Individual differences in college-age learners: The importance of relational reasoning for learning and assessment in higher education.

BACKGROUND

The term individual differences refers to the physical, behavioral, cognitive, social, and emotional attributes that make each human unique. Late adolescence to young adulthood represents a time of significant neurobiological and cognitive transformations that contribute further to human variability. Those transformations include an increase in the white matter of the brain accompanied by an increased capacity for higher-order thinking, reasoning, decision-making, and selfcontrol. These capacities fall under the category of executive functions.

AIM

The purpose of this article is to overview one particular executive function, relational reasoning; to consider its significance to college students' learning and performance; and to argue for its inclusion in assessment programs within higher education.

RESEARCH SUMMARY

Relational reasoning can be defined as the ability to discern meaningful patterns within any informational stream. Through an orchestrated program of research, four forms of relational reasoning have been identified that reflect perceived similarities (analogical), discrepancies (anomalous), contradictions (antinomous), and contrasts (antithetical). These four forms have been documented in studies of doctors diagnosing cases, science and mathematics teachers providing instruction, and engineering students designing new products. These manifestations have also formed the structure of formal measures of relational reasoning that have been shown to be psychometrically sound indicators of this executive function.

CONCLUSIONS AND IMPLICATIONS

This article closes with an argument for the inclusion of relational reasoning in performance assessments designed for higher education. Consistent with views of competence as a continuum, it is argued that this inclusion should encompass the measurement of relational reasoning both as an underlying general competence and as a component of domain-specific performance.