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Beyond IQ:  The Model of Academic Motivation and Competence

"Chance favors the prepared mind"

- Louis Pasteur

Individuals, regardless of their individual characteristics, do not learn in vacuums. Cognitive and non-cognitive individual difference characteristics interact with a variety of environmental variables to produce various educational and work outcomes.

beyond-iqA number of comprehensive models of school learning have been postulated to describe and explain the learning process.  All models of school learning recognize the contribution of certain intrinsic learner characteristics.   The major categories of learner characteristics are learner demographics, history of educational placement, social and behavioral outcomes, motivation and affective, cognitive, metacognitive, and psychomotor abilities.

IAP and MindHub™ have a particular interest in the non-cognitive variables, that when combined with cognitive or intellectual abilities, circumscribe the primary individual differences learners bring to learning environments.  Based on a review and integration of research and theory Dr. McGrew has articulated a heuristic Model of Achievement Competence Motivation (MACM), which serves as a model for investigating and measuring essential learning behaviors.  This model builds on Richard Snow’s concept of academic aptitude.

This model has been integrated into a more comprehensive Cognitive-Affective-Motivation Model of Learning (CAMML) which is described in the following article.

A number of special research reports, briefs, on-line SlideShare Power Point presentations, and web-based Mind Map resources are available for download or for on-line web page viewing at the MindHub™ Special Reports and Publications section. Visit IQ’s Corner for new reports.


Below are the MACM and CAMML models as described in McGrew (2022)




An updated "big picture" background overview (Beyond Cognitive Abilities:  An Integrative Model of Learning-related Personal Competencies and Aptitude Trait Complexes) is available at IQs Corner