Reliability and Validity in Research > Curricular validity

## What is Curricular Validity?

Validity is defined by how well a test measures what it’s supposed to measure.

**Curricular validity**refers to how well test items

*reflect the actual curriculum*(i.e. a test is supposed to be a measure of what’s on the curriculum). It usually refers to a specific, well-defined curriculum, like those provided by states to schools. McClung (1978) defines it as

“…a measure of how well test items represent the objectives of the curriculum”.

A similar term is instructional validity, which is how well the test items reflect what is actually *taught*. McClung defines instructional validity as “an actual measure of whether the schools are providing students with instruction in the knowledge and skills measured by the test.”

In an ideal educational world, there would be no need for a distinction between instructional and curricular validity: teachers follow a curriculum, students learn what is on the curriculum through their teachers. However, **it doesn’t always follow that a child will be taught what is on the curriculum.** Many things can have an impact on what parts of the curriculum are taught (or not taught), including:

- Inexperienced teachers,
- Substitute teachers,
- Poorly managed schools/flow of information,
- Teachers may choose not to teach specific parts of the curriculum they don’t agree with (e.g. evolution or sex education),
- Teachers might skip over parts of the curriculum they don’t fully understand (like mathematics. According to
*this report*, elementary school teachers struggle with basic math concepts).

## How to Measure Curricular Validity

Curricular validity is usually measured by a panel of curriculum experts. It’s not measured statistically, but rather by a rating of “valid” or “not valid.” A test that meets one definition of validity might not meet another. For example, a test might have curricular validity, but not instructional validity and vice versa.

**References**:

McClung, M. S. (1978). Competency testing programs: Legal and educational

issues. Fordham Law Review, 47, 651-712.

Ostashevsky, L. (2016). Elementary school teachers struggle with Common Core math standards.

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*Statistical concepts explained visually* - Includes many concepts such as sample size, hypothesis tests, or logistic regression, explained by Stephanie Glen, founder of StatisticsHowTo.

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