Trois experiences mettent a l'epreuve un modele prenant en compte les differences dans les capacites cognitives, les processus auto-regulateurs de la motivation et les exigences de traitement de l'information

Motivation and cognitive abilities: an integrative/aptitude-treatment interaction approach to skill acquisition

There appears to be a lack of new ideas in driver behavior modeling. Although behavioral research is under some pressure, it seems too facile to attribute this deplorable state of affairs only to a lack of research funds. In my opinion the causal chain may well run in the opposite direction. An analysis of what is wrong has led me to the conclusion that human factors research in the area of driver behavior has hardly been touched by the “cognitive revolution” that swept psychology in the past fifteen years. A more cognitive approach might seem advisable and the “promise of progress” of such an approach should be assessed.

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A Critical View of Driver Behavior Models: What Do We Know, What Should We Do?

This study provided a meta-analysis of the relationship of the Ohio State leadership behaviors— Consideration and Initiating Structure—with leadership. Overall, 163 independent correlations for Consideration and 159 correlations for Initiating Structure were analyzed. Results revealed that both Consideration (.48) and Initiating Structure (.29) have moderately strong, nonzero relations with leadership outcomes. Consideration was more strongly related to follower satisfaction (leader satisfaction, job satisfaction), motivation, and leader effectiveness, and Initiating Structure was slightly more strongly related to leader job performance and group– organization performance. Validities did vary by leadership measure, but in most cases validities generalized regardless of the measure used. Overall, the results provide important support for the validity of Initiating Structure and Consideration in leadership research.

http://www.timothy-judge.com/Judge,%20Piccolo,%20&%20Ilies%20(JAP%202004).pdf

The forgotten ones? The validity of Consideration and Initiating Structure in leadership research

SUMMARY—Amid ongoing public speculation about the reasons for sex differences in careers in science and mathematics, we present a consensus statement that is based on the best available scientific evidence. Sex differences in science and math achievement and ability are smaller for the mid-range of the abilities distribution than they are for those with the highest levels of achievement and ability. Males are more variable on most measures of quantitative and visuospatial ability, which necessarily results in more males at both high- and low-ability extremes; the reasons why males are often more variable remain elusive. Successful careers in math and science require many types of cognitive abilities. Females tend to excel in verbal abilities, with large differences between females andmalesfound whenassessmentsincludewriting samples. High-level achievement in science and math requires the ability to communicate effectively and comprehend abstract ideas, so the female advantage in writing should be helpful in all academic domains. Males outperform females on most measures of visuospatial abilities, which have been implicated as contributing to sex differences on standardized examsin mathematics and science. An evolutionary account of sex differences in mathematics and science supports the conclusion that, although sex differences in math and science performance have not directly evolved, they could be indirectly related to differences in interests and specific brain and cognitive systems. We review the brain basis for sex differences in science and mathematics, describe consistent effects, and identify numerous possible correlates. Experience alters brain structures and functioning, so causal statements about brain differences and success in math and science are circular. A wide range of sociocultural forces contribute to sex differences in mathematics and science achievement and ability—including the effects of family,neighborhood,peer,andschoolinfluences;training and experience; and cultural practices. We conclude that early experience, biological factors, educational policy, and cultural context affect the number of women and men who pursue advanced study in science and math and that these effects add and interact in complex ways. There are no single or simple answers to the complex questions about sex differences in science and mathematics.

/pdf/the-science-of-sex-differences-in-science-and-mathematics-z189hy1b2o.pdf

The Science of Sex Differences in Science and Mathematics

Determinants of individual differences during skill acquisition: Cognitive abilities and information processing.

Describes the author's research efforts to link basic and applied psychology concepts in each of the following areas: aptitude measurement, learning and training, and human task performance. Several studies are described in detail to illustrate a number of broad issues, particularly the possibility

https://psycnet.apa.org/journals/amp/27/11/1017.pdf

On the relation between abilities, learning, and human performance.

This report reviews and discusses a number of the methodological questions relating to the application of an experimental-correlational approach to the problem of assessing complex performance. The...

Edwin A. Fleishman

Papers

On the relation between abilities, learning, and human performance.

Performance assessment based on an empirically derived task taxonomy.

Development of a behavior taxonomy for describing human tasks: a correlational-experimental approach.

Relationship between leadership patterns and effectiveness ratings among israeli foremen

Attitude versus skill factors in work group productivity.