Beyond cognitive abilities: An integrative model of learning-related personal competencies and aptitude trait complexes

Dr. Kevin S. McGrew
Institute for Applied Psychometrics
& University of Minnesota
Beyond Cognitive Abilities: An Integrative
Model of Learning-related Personal
Competences and Aptitude Trait Complexes
© Institute for Applied Psychometrics (IAP) Dr. Kevin McGrew 10-13-16

Going “beyond cognitive abilities” has been an area of
study in education and psychology for decades

Spearman on “conative” abilities (1927)
“The process of cognition
cannot possibly be treated apart
from those of conation and
affection, seeing that all these
are but inseparable aspects in
the instincts and behavior of a
single individual, who himself,
as the vary name implies, is
essentially indivisible” (p. 2)

Conation: the
proactive (as
opposed to habitual)
part of motivation
that connects
knowledge, affect,
drives, desires, and
instincts to behavior

“The tendency to take and maintain a definite
direction; the capacity to make adaptations for the
purpose of attaining a desired end; and the power
of auto-criticism” (translation by Terman, 1916, p.
45). All three of these phrases refer at least as
much to conative processes and attitudes as to
reasoning powers.
Binet's concept of intelligence was much like
Snow's concept of aptitudes (p. 5).
Alfred Binet’s definition of Intelligence (Corno
et al., 2002 translation by Terman, 1916)

“When our scales measure the non-
intellective as well as the intellectual factors
in intelligence, they will more nearly
measure what in actual life corresponds to
intelligent behavior” (p. 103)
Important distinction: Intelligence vs.
intelligent performance
David Wechsler (1944) on “non-intellective factors”

Messick (1979) on “non-cognitive factors”

It is important to not target “feel good” faddish
variables that have good face or consumer
validity— and that have little empirical validity

Back to the Future: Non-cognitive factors are again being
revisited with different terminology
• Social-emotional learning
• Cognitive engagement
• Self-determination
• Growth mindset
• Habits of Mind
• Self-beliefs
• Grit
• …..

“Students' engagement with school, the belief
that they can achieve at high levels, and their
ability and willingness to do what it takes to
reach their goals not only play a central role
shaping students' ability to master academic
subjects, they are also valuable attributes that
will enable students to lead full lives, meeting
challenges and making the most of available
opportunities along the way (Schunk and
Mullen, 2013). In order to effectively meet the
economic, political and social demands for
competencies, much more is required of
students and adults than just cognitive
proficiency (Levin, 2012).”

Cognitive
engagement
literature

A “big picture” model (taxonomy; working
heuristic model), even if provisional, is needed to
guide research and development regarding the
assessment of student competencies and learning

We have an embarrassment of riches in search of order
• Social-emotional learning
• Cognitive & student engagement
• Self-determination
• Habits of Mind
• Growth mindset
• Self-beliefs
• Grit
• …..
• Need for Achievement Theory
• Intrinsic Motivation Theory
• Goal Setting Theory
• Attribution Theory
• Achievement Goal Theory
• Interest Theory
• Self-efficacy Theory
• Self-worth Theory
• Self-regulation Theory
• Self-determination theory
• ……

Physical
Competence
Social-
Emotional
Intelligence
Conceptual
Intelligence
Practical
Intelligence
Personal
Competence
Greenspan’s Model(s) of Personal Competence

Physical Cognitive Conative Affective
Personality
Adapted Snow (Corno et al., 2002) model of aptitude
Intellect

• Aptitude – “a predisposition to respond in a way that fits, or
does not fit, a particular situation or class of situations. The
common thread is potentiality” (Corno et al., 2002, p. 3)
• “Aspects of personality—achievement motivation, freedom
from anxiety, appropriately positive self-concept, control of
impulses, and others—are aptitudes as well, contributing
importantly to copy with some challenges” (Snow, et al.,
1996, p. 4)
Aptitude intelligence

A proposed “big picture” heuristic conceptual framework (a meta-taxonomy model):
Integrate these two broad stroke models*
* Plus information from
recent related research
© Institute for Applied Psychometrics
(IAP) Dr. Kevin McGrew 10-13-16

Despite the explosion of discussions regarding social-emotional
learning (SEL) by policy-makers and educators, well validated
models of social and emotional competencies are not available.
The conceptual research in these areas is in the formative stages.
• Lots of conceptual clutter
• The jingle-jangle jungle fallacy

Physical
Physical
abilities
Psycho-
motor
abilities
Sensory-
perceptual
abilities
Cognitive
Cognitive
processes
Acquired
knowledge
systems
Conative
Motivations
Volitional
controls
Affective
Temper-
ament traits
Character-
istic moods
Intellect
Personality
The big picture: An adapted Snow (Corno et al., 2002) model of aptitude (MACM revised; 10-13-16)
Knowing FeelingWilling
Cool intelligences Hot intelligences
© Institute for Applied
Psychometrics (IAP) Dr.
Kevin McGrew 10-13-16

Cool intelligences
Abilities involving
perceptual
processing and
logical reasoning
Hot intelligences:
Abilities involving
emotionally-salient
information

(Note. The cognitive aspects
of social intelligence [Gei]
have provisionally been added
to the CHC taxonomy)
Note. Cognitive processes are similar to
procedural knowledge or “intelligence-as-
process” (Ackerman PPIK model)
Acquired knowledge systems can also be
labeled as declarative knowledge or
“intelligence as knowledge” (Ackerman PPIK)
Personal competence
domain
Cognitive
Cognitive
processes
Acquired
knowledge
systems
Cognitive taxonomy: Best evidence-based consensus model:
Cattell-Horn-Carroll (CHC) model of cognitive abilities

Gc Gkn Grw Gq Gf Gwm Gv Ga Gl Gr Gs Gt
g
The Cattell-Horn-Carroll (CHC) taxonomy of human abilities (v 2.4)
A higher-order conceptualization based on MDS of the WJ IV norm data (McGrew & Schneider, 06-20-16)
(The tentative broad abilities of Gh, Gk, Go, Gk, Gp, Gps &
Gei and all broad domain level I narrow abilities omitted for
readability purposes.)
Intelligence-as-
Knowledge (Ackerman)
Acquired knowledge
systems
gc Cattell
Intelligence-as-Process
(Ackerman)
System 2 (controlled deliberate
cognitive operations/processes)
(Kahneman)
gf Cattell
Intelligence-as-Process:
Speed/fluency (Ackerman)
System 1 (automatic rapid
cognitive processes)
(Kahneman)
gs – General speed factor

Trait-complexes (combinations, mixtures, compounds, etc.)
Ackerman PPIK model
“Intelligence-as-Process
“Personality”
“Interests”
“Intelligence-as-Knowledge”

Affective
Temper-
ament traits
Character-
istic moods

AffectiveConative
Motivations
Volitional
controls
Temper-
ament
traits
Character-
istic moods
Personality
Personal competence
domain
E C AES OE
Personality taxonomy: Best evidence-based
consensus model: The Big Five
E = Extraversion
C = Conscientiousness
ES = Emotional stability (aka, neuroticism)
A = Agreeableness
OE = Openness to experience

Factor analysis
of 209 items in
very large
samples
The SENNA 1.0
SEMS (social
emotional skills)
empirically
based model

The SENNA 1.0 SEMS dimensions
correspond (subsume and go
beyond) the Big Five +
E = Extraversion
C = Conscientiousness
ES = Emotional stability (aka, neuroticism)
A = Agreeableness
OE = Openness to experience
LC = Locus of control
E C AES OE LC
Conscientiousness (C): Working Hard and
Persevering at Tasks at School
Emotional Stability (ES): Managing
Negative Emotions Versus Experiencing
Negative Affect
Agreeableness (A): Prosocial Skills in
Peer Relationships
Open-Mindedness (OE): Curiosity,
Imagination, and Invention
External Locus of Control/Negative
Valence (LC): Ineffective Coping and
Hopeless Beliefs
Extraversion (E): Energetic
Approach to the Social World
The SENNA 1.0 SEMS empirically based model

The SENNA 2.0 SEMS
dimensions correspond
(subsume and go beyond)
the Big Five +
E A CN O
Engaging with Others (vs Withdrawal
and Avoidance) - E
Conscientious Task Performance (or
Goal Orientation) - C
Negative-Emotion Regulation (or
Emotional Resilience = ER) - N
Amity (vs Enmity): “Tending and
Befriending” Others - A
Open-Mindedness: Interest and
devotion to matters of the mind - O

The SENNA 2.0 SEMS dimensions correspond to
dimensions, or combinations of dimensions, from these
domains from the adapted Snow model
E A CN O

Conative
Motivations
Volitional
controls
Personal
competence
domain
Conative taxonomy: A “working” heuristic framework:
The Model of Academic Competence and Motivation
(MACM; Revised 09-26-16; K. McGrew)*
Self-
Regulation
Cognitive
styles & lrng
approaches
Volitional
controls
Motivational
orientation
Interests &
Attitudes
Self-beliefs
Motivations
(Note: Self-regulation is most likely
closely tied to the concept of executive
functions
* The MACM domains are very similar
to cognitive engagement action
patterns and dispositions and drivers
of engagement
• “Do I want to do this activity
and why?”
• “Is this activity of interest to
me…is it worth the effort?”
• “Can I do this
activity?
• “Am I capable?”
• “What do I need to do to succeed?”
© Institute for Applied Psychometrics (IAP)
Dr. Kevin McGrew 10-13-16

The
background
information
and white
paper that
outlines the
Model of
Academic
Competence
and Motivation
(MACM) is
available
online.
http://tinyurl.com/cf7uj2

Dispositions concern not what abilities people have, but how people
are disposed to use and invest their abilities and capabilities — what
they are disposed to do.
Passions, motivations, sensitivities, and values all seem likely to play a
role in intelligence. To define intelligence as a matter of ability
without also honoring the other elements that enliven it is to fail to
capture its human spark.
Thinking dispositions & drivers of
cognitive engagement. The human spark
of learning and intelligence
Psychometrics (IAP) Dr.
Kevin McGrew 10-13-16

© Institute for Applied Psychometrics
(IAP) Dr. Kevin McGrew 10-13-16

More information available at the MindHub™ web portal

Commitment
to action
“Crossing the
Rubicon”
Reciprocal
interactions
& feedback
Orientations Towards Self
(Motivations)
Phrases used to describe this stage
-Arena of planning and decision-making
-Contemplating and deliberating over options
-Processes involved in decision to pursue goals
-WishWantIntentions
Self-
Beliefs
Motivational
orientations
Interests &
Attitudes
• Can I do this task?
• Do I want to do this task & why?
Volitional Controls
(Cognitive Styles & Lrng.
Approaches)
Phrases used to describe this stage
-Arena of Implementation and management
-Carrying out plans and intentions
-Action orientation (state or action oriented)
-Mindfulness (mindful effort investment)
-Self-regulation of cognition and emotions
Self-Regulated
Learning
Strategies
Conative
styles
• What do I need to do to succeed?
OutcomesCOMMITMENT PATHWAY TO ENGAGED LEARNING
Contemplate & plan Decide & Commit Implement & monitor
Cognitive
engagement
Feedback loop
Psychometrics (IAP) Dr. Kevin
McGrew 10-13-16

• Academic motivation
• Intrinsic motivation
• Academic goal orientation
• ….
• Academic interests,
attitudes & values
• ….
• Locus of control
• Academic self-efficacy
• Academic self-concept
• Academic ability
conception
• ….
• Planning & activation
• Monitoring
• Control & regulation
• Reaction & reflection
• ….
• Cognitive styles
• Approaches to learning
• Defensive styles
• ….
Motivational
orientation
Interests &
Attitudes
Self-
Regulation
Self-beliefs
Cognitive
styles & lrng.
approaches
Motivations Volitional
controls
Conative
McGrew 10-13-16

Many current educational
initiatives are emphasizing abilities
such as creative thinking, creativity,
and complex problem solving.
How can one conceptualize these
type of valued educational
outcomes?

CHC
MACM
Proposal
The CHC, MACM,
& SENNA SEMS
taxonomies can be
used to understand
important constructs
and can be used as
blueprints for
evaluating and
developing instruments SENNA SEMS (Big 5+)
McGrew 10-13-16

Constructs such as critical thinking, creativity, and complex problem solving might be conceptualized as
combinations (amalgams) of cognitive, conative and affective characteristics
Other models of “intelligence” (Gardner’s Multiple Intelligences) might be considered as a model that
combines characteristics across cognitive, physical, conative and affective domains
Think about these constructs as trait-complexes (combinations, mixtures, compounds, amalgams, etc.)
McGrew 10-13-16

Think about these constructs as trait-complexes (combinations, compounds, etc.;
see Ackerman’s PPIK model as illustrative example)

Intellectual or cognitive
“performance”
A hypothesized model for
understanding various
cognitive constructs
Intended to help minimize
the jingle-jangle fallacy and
amount of conceptual clutter
Example
trait complexes
Relative strength
Relative weakness © Institute for Applied
McGrew 10-13-16

• Expertise/ach in math
• Critical thinking in math
• Creativity in math
• Gardner’s logical-
mathematical intelligence
• Expertise/ach in science
• Critical thinking in science
• Creativity in science
© Institute for
Applied
Psychometrics (IAP)
Dr. Kevin McGrew
10-13-16

• Expertise/ach in dance
• Critical thinking in dance
• Creativity in dance
• Gardner’s bodily-kinesthetic
intelligence
McGrew 10-13-16

Cognitive
(Knowing)
Conative
(Willing)
Affecting
(Feeling)
Or, think of these
constructs in the
following manner
McGrew 10-13-16

Cognitive
(Knowing)
Conative
(Willing)
Affective
(Feeling)
The constructs of critical thinking, complex problem solving, creativity, etc.
can be thought of as trait complexes (mixtures, compounds, amalgams, constellations)
McGrew 10-13-16

Cognitive
(Knowing)
Conative
(Willing)
Conative
(Feeling)
Critical thinking ???
McGrew 10-13-16

Affective
(Feeling)
Conative
(Willing)
Cognitive
(Knowing)
Critical thinking ???
McGrew 10-13-16

Cognitive
(Knowing)
Conative
(Willing)
Conative
(Feeling)
Complex problem solving ???
McGrew 10-13-16

Conative
(Feeling)
Cognitive
(Knowing)
Conative
(Willing)
Complex problem solving ???

Cognitive
(Knowing)
Conative
(Willing)
Affective
(Feeling)
Social intelligence?????

Critical thinking Complex problem solving Social intelligence
Think of these constructs (and others) as different
combinations of personal characteristics (complexes,
amalgams, combinations, constellations, etc.)

CHC
MACM
Proposal
The CHC, MACM,
& SENNA SEMS
taxonomies can be
used to
understand
important
constructs and to
be used as
blueprints for
evaluating and
developing
instruments
SENNA SEMS (Big 5+)© Institute for Applied
McGrew 10-13-16

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