Author: Airlie Hilliard
Image-based assessments are psychometric assessments that can measure constructs such as personality and creativity. There are multiple formats that image-based assessments can take, including using images to replace question statements or using images to replace response options. Here, response options might represent a continuum of a single trait, or might use a mixed-trait or forced-choice format where images represent two or more different traits.
The scoring of image-based assessments can also vary, depending on the format of the assessment. For example, when using images to represent Likert scale points or high or low levels of a trait, a typical scoring key might be used that sums the number of times an image representing that trait is selected or summing the scale points represented by each chosen image. Forced choice formats can be more complex to score, so approaches based on item response theory might be used. Alternatively, an algorithmic approach might be taken that uses artificial intelligence or machine learning, where image choices are used to predict the construct as measured by another format, such as a questionnaire-based measure using a regression-based approach.
How can image-based assessments improve the candidate experience?
Like with many other novel assessment formats, particularly those that use artificial intelligence in their scoring, image-based assessments can have a number of benefits to the candidate experience. For example, alternative formats can increase engagement and immersion, making the experience more enjoyable for candidates. Images also evoke stronger reactions than text, meaning that choices might be more intuitive and easier to make, which can shorten the completion time.
Indeed, particularly when scored by algorithms, alternative formats can be quicker to complete since the algorithms can identify patterns in data, meaning that rich inferences can be made from relatively shorter assessments. This can help to reduce some of the pressure on candidates if they are not in the testing context for as long, and can mean the assessment is more convenient for candidates to complete since they do not have to set aside a large portion of their day.
How can image-based assessments be more accessible?
Assessments should be designed with universal design in mind in order to maximise the accessibility of procedures to different needs. Given that image-based assessments remove much of the text element of assessments, this can reduce some of the cognitive burden that comes with having to read large amounts of text. Furthermore, the lesser emphasis on text could help to support candidates with dyslexia and ADHD by requiring less reading and enabling greater concentration on the answering of the assessment. This may also help to support candidates with language processing disorders, or even bilingual or multilingual candidates by visually representing constructs in a way that is largely language agnostic.
How can the accessibility of image-based assessments be maximised?
While reducing the language element can be useful for some, it is also important to balance this for those who may have a preference for written or text-based communication. Ambiguous images that rely on the inference of facial cues might also be problematic for autistic candidates or visually impaired candidates for example. An over-reliance on colours could also be difficult for colourblind applicants to complete.
To overcome this, image-based assessments could be accompanied by ALT text that is supported by screen readers and by using well-designed and well-chosen images that are not ambiguous and have face validity for the construct they are measuring. Furthermore, accessibility can be maximised by ensuring that any key information to be inferred from the images is not represented only by colour and providing adjectives or a short statement with each image as a resource candidates can look to in support of their interpretation.
How can image-based assessments support diversity, equity, and inclusion?
Image-based assessments that depict humans provide an opportunity to promote and support diversity, equity, and inclusion by ensuring that the individuals in these images are diverse and do not play into stereotypes. For example, images should represent a wide range of ages, sexes and genders, ethnicities, body types, and abilities or disabilities. Furthermore, an active effort should be made to promote equality in images by avoiding stereotypes – such as images of men cleaning or showing emotion rather than females, to avoid stereotypes about cleaning being a female responsibility and females being emotional. By normalising the challenging of stereotypes, this can open up conversations about other ways they can be challenged within organisations.
Having an assessment that is perceived as more diverse and inclusive can also help to improve perceptions of an organisation if candidates believe that the selection assessment is a representation of the company’s values. This can result in access to a richer pool of top talent by attracting candidates who are typically underrepresented, and can give candidates a sense of belonging.
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