ebel, 1956). When administering the test on the sample, it is important to note that the sample selected is not only random (representative) but also large enough. Large sample size is elected bisque it helps in reducing bias. The sample will not be convened in the same room but will be meeting at a specific location across the city due to convenience purposes and given the instrument or questionnaire to fill.

External Validity Evidence From Outside Studies

The researcher will conduct his validation study, which may be expensive. However, due to time constraints, the researcher will use some of the professionally created assessment tools and products with already documented validity. It is important to note that the validity evidence may be obtained from other tests or outside test study. It is transferable to the current study based on the uniform guidelines and the standard based on the SIOP principle.

How to Interpret Validity Coefficients

It is a general rule that a higher validity coefficient is more beneficial than a low validity coefficient. A test will be considered valid if the coefficient is above 0.35. However, coefficients of R=0.21 and above is useful. Any validity coefficient bellow 0.21 is poor, thus unlikely to be useful. For a single test, it is important to note that the validities for selection will be relatively higher than the multiple tests because it is only a single test. The measure is used for predicting selected or fewer aspects of the total performances. For example, when administering the psychometrics test on job applicants, it is important to ensure that the tool can be used to provide reliable and valid results. This will be done by ensuring that all the aspects of the job are tested without which the test results may either be invalid or unreliable. The test should be reliable if the level of the adverse impact that can be associated with the assessment tools. This way, the test should be pilot-tested before it is administered.

Conclusion

The decision to implement a specific assessment or test will be determined by the validity of the assessment. If the assessment is very beneficial because of the high validity and reliability, then it is accepted. The goal is to reduce the adverse effect of the testing statement. The evaluation of the validity assessment is very complex and multiple factor method is the most effective way because, with the multifactor, it is easy to assess several constructs and increases the transferability of the instrument. Applying valid and reliable assessment instruments properly can help the organization achieve its aims and make better decisions. Combining several assist tools incorporate activities such as hiring is advisable if resources are not constraining, but it is important to be a caution to the errors assayed with specific tools.

References

Ebel, R. (1956). Obtaining and Reporting Evidence on Content Validity. Educational And Psychological Measurement, 16(3), 269-282. doi: 10.1177/001316445601600301

Huddleston, E. (1956). Test Development based on Content Validity. Educational And Psychological Measurement, 16(3), 283-293. doi: 10.1177/001316445601600302

Lennon, R. (1956). Assumptions Underlying the Use of Content Validity. Educational And Psychological Measurement, 16(3), 294-304. doi: 10.1177/001316445601600303

Levine, A. (1958). Aptitude Versus Achievement Tests As Predictors of Achievement. Educational And Psychological Measurement, 18(3), 517-525. doi: 10.1177/001316445801800306