Understanding concurrent validity: how correlating test scores with other measures informs assessment

Validity isn’t a dusty term you file away in a drawer of theory. For ESOL topics, it’s a practical way to judge whether a test really reflects what it sets out to measure. Think of it like checking a compass before you hike: you want to trust the needle, not guess at where you’re headed. With that in mind, here’s a clear, human-friendly guide to the four big types of validity you’ll hear about in GACE ESOL materials, including the one that answers the question you’re likely to see.

Validity 101: what are we really testing?

• Content validity: Does the test cover the right material? If we’re assessing English language proficiency, are the items and tasks drawn from listening, reading, speaking, and writing in ways that reflect real use?

• Construct validity: Is the test measuring the theoretical concept it claims to measure? For language, that means things like communicative ability, or accuracy in grammar, or vocabulary depth—does the data support that the test taps those ideas?

• Concurrent validity: Are the test scores tied to other related measures taken at the same time? In other words, do scores line up with how we already expect a student to perform on related indicators, when those indicators are measured now?

• Face validity: Does the test look like it’s measuring what it should, at first glance? This one isn’t about numbers or studies; it’s about a intuitive impression—do students and teachers feel the test is asking about the right things?

Let’s slow down and zoom in on concurrent validity, since that’s the one you’ll often see described as “the one that correlates with other measures taken at the same time.”

Concurrent validity in everyday terms

Here’s the thing: concurrent validity is all about correlation. If you give a new English language measure today and also record scores from an established, related measure at the same moment, you should see a relationship between the two sets of scores. A strong, positive correlation suggests the new measure is behaving like the established one in the same context. It’s not about proving a theory in the long run; it’s about a snapshot that shows the new measure aligns with what we already know about language ability at that moment.

A simple classroom-style example helps. Imagine you’ve created a short oral proficiency task for students and you want to know if it’s doing a good job of reflecting speaking ability. You compare results from this new task with scores from a well-established speaking assessment that’s been around for years. If students who score high on the new task also score high on the established one, that’s concurrent validity at work. If the correlation is weak or non-existent, you’d pause and reconsider whether the new task is really measuring speaking ability—or perhaps it’s tapping something else entirely, like quick memory or pronunciation quirks.

Why concurrent validity matters in ESOL contexts

• It helps educators decide which tools to trust in the moment. When you’re making decisions about placement, intervention, or even feedback you give to learners, you want to rely on measures that line up with other trusted data.

• It keeps comparisons fair. If every measure is supposed to gauge language ability, it makes sense to check whether a new measure behaves like an established one—under the same conditions and at the same time.

• It informs us about the relationships between skills. Language ability isn’t one neat bundle; it’s a bundle of listening, speaking, reading, and writing, with overlaps and gaps. Concurrent validity can reveal whether a test taps those overlapping areas in a sensible way.

A quick contrast: other validity types in plain language

• Construct validity: Think of this as the big-picture proof. It answers the question, “Does this test capture the underlying construct we care about?” Rather than a single moment in time, it often requires a broader set of analyses, like looking at how test items cluster together or how results align with theories about language learning. It’s the deeper dive.

• Content validity: This one is about the content itself. Do the questions, tasks, or prompts cover the full domain you want to measure? If the goal is to assess overall language proficiency, you’d expect a good test to include a spectrum of tasks across listening, reading, speaking, and writing.

• Face validity: This is the first impression test-takers get. It’s subjective and informal, but it matters. If a test looks irrelevant or confusing, test-takers may approach it with distrust, which can affect performance independent of actual ability.

Connecting the ideas with real-world test design

Let me explain with a simple analogy you might relate to. Suppose you’re shopping for a new umbrella. You don’t just check whether it opens and closes. You also want to know if it resists wind, if the fabric blocks rain as promised, and whether it feels sturdy in your hand. If all those pieces line up, you have more confidence in the umbrella’s usefulness in a real downpour.

Language testing works similarly. A single feature—say, a speaking task—should not be the sole basis for judging a learner’s overall ability. Test designers look for a blend: content validity ensures the right domains are covered; construct validity makes sure the test measures the intended language constructs; concurrent validity confirms that new tools behave like trusted measures in the same moment;face validity keeps the interface and items approachable so test-takers aren’t fighting the format as they work.

Digressions that still circle back

A lot of the nuance in validity comes down to what counts as “good evidence.” In practice, teams might gather multiple lines of evidence: expert reviews of items to judge domain coverage, statistical analyses that show how items relate to each other, and correlations with external benchmarks. It’s a little like assembling a bouquet from different flowers: each bloom adds color, but together they create a fuller picture.

If you’re wandering through ESOL materials and you see a mention of validity, you can ask yourself a few friendly questions:

• Are we looking at how scores relate to other measures we trust?

• Do the tasks resemble real language use, not just vocabulary drills or grammar drills?

• Is there a clear rationale for why certain tasks exist in the test?

The practical upshot for learners and instructors

• Clarity in expectations: When tests are backed by solid validity work, learners know what the assessments aim to capture. That means feedback can be targeted and meaningful.

• Fairness in scoring: Validity work often goes hand in hand with fair design. If a measure aligns with a well-established standard, it reduces the chance that a learner is penalized for quirks unrelated to language ability.

• Better teaching moves: For instructors, understanding validity helps connect classroom activities to the aims of assessment. If a test claims to measure communicative competence, you’ll want activities that give students chances to practice real communication in varied contexts.

A gentle verdict on the original question

Which type of validity is established by correlating test scores with other measures taken at the same time? The answer is concurrent validity. It’s all about the moment-to-moment alignment between the new measure and related measures that already exist. It’s a practical, evidence-based check that helps ensure the test is behaving like its established cousins when you’re collecting data right now.

If you’re curious to explore further, you can think of this topic as part of a bigger conversation about how we understand learning in real time. Language isn’t a single skill you can pin down with a single metric. It’s living, changing, and expressed in many ways—through what you hear, what you read, how you write, and how you speak. Validity helps us keep faith with that complexity.

A few light, human touches to end

• You’ll notice that the world of testing lives somewhere between art and science. You don’t just plug in numbers and call it a day; you interpret patterns, question surprises, and refine approaches.

• If you’ve ever wondered why a test feels easy or hard, you’re tapping into the psychology behind validation. The best assessments balance challenge with fairness, and they do so by gathering evidence from multiple angles.

• And yes, it can get a bit nerdy. The good news is that the core idea is simple: we want the scores to reflect what we say they reflect, and we want to see that reflected in other reliable measures happening at the same time.

If this topic sparks other questions—about how different validity types interact, or how educators decide which measures to trust—feel free to swing back. A thoughtful look at measurement makes any language journey more meaningful, because it helps you see beyond the surface and understand what underpins the numbers you encounter.

In the end, validity is the compass that keeps the voyage honest. And when you connect the dots between what a test claims to measure and what it actually shows in the moment, you’re doing more than answering a single question. You’re tapping into the core idea of responsible assessment: moving together toward clearer understanding, one well-supported conclusion at a time.