High volume assessment: which is better for the candidate experience, short online assessments or serious games?

How do you select top international talent?

Suppose, as an organization, you are dealing with large volumes of candidates in your recruitment and selection process. So, which is better, the psychological test or serious gaming?

Pretty tough question. In any case, what not to do is clear. CV selection based on unclear criteria and then burdening the entire organization with interviews with candidates not pre-selected.

Yet this is still too common. If you don’t want to think about implementing online testing or serious gaming, at least delve into Lou Adler’s thinking on killer questions.

Psychological tests (the right ones) are proven reliable and valid. They have been examined along scientific criteria for usefulness in selection. They measure relevant predictive characteristics such as (parts of) intelligence, personality structure, or motivations, for example.

Commitment and psychological testing reinforce each other

Increasingly, psychological tests can be taken entirely online. Even ability tests, which measure components of intelligence, can now be taken online and at home. The downside is that they are generally not that fun to take.

An organization may ask a candidate to take an online assessment if the candidate is well into the application process and is seriously considering joining the organization.

A self-assessment makes a candidate curious

What matters with self-assessment is that the results are meaningful and relevant to the candidate. Even then, there is a willingness to take tests and questionnaires.

For example, consider using ability tests anonymously in the sourcing phase so that a candidate can determine for themselves whether they meet the set standard. Then it becomes relevant to the candidate because they learn something about themselves.

A fun recruitment game, breaks the ice

Serious gaming can be an enjoyable experience. A common term associated with it is “immersive,” meaning that players become deeply engaged in the gaming experience. Various game mechanics are used to draw players into this world. As a result, serious gaming is often more fun and approachable than traditional testing methods. This can encourage candidates to participate more readily. If the game is well-designed, players will be more likely to engage with it, making it a suitable tool during the sourcing phase of recruitment. However, there are drawbacks; the psychometric validity of the available games is not yet very convincing.

A lot of work is underway on this by various parties, but it is still a work in progress. The scientific body of evidence that makes good psychometric tests robust is still being built here. Read more about the difference between recruitment and assessment games here.

So for now, the question “which is better for the candidate experience?” presents a dilemma: robustness and high-quality feedback versus approachability. That the market needs both is clear by now. After all, the different phases of the candidate journey require different approaches.

Questions, comments or a different take on this topic? Let us know below and engage with the author.

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Evidence-based Selection Methods.

This fact sheet provides an overview of the most commonly used (psychological) selection methods, both classical and modern. The figures are based on meta-analyses and dominant scientific literature.

Method Predictive validity (r) Typical reliability
Cognitive ability (GMA test) .51 High (.85-.95)
Work test .54 High
(inter-rater ≥.70)
Structured interview .51 Medium-high (.60-.75)
Unstructured interview .18-.38 Low-medium (.40-.55)
Integrity test .41 High (α ≥.80)
Conscientiousness (Big Five) .31 Medium-high (α ~.75-.85)
Job knowledge test .48 High (≥.80)
Years of service .18 Not applicable
Video/asynchronous interview (incl. AI) .30-.40 Good at structuring; algorithmically variable
Machine learning / algorithmic models .20-.50 Depends on dataset; generalizability limited
Serious games / game-based work samples .35-.50 High on objective metrics
Social media screening .00-.20 Low and variable

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