How to Choose the Right Assessments for Early Careers Hiring
2 minutes
Chief psychologist, Ben, explains the three key things you want from your early careers assessments: potential, scale, and convenience.
When it comes to early careers hiring, there are four things that really matter when you're choosing an assessment. Focusing on potential; ensuring the assessment scales; it doesn't take too much time; and it's AI-resistant.
Get these right and you're laughing, drop the ball on one of them and you'll be paying a price.
Focus on potential, not current skills
The first thing is this: for grads, apprentices, and interns, you're not hiring for what they can do right now. You're hiring for what they'll be able to do once you've trained them.
That's a fundamentally different brief to experienced hiring, where someone needs to walk in and get on with it from day one. Early careers doesn't work like that. You're going to be training them, putting them through qualifications, giving them structured development. So what actually matters is whether they can learn, whether they'll benefit from that investment, and whether they've got the underlying ability to succeed in whatever you put them through.
Realistically, they're new. Most of them haven't worked anywhere meaningfully before, so expecting a high level of technical skill isn't reasonable. And even for the ones who do have a bit of a head start, that advantage tends to disappear pretty quickly once everyone's going through the same training. What lasts is the capacity to learn. That's what you're actually assessing for.
So the message here is: assess their cognitive ability (usually best measured through a combination of numerical, verbal and logical reasoning tests), not hard skills.
Make sure it scales
The second thing is that your assessment needs to be easy for you to interpret, especially given that early careers hiring usually comes with volume. We're often talking hundreds of candidates, sometimes thousands.
You need something you can rank. Not something where you have to sit down with a detailed report for every single candidate just to make a screening decision. That doesn't scale, and it'll become a bottleneck fast. The assessment should give you a clear score you can sort by, so the process stays manageable however many applications you're dealing with.
Keep it reasonable for candidates
The third thing is candidate experience, which is easy to underestimate.
Early careers applicants are typically going through multiple processes at once. They're applying to several organisations, each with their own tests, interviews, and assessment centres. Their time is genuinely stretched, and if your process is inconvenient or unusually demanding, they'll naturally gravitate towards employers whose processes are easier to fit around everything else they've got going on.
You don't need to make it frictionless. But you do need to make it manageable. That means it shouldn't take too long, and it shouldn't have technical or logistical requirements that would stop a reasonable candidate from completing it. Keep it accessible, and you'll hold onto more of the good ones.
Make sure it's resistant to AI
There's a fourth thing that's becoming increasingly hard to ignore: AI.
Young people are, broadly speaking, very comfortable with AI tools. They've grown up with advanced tech, they use AI constantly, and if there's an opportunity to use AI assistance during an assessment, a significant number will take it. That's not a moral judgement on them, it's just the reality of where things are.
Most traditional assessments weren't built with this in mind. If your assessment is a static set of questions with written answers, it can be cheated with AI. Doesn't matter how many anti-cheat measures you've wrapped around it, whether that's recording the candidate, tracking their mouse, locking their browser. Someone can easily use their phone to get an AI to write the answer. There's no technical barrier stopping them.
The only reliable answer is an assessment that's resistant to AI by design, not by surveillance. This typically means assessments with moving parts, dynamic elements, or formats that don't lend themselves to being answered by a language model sitting on a separate device. The goal isn't to catch cheaters after the fact but to build a process where the opportunity to cheat doesn't really exist in the first place.
We've written separately about what makes an assessment AI-resistant, and it's worth a read if this is something you're thinking about. The short version is: static question-and-answer formats are increasingly vulnerable, and the solution is in the design of the assessment itself, not in the monitoring layer on top of it.
Why Mindmetriq works for early careers hiring
If you're looking for an assessment that actually meets all of the above, Mindmetriq is worth a serious look.
It's built to assess general cognitive ability (potential) rather than existing hard skill knowledge, which makes it perfect for early careers.
It's also highly scalable. Candidates get a single score that you can rank and filter by, which means you're not spending hours interpreting reports when you've got 500 applications to get through. The process stays clean and manageable however high the volume gets.
From a candidate experience perspective, it's designed to be completed relatively quickly (each task is 4-6 minutes, so you can get a measure of general cognitive ability in under 15 minutes). It's also been designed to be performed on mobiles as well as desktops, so it very accessible to candidates especially those who may only have access to a phone.
And on the AI question, Mindmetriq is designed with this in mind. Its format doesn't lend itself to being completed with AI assistance in the way that a static written assessment does, which means you're getting an honest picture of who you're actually assessing.
For early careers hiring specifically, it covers the things that matter. That's not always easy to find in a single tool.
Conclusion and next steps
Early careers hiring has its own logic, and the assessments that work well for experienced hiring often don't translate. You need something that measures potential, scales without becoming a burden, gives candidates a reasonable experience, and holds up against AI use.
If you'd like to find out more about how Mindmetriq fits into an early careers process, or if you want to talk through what the right assessment setup looks like for your organisation, get in touch with the team at Test Partnership. We work with early careers hiring teams regularly and can help you figure out what actually makes sense for your context.
Primary author
Ben Schwencke
Chief psychologist at Test Partnership. MSc in Organisational Psychology with over ten years experience in psychometric testing.
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