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Intelligent Insights on Intelligence Theories and Tests
Showing posts with label self-beliefs. Show all posts
Showing posts with label self-beliefs. Show all posts
Friday, February 07, 2025
Monday, January 11, 2021
The Model of Achievement Competence Motivation (MACM): Part D-Volition and Self-Regulated Learning Domains
The Model of Achievement Competence Motivation (MACM) is a series of slide modules. By clicking on the link you can view the slides at SlideShare. This is the fourth (Part D) in the series--Volition and Self-regulated Learning Domains described.. There will be a total of five modules. The modules will serve as supplemental materials to "The Model of Achievement Competence Motivation (MACM)--Standing on the shoulders of giants" (McGrew, in press, 2021 - in a forthcoming special issue on motivation in the Canadian Journal of School Psychology)
You should be able to access the prior modules (A-C) from the link above.
Click here for prior "beyond IQ" labeled posts at this blog.
Wednesday, January 06, 2021
The Model of Achievement Competence Motivation (MACM) Part B: An overview of the MACM model
The Model of Achievement Competence Motivation (MACM) is
a series of slide modules. By clicking on the link you can view the
slides at SlideShare. This is the second (Part B) in the series--An overview of the model. There will be a total of five modules. The
modules will serve as supplemental materials to "The Model of
Achievement
Competence Motivation (MACM)--Standing on the shoulders of giants"
(McGrew, in press, 2021 - in a forthcoming special issue on motivation
in the
Canadian Journal of School Psychology)
Click here for first of the series (Part A: Introduction and Background)
Click here for prior "beyond IQ" labeled posts at this blog.
Saturday, August 11, 2018
Beyond IQ: Mining the “no-mans-land” between Intelligence and IQ: Journal of Intelligence special issue
I am pleased to see the Journal of Intelligence addressing the integration of non-cognitive variables (personality; self-beliefs; motivational constructs; often called the “no-mans land” between intelligence and personality— I believe this catchy phrase was first used by Stankov) with intellectual constructs to better understanding human performance. I have had a long-standing interest in such comprehensive models as reflected by my articulation of the Model of Academic Competence and Motivation (MACM) and repeated posting of “beyond IQ” information at my blogs.
Joel Schneider and I briefly touched in this topic in our soon to be published CHC intelligence theory update chapter. Below is the select text and some awesome figures crafted by Joel.
Our simplified conceptual structure of knowledge abilities is presented in Figure 3.10. At the center of overlapping knowledge domains is general knowledge—knowledge and skills considered important for any member of the population to know (e.g., literacy, numeracy, self-care, budgeting, civics, etiquette, and much more). The bulk of each knowledge domain is the province of specialists, but some portion is considered important for all members of society to know. Drawing inspiration from F. L. Schmidt (2011, 2014), we posit that interests and experience drive acquisition of domain-specific knowledge.
In Schmidt's model, individual differences in general knowledge are driven largely by individual differences in fluid intelligence and general interest in learning, also known as typical intellectual engagement (Goff & Ackerman, 1992). In contrast, individual differences in domain-specific knowledge are more driven by domain-specific in-terests, and also by the “tilt” of one's specific abilities (Coyle, Purcell, Snyder, & Richmond, 2014; Pässler, Beinicke, & Hell, 2015). In Figure 3.11, we present a simplified hypothetical synthesis of several ability models in which abilities, interests, and personality traits predict general and specific knowledge (Ackerman, 1996a, 1996b, 2000; Ackerman, Bowen, Beier, & Kanfer, 2001; Ackerman & Heggestad, 1997; Ackerman & Rolfhus, 1999; Fry & Hale, 1996; Goff & Ackerman, 1992; Kail, 2007; Kane et al., 2004; Rolfhus & Ackerman, 1999; Schmidt, 2011, 2014; Schneider et al., 2016; Schneider & Newman, 2015; Woodcock, 1993; Ziegler, Danay, Heene, Asendorpf, & Bühner, 2012).
Click on images to enlarge.
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Joel Schneider and I briefly touched in this topic in our soon to be published CHC intelligence theory update chapter. Below is the select text and some awesome figures crafted by Joel.
Our simplified conceptual structure of knowledge abilities is presented in Figure 3.10. At the center of overlapping knowledge domains is general knowledge—knowledge and skills considered important for any member of the population to know (e.g., literacy, numeracy, self-care, budgeting, civics, etiquette, and much more). The bulk of each knowledge domain is the province of specialists, but some portion is considered important for all members of society to know. Drawing inspiration from F. L. Schmidt (2011, 2014), we posit that interests and experience drive acquisition of domain-specific knowledge.
In Schmidt's model, individual differences in general knowledge are driven largely by individual differences in fluid intelligence and general interest in learning, also known as typical intellectual engagement (Goff & Ackerman, 1992). In contrast, individual differences in domain-specific knowledge are more driven by domain-specific in-terests, and also by the “tilt” of one's specific abilities (Coyle, Purcell, Snyder, & Richmond, 2014; Pässler, Beinicke, & Hell, 2015). In Figure 3.11, we present a simplified hypothetical synthesis of several ability models in which abilities, interests, and personality traits predict general and specific knowledge (Ackerman, 1996a, 1996b, 2000; Ackerman, Bowen, Beier, & Kanfer, 2001; Ackerman & Heggestad, 1997; Ackerman & Rolfhus, 1999; Fry & Hale, 1996; Goff & Ackerman, 1992; Kail, 2007; Kane et al., 2004; Rolfhus & Ackerman, 1999; Schmidt, 2011, 2014; Schneider et al., 2016; Schneider & Newman, 2015; Woodcock, 1993; Ziegler, Danay, Heene, Asendorpf, & Bühner, 2012).
Click on images to enlarge.
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Saturday, March 17, 2018
The importance of differential psychology for school learning: 90% of school achievement variance is due to student characteristics
This is why the study of individual differences/differential psychology is so important. If you don’t want to read the article you can watch a video of Dr. Detterman where he summarizes his thinking and this paper.
Education and Intelligence: Pity the Poor Teacher because Student Characteristics are more Significant than Teachers or Schools. Article link.
Douglas K. Detterman
Case Western Reserve University (USA)
Abstract
Education has not changed from the beginning of recorded history. The problem is that focus has been on schools and teachers and not students. Here is a simple thought experiment with two conditions: 1) 50 teachers are assigned by their teaching quality to randomly composed classes of 20 students, 2) 50 classes of 20 each are composed by selecting the most able students to fill each class in order and teachers are assigned randomly to classes. In condition 1, teaching ability of each teacher and in condition 2, mean ability level of students in each class is correlated with average gain over the course of instruction. Educational gain will be best predicted by student abilities (up to r = 0.95) and much less by teachers' skill (up to r = 0.32). I argue that seemingly immutable education will not change until we fully understand students and particularly human intelligence. Over the last 50 years in developed countries, evidence has accumulated that only about 10% of school achievement can be attributed to schools and teachers while the remaining 90% is due to characteristics associated with students. Teachers account for from 1% to 7% of total variance at every level of education. For students, intelligence accounts for much of the 90% of variance associated with learning gains. This evidence is reviewed
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Education and Intelligence: Pity the Poor Teacher because Student Characteristics are more Significant than Teachers or Schools. Article link.
Douglas K. Detterman
Case Western Reserve University (USA)
Abstract
Education has not changed from the beginning of recorded history. The problem is that focus has been on schools and teachers and not students. Here is a simple thought experiment with two conditions: 1) 50 teachers are assigned by their teaching quality to randomly composed classes of 20 students, 2) 50 classes of 20 each are composed by selecting the most able students to fill each class in order and teachers are assigned randomly to classes. In condition 1, teaching ability of each teacher and in condition 2, mean ability level of students in each class is correlated with average gain over the course of instruction. Educational gain will be best predicted by student abilities (up to r = 0.95) and much less by teachers' skill (up to r = 0.32). I argue that seemingly immutable education will not change until we fully understand students and particularly human intelligence. Over the last 50 years in developed countries, evidence has accumulated that only about 10% of school achievement can be attributed to schools and teachers while the remaining 90% is due to characteristics associated with students. Teachers account for from 1% to 7% of total variance at every level of education. For students, intelligence accounts for much of the 90% of variance associated with learning gains. This evidence is reviewed
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Monday, November 14, 2016
Beyond Cognitive Abilities: An Integrative Model of Learning-Related Personal Competencies and Aptitude Trait Complexes
For centuries educational psychologists have highlighted the
importance of "non-cognitive" variables in school learning. Below readers will find a PPT presentation that presents a "big picture"
overview of how cognitive abilities and non-cognitive factors can be integrated
into an over-arching conceptual framework.
The presentation also illustrates how the big picture framework can be
used to conceptualize a number of contemporary "buzz word"
initiatives related to building 21st century educationally important skills
(social-emotional learning, critical thinking, creativity, complex problem
solving, etc.)
The two preliminary images can be enlarged by click on them.
Prior related "Beyond IQ" blog posts can be found here.
The two preliminary images can be enlarged by click on them.
Prior related "Beyond IQ" blog posts can be found here.
Friday, September 16, 2011
Beyond IQ Series #13: Self Beliefs:"Can I do this activity"--Locus of Control
This 13th installment in the Beyond IQ series introduces the broad MACM domain of self beliefs, and the first subdomain in this area--locus of control . [All installments in this series (and other related posts and research) can be found by clicking here].
(double click on image to enlarge)
Self-Beliefs: Can I do this activity?
When pondering this question, students reflect on a number of motivational self-beliefs (e.g., self- confidence, academic self-concept, academic self- efficacy) that have dominated social cognitive models of motivation research the past three decades. Although germane to all students, this question is particularly salient for students who have experienced repeated academic failure (e.g., students with disabilities, disadvantaged students).
Locus of Control: Definition and Conceptual Background
A person’s belief about the perceived causes (internal vs. external) for their success or failure. An internal attribution orientation is present when a person perceives their success or failure as contingent on their own behavior and due to relatively unchanging personal characteristics. An external orientation is present when success or failure is perceived as being under the control of others, unpredictable, and the result of luck, chance, or fate.
Locus of control is an individual’s beliefs about the perceived causes (internal or external) for personal success or failure on a task. According to attribution theory, when a student fails or succeeds at a task (e.g., failing a reading exam or a particular assignment), the student analyzes the situation to determine the causes for the outcome. An internal attribution orientation is inferred when a student perceives personal success or failure as contingent on their behavior and relatively permanent personal characteristics. An external orientation is present when a student views academic success or failure as being under the control of others, unpredictable, and/or the result of luck, chance, or fate (Elliott, 1997; Linnenbrink & Pintrich, 2002b; Rotter, 1966). Causal attributions are categorized as per the dimensions of stability (the stability of the cause), locus (internal or external), and controllability (can the perceived cause be controlled).
Locus of Control: Implications
The locus of control construct (and attribution theory) has a lengthy history in psychology. Locus of control is a popular and important concept in many theories of individual differences “because it has consistently shown a difference between ‘normal’ and ‘special’ populations” (Elliott, 1997, p. 27). The research literature has consistently associated a high internal locus of control (vs low external) with a wide array of positive outcomes. Briefly, research (Beirne- Smith, Ittenbach, & Patton, 1998; Borkowski, Weyhing, & Carr, 1988; Elliott, 1997; Linnenbrink & Pintrich, 2002b; Rivera et al., 1998; Snow et al., 1996) has suggested the following:
Level of internality is correlated with academic achievement (teacher grades and tests) and the degree of effort a student invests in free-time intellectual and learning activities. The positive effect of being a “high internal” on academic achievement may not be direct, but rather, may be mediated through other academic facilitators.
High internals are better able to defer gratification, adopt a long-term future-oriented perspective, and are more persistent when faced with difficult and challenging tasks.
The positive effect of causal attributions varies as a function of the primary characteristics of causality. In general, positive adaptation and outcomes occur when success or failure is attributed to stable internal characteristics (e.g., ability). Within-person trait-like characteristics are hypothesized to be viewed by the student as being readily available when faced with future learning tasks. Attributions to more unstable but controllable internal characteristics can also be adaptive. For example, motivation and persistence are characteristics that tend to fluctuate over time (therefore are not reflective of an unchangeable stable trait). These more fluid personal characteristics can be modified by the student. Finally, the negative effects of failure can be buffered when the causal attribution focuses on more unstable, uncontrollable, and external factors (e.g., bad luck).
There is a large body of attribution theory/locus of control literature focused on students with behavior and learning problems. This is not unexpected given that: (a) a student’s beliefs about the causes of success and failures impacts future learning; and (b) attribution beliefs can be environmentally influenced (Linnenbrink & Pintrich, 2002b). For example, students with learning disabilities often develop significant motivation and social problems due to inaccurate perceptions of stable within-person characteristics that are often the focal point of causal success or failure (ability and skills). Attributing unsuccessful learning to personal inabilities has been associated with a more passive learning style and learned helplessness (where many students with disabilities develop a failure expetancy and a dependence on others to solve their problems). Research involving students with mental retardation has reported that these individuals may often display an external locus of control that, in turn, is often associated with learned helplessness and lower levels of personal responsibility, self-reliance, and self-regulatory learning. Locus of control is an important MACM variable and a valued outcome for students with a checkered history of academic success and failure.
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intelligence IQ tests IQ testing IQ scores CHC intelligence theory CHC theory Cattell-Horn-Carroll human cognitive abilities psychology school psychology individual differences cognitive psychology neuropsychology neuroscience psychology special education educational psychology psychometrics psychological assessment psychological measurement IQs Corner general intelligence Beyond IQ aptitude school learning social emotional learning resiliency training CASEL motivation
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Sunday, November 30, 2008
Beyond IQ Project: Ed Psych article abstracts
A recent issue of the Journal of Educational Psychology (2008, Vol. 100, 8) had a number of articles dealing with constructs included in the Beyond IQ projects Model of Academic Competence and Motivation (MACMM). Below are the iAbstracts (images captured and emailed from myiPhone). If any reader would like to read one of the articles (I would provide a copy of the pdf file), in exchange for a guest blog post summary to this bog, please contact the blogmaster (iapsych@charter.net)
Technorati Tags: psychology, educational psychology, school psychology, neuropsychology, Journal of Educational Psychology, motivation, self-beliefs, self-efficacy, self-confidence, goal orientation, MACMM, Beyond IQ, IQs Corner, academic competence
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