The Cognitive-Affective-Motivation Model of Learning (CAMML): Standing on the Shoulders of Giants

• Published in: Canadian journal of school psychology Vol. 37; no. 1; pp. 117 - 134
• Main Author: McGrew, Kevin S.
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01-03-2022; SAGE PUBLICATIONS, INC
• Subjects: Academic Achievement; Achievement Need; Cognitive Ability; Educational psychology; Independent Study; Intelligence; Investment; Learning Readiness; Motivation; Personality Traits; Resistance (Psychology); School Psychologists; School Psychology; Student Motivation; domain-specific; crossing the Rubicon; self-regulated learning; taxonomies; Gf-Gc theory; readiness; Big 5; motivation; aptitudes; aptitude complexes; CHC theory; individual differences
• ISSN: 0829-5735; 2154-3984
• DOI: 10.1177/08295735211054270

The Cognitive-Affective-Motivation Model of Learning (CAMML) is a proposed framework for integrating contemporary motivation, affective (Big 5 personality) and cognitive (CHC theory) constructs in the practice of school psychologists (SPs). The central tenet of this article is that SPs need to integrate motivation alongside affective and cognitive constructs vis-à-vis an updated trilogy-of-the-mind (cognitive, conative, affective) model of intellectual functioning. CAMML builds on Richard Snow’s seminal research on academic aptitudes—which are not synonymous with cognitive abilities. Learning aptitude complexes are academic domain-specific cognitive abilities and personal investment mechanisms (motivation and self-regulation) that collectively produce a student’s readiness to learn in a specific domain. CAMML incorporates the “crossing the Rubicon” commitment pathway model of motivated self-regulated learning. It is recommended SPs take a fresh look at motivation theory, constructs, and research, embedded in the CAMML aptitude framework, by going back-to-the-future guided by the wisdom of giants from the field of cognition, intelligence, and educational psychology.