When setting up a role in Assess, the learning environment helps define the cognitive and experiential demands of the position. It looks at four key dimensions:
- Level of experience required
- Learning demands of the role
- Pace of work
- Variety of tasks and responsibilities
These inputs help shape a picture of the kind of work environment someone will be stepping into.
It is important to note that the questions help define the learning environment associated with the role. Each set of options represents different requirements and is not necessarily ranked on a scale from less important to more important for the role.
Once selections are made across all four categories, as seen above, the system calculates an ideal benchmark percentile. This helps determine the level of Aptitude that is likely to lead to success in the role.
The system then compares a candidate’s Aptitude score against this benchmark to generate a star rating.
Ratings reflect how closely a candidate’s Aptitude aligns with the role’s defined learning environment:
- Indicates very strong alignment
- Indicates moderate alignment
- Indicates limited alignment
This scoring is always comparative and role-specific; it is not about "good or bad" Aptitude but about fit for the environment described.
The logic behind the learning environment is grounded in science, allowing role definitions to go beyond surface-level traits. As informed by research, it must be noted that aptitude scores that are higher than what is required for the role are not penalised in the star rating. This helps ensure that candidate-job matches are both evidence-based and adaptable to a wide range of industries and seniority levels.