Fairness in Assessment: Identifying a Complex Adaptive System

Assessment design in health professions education is continuously evolving. There is an increasing desire to better embrace human judgement in assessment. Thus, it is essential to understand what makes this judgement fair. This study builds upon existing literature by studying how assessment leaders conceptualise the characteristics of fair judgement.

Sixteen assessment leaders from 15 medical schools in Australia and New Zealand participated in online focus groups. Data collection and analysis occurred concurrently and iteratively. We used the constant comparison method to identify themes and build on an existing conceptual model of fair judgement in assessment.

Fairness is a multi-dimensional construct with components at environment, system and individual levels. Components influencing fairness include articulated and agreed learning outcomes relating to the needs of society, a culture which allows for learner support, stakeholder agency and learning (environmental level), collection, interpretation and combination of evidence, procedural strategies (system level) and appropriate individual assessments and assessor expertise and agility (individual level).

We observed that within the data at fractal, that is an infinite pattern repeating at different scales, could be seen suggesting fair judgement should be considered a complex adaptive system. Within complex adaptive systems, it is primarily the interaction between the entities which influences the outcome it produces, not simply the components themselves. Viewing fairness in assessment through a lens of complexity rather than as a linear, causal model has significant implications for how we design assessment programs and seek to utilise human judgement in assessment.