“Why g matters: The complexity of everyday life”, (1997-01):
Personnel selection research provides much evidence that intelligence (g) is an important predictor of performance in training and on the job, especially in higher level work. This article provides evidence that g has pervasive utility in work settings because it is essentially the ability to deal with cognitive complexity, in particular, with complex information processing. The more complex a work task, the greater the advantages that higher g confers in performing it well. Everyday tasks, like job duties, also differ in their level of complexity. The importance of intelligence therefore differs systematically across different arenas of social life as well as economic endeavor. Data from the National Adult Literacy Survey are used to show how higher levels of cognitive ability systematically improve individual’’s odds of dealing successfully with the ordinary demands of modern life (such as banking, using maps and transportation schedules, reading and understanding forms, interpreting news articles). These and other data are summarized to illustrate how the advantages of higher g, even when they are small, cumulate to affect the overall life chances of individuals at different ranges of the IQ bell curve. The article concludes by suggesting ways to reduce the risks for low-IQ individuals of being left behind by an increasingly complex postindustrial economy.
2009-duckworth.pdf: “Positive predictors of teacher effectiveness”, (2009; ):
Some teachers are dramatically more effective than others, but traditional indicators of competence (eg., certification) explain minimal variance in performance. The rigors of teaching suggest that positive traits that buffer against adversity might contribute to teacher effectiveness.
In this prospective longitudinal study, novice teachers (n = 390) placed in under-resourced public schools completed measures of optimistic explanatory style, grit, and life satisfaction prior to the school year. At the conclusion of the school year, teacher effectiveness was measured in terms of the academic gains of students. All 3 positive traits individually predicted teacher performance. When entered simultaneously, however, only grit and life satisfaction remained statistically-significant predictors.
These findings suggest that positive traits should be considered in the selection and training of teachers.
[Keywords: learned helplessness, explanatory style, grit, life satisfaction, teacher performance]
2007-noftle.pdf: “Personality predictors of academic outcomes: Big five correlates of GPA and SAT scores”, (2007; ):
The authors examined relations between the Big Five personality traits and academic outcomes, specifically SAT scores and grade-point average (GPA).
Openness was the strongest predictor of SAT verbal scores, and Conscientiousness was the strongest predictor of both high school and college GPA. These relations replicated across 4 independent samples and across 4 different personality inventories. Further analyses showed that Conscientiousness predicted college GPA, even after controlling for high school GPA and SAT scores, and that the relation between and college GPA was mediated, both concurrently and longitudinally, by increased academic effort and higher levels of perceived academic ability. The relation between Openness and SAT verbal scores was independent of academic achievement and was mediated, both concurrently and longitudinally, by perceived verbal intelligence.
Together, these findings show that personality traits have independent and incremental effects on academic outcomes, even after controlling for traditional predictors of those outcomes.
We analyze a data set comprised of academic records of undergraduates at the University of Oregon from 2000-2004. We find correlations of roughly 0.35 to 0.5 between SAT scores and upper division, in-major GPA (henceforth, GPA). Interestingly, low SAT scores do not preclude high performance in most majors. That is, the distribution of SAT scores after conditioning on high GPA (e.g., 3.5 or even 4.0) typically extends below 1000 (the average among test takers). We hypothesize that “overachievers” overcome cognitive deficits through hard work, and discuss to what extent they can be identified from high school records. Only a few majors seem to exhibit a “cognitive threshold”—such that high GPA (mastery of the subject matter) is very unlikely below a certain SAT threshold (i.e., no matter how dedicated or hard working the student). Our results suggest that almost any student admitted to university can achieve academic success, if they work hard enough. In addition to our primary result, we find that the best predictor of GPA is a roughly equally weighted sum of SAT and high school GPA, measured in standard deviation units. Using a sub-population of honors college students, we can estimate how students at elite universities would fare at a typical state university, allowing us to comment on issues such as grade inflation. Finally, we observe that 1) SAT scores fluctuate little on retest (very high reliability), 2) SAT and GRE scores (where available) correlate at roughly 0.75 (consistent with the notion that both tests measure a stable general cognitive ability) and 3) the SAT distribution of students that obtained a degree does not differ substantially from that of the entering class.
2008-chamorropremuzic.pdf: “Personality, intelligence and approaches to learning as predictors of academic performance”, (2008-05-01; ):
Students completed 4 psychometric tests soon after arriving at university: the NEO–PI-R measure of the Big Five personality traits (Costa & McCrae 1992); the Study Process Questionnaire, which measures approaches to learning (Biggs 1978); and 2 measures of cognitive ability: the Wonderlic IQ Test (Wonderlic, 1992) and the Baddeley Reasoning Test (Baddeley 1968) of fluid intelligence (gf). A year later they completed comprehensive essay-based exams and received a mean score based on 6 examinations.
Academic performance (AP) correlated with ability, achieving and deep learning approaches, Openness and. Together, these variables explained 40% of the in AP. Path analyses indicated that the effects of ability on AP were mediated by personality and learning approaches.
[Keywords: personality, intelligence, learning, academic performance]
2011-gensowski.pdf: “The Effects of Education, Personality, and IQ on Earnings of High-Ability Men”, (2011-01-24; ):
[Preprint version of Gensowski 2018]
This paper estimates the internal rate of return (IRR) to education for men and women of the Terman sample, a 70-year long prospective cohort study of high-ability individuals. The Terman data is unique in that it not only provides full working-life earnings histories of the participants, but it also includes detailed profiles of each subject, including IQ and measures of latent personality traits. Having information on latent personality traits is important as it allows us to measure the importance of personality on educational attainment and lifetime earnings.
Our analysis addresses two problems of the literature on returns to education: First, we establish causality of the treatment effect of education on earnings by implementing generalized matching on a full set of observable individual characteristics and unobserved personality traits. Second, since we observe lifetime earnings data, our estimates of the IRR are direct and do not depend on the assumptions that are usually made in order to justify the interpretation of regression coefficients as rates of return.
For the males, the returns to education beyond high school are sizeable. For example, the IRR for obtaining a bachelor’s degree over a high school diploma is 11.1%, and for a doctoral degree over a bachelor’s degree it is 6.7%. These results are unique because they highlight the returns to high-ability and high-education individuals, who are not well-represented in regular data sets.
Our results highlight the importance of personality and intelligence on our outcome variables. We find that personality traits similar to the Big Five personality traits are statistically-significant factors that help determine educational attainment and lifetime earnings. Even holding the level of education constant, measures of personality traits have statistically-significant effects on earnings. Similarly, IQ is rewarded in the labor market, independently of education. Most of the effect of personality and IQ on life-time earnings arise late in life, during the prime working years. Therefore, estimates from samples with shorter durations underestimate the treatment effects.
2011-uysala.pdf: “Unemployment duration and personality”, Selver Derya Uysal, Winfried Pohlmeier
A life span health-behavior model was investigated in this longitudinal study of personality influences on health. Teachers assessed 963 elementary schoolchildren on traits that formed scales assessing the dimensions of the five-factor (Big Five) model of personality. Smoking, alcohol use, body mass index ( ), and self-rated health were assessed 40 years later in midlife. Childhood personality traits were statistically-significantly associated with all 4 outcomes, and the effects were consistently larger for women than men. For men and women, childhood Conscientiousness was associated with less adult smoking and better adult self-rated health and, for women only, with lower adult . Mediation analyses suggested that the effects of Conscientiousness on self-rated health were partially mediated by smoking and . These findings add to the growing evidence that childhood personality traits predict adult health outcomes and are discussed in terms of future testing of the life span health-behavior model.
Objective: Personality traits predict both health behaviors and mortality risk across the life course. However, there are few investigations that have examined these effects in a single study. Thus, there are limitations in assessing if health behaviors explain why personality predicts health and longevity.
Method: Utilizing 14-year mortality data from a national sample of over 6,000 adults from the Midlife in the United States Study, we tested whether alcohol use, smoking behavior, and waist circumference mediated the personality-mortality association.
Results: After adjusting for demographic variables, higher levels of Structural equation models provided evidence that heavy drinking, smoking, and greater waist circumference significantly mediated the Conscientiousness-mortality association by 42%.predicted a 13% reduction in mortality risk over the follow-up.
Conclusion: The current study provided empirical support for the health-behavior model of personality-Conscientiousness influences the behaviors persons engage in and these behaviors affect the likelihood of poor health outcomes. Findings highlight the usefulness of assessing mediation in a structural equation modeling framework when testing proportional hazards. In addition, the current findings add to the growing literature that personality traits can be used to identify those at risk for engaging in behaviors that deteriorate health and shorten the life span.
The ability of personality traits to predict important life outcomes has traditionally been questioned because of the putative small effects of personality. In this article, we compare the predictive validity of personality traits with that of socioeconomic status (SES) and cognitive ability to test the relative contribution of personality traits to predictions of three critical outcomes: mortality, divorce, and occupational attainment. Only evidence from prospective longitudinal studies was considered. In addition, an attempt was made to limit the review to studies that controlled for important background factors. Results showed that the magnitude of the effects of personality traits on mortality, divorce, and occupational attainment was indistinguishable from the effects of and cognitive ability on these outcomes. These results demonstrate the influence of personality traits on important life outcomes, highlight the need to more routinely incorporate measures of personality into quality of life surveys, and encourage further research about the developmental origins of personality traits and the processes by which these traits influence diverse life outcomes.
“You and Your Research”, (1986-03-07):
[Transcript of a talk by mathematician and Bell Labs manager Richard Hamming about what he had learned about computers and how to do effective research (republished in expanded form as Art of Doing Science and Engineering: Learning to Learn; 1995 video). It is one of the most famous and most-quoted such discussions ever.]
At a seminar in the Bell Communications Research Colloquia Series, Dr. Richard W. Hamming, a Professor at the Naval Postgraduate School in Monterey, California and a retired Bell Labs scientist, gave a very interesting and stimulating talk, ‘You and Your Research’ to an overflow audience of some 200 Bellcore staff members and visitors at the Morris Research and Engineering Center on March 7, 1986. This talk centered on Hamming’s observations and research on the question “Why do so few scientists make substantial contributions and so many are forgotten in the long run?” From his more than 40 years of experience, 30 of which were at Bell Laboratories, he has made a number of direct observations, asked very pointed questions of scientists about what, how, and why they did things, studied the lives of great scientists and great contributions, and has done introspection and studied theories of creativity. The talk is about what he has learned in terms of the properties of the individual scientists, their abilities, traits, working habits, attitudes, and philosophy.
2005-zhao.pdf: “What Makes the Difference? A Practical Analysis of Research on the Effectiveness of Distance Education”, (2005; ):
This article reports findings of a meta-analytical study of research on distance education. The purpose of this study was to identify factors that affect the effectiveness of distance education. The results show that although the aggregated data of available studies show nodifference in outcomes between distance education and face-to-face education as previous research reviews suggest, there is remarkable difference across the studies. Further examination of the difference reveals that distance education programs, just like traditional education programs, vary a great deal in their outcomes, and the outcome of distance education is associated with a number of pedagogical and technological factors. This study led to some important data-driven suggestions for and about distance education.
2004-kim.pdf: “Schniederjans_lo”, mcdonaldm
2006-bassili.pdf: “Promotion and prevention orientations in the choice to attend lectures or watch them online”, (2006-11-06; ):
When presented with the option to use a new instructional technology, students often face an approach-avoidance conflict. This study explored promotion and prevention orientations, concepts linked to approach and avoidance in Higgins’s regulatory focus theory, in the choice to attend lectures or watch them online. Openness, a core disposition in the Big Five Model of personality, and positive attitudes towards the utility of the Internet, reflect promotion orientations that are potentially related to the choice to watch lectures online. By contrast, neuroticism, another core disposition in the Big Five Model, and anxiety about the Internet as a computer technology, reflect a prevention orientation that is potentially related to the choice of attending lectures in class. The results illustrate that both promotion and prevention are at work in the choice to attend lectures or to watch them online. Neuroticism and anxiety about the Internet as a computer technology were related to the choice to attend lectures in class, whereas the perceived utility of the Internet was related to the choice to watch lectures online. Instructional mode choice was not related to examination performance, suggesting that the choice to attend lectures or watch them online has more to do with individual differences in promotion and prevention orientations than with pedagogical characteristics that impact learning.
2009-nemanich.pdf: “Enhancing Knowledge Transfer in Classroom Versus Online Settings: The Interplay Among Instructor, , , Content, and Context”Ambika p PrasadTECHBOOKS
2010-abzug.pdf: “PAPER Template”, IATED
2012-hendegren.pdf: “The Dog that Didn't Bark: What Item Nonresponse Shows about Cognitive and Non-Cognitive Ability”, David Hedengren, Thomas Stratmann
2011-chahino.pdf: “AN EXPLORATION OF THE RELATIONSHIP BETWEEN STUDENTS TAKING ONLINE CLASSES AND PERSONALITY TYPES”, mchahino
2013-keller.pdf: “The importance of personality in studentsâ€™ perceptions of the online learning experience”, Heath Keller, Steven J. Karau
2013-fariba.pdf: “Academic Performance of Virtual Students based on their Personality Traits, Learning Styles and Psychological Well Being: A Prediction”, Tabe Bordbar Fariba
1969-jensen.pdf: “How Much Can We Boost IQ and Scholastic Achievement?”, (1969-05-01; ):
Arthur Jensen argues that the failure of recent compensatory education efforts to produce lasting effects on children’s IQ and achievement suggests that the premises on which these efforts have been based should be reexamined. He begins by questioning a central notion upon which these and other educational programs have recently been based: that IQ differences are almost entirely a result of environmental differences and the cultural bias of IQ tests. After tracing the history of IQ tests, Jensen carefully defines the concept of IQ, pointing out that it appears as a common factor in all tests that have been devised thus far to tap higher mental processes. Having defined the concept of intelligence and related it to other forms of mental ability, Jensen employs an analysis ofmodel to explain how IQ can be separated into genetic and environmental components. He then discusses the concept of “heritability”, a statistical tool for assessing the degree to which individual differences in a trait like intelligence can be accounted for by genetic factors. He analyzes several lines of evidence which suggest that the heritability of intelligence is quite high (ie., genetic factors are much more important than environmental factors in producing IQ differences). After arguing that environmental factors are not nearly as important in determining IQ as are genetic factors, Jensen proceeds to analyze the environmental influences which may be most critical in determining IQ. He concludes that prenatal influences may well contribute the largest environmental influence on IQ. He then discusses evidence which suggests that social class and racial variations in intelligence cannot be accounted for by differences in environment but must be attributed partially to genetic differences. After he has discussed the influence on the distribution of IQ in a society on its functioning, Jensen examines in detail the results of educational programs for young children, and finds that the changes in IQ produced by these programs are generally small. A basic conclusion of Jensen’s discussion of the influence of environment on IQ is that environment acts as a “threshold variable.” Extreme environmental deprivation can keep the child from performing up to his genetic potential, but an enriched educational program cannot push the child above that potential. Finally, Jensen examines other mental abilities that might be capitalized on in an educational program, discussing recent findings on diverse patterns of mental abilities between ethnic groups and his own studies of associative learning abilities that are independent of social class. He concludes that educational attempts to boost IQ have been misdirected and that the educational process should focus on teaching much more specific skills. He argues that this will be accomplished most effectively if educational methods are developed which are based on other mental abilities besides IQ.