ackerman

A long “intellectual” journey

A long “intellectual” journey

The changing nature of work is having a profound impact on the human experience, particularly among older workers. Two integrative theoretical and empirical frameworks of adult development over the past 3 decades provide new insights into aging and work in the 21st century. The first framework focuses on adult intellect and the second on work motivation. We provide a brief review of these frameworks, discuss the implications for reconsidering adult work lives in the context of interindividual differences, intraindividual change, and external forces, and argue for greater attention to individual differences in knowledge, skills, and motivation. Six broad themes, arising from the convergence of theory, research findings, and emerging patterns of work, are proposed as guides for forging new directions on the intellectual and motivational aspects of adult development in the world of 21st century work.

Work in the 21st century: New directions for aging and adult development

This paper is an attempt to provide a brief guide to major conceptual and statistical problems that are unique to the study of individual differences in intelligence and various intellectual abilities, in the context of laboratory experimental studies, and to suggest strategies to successfully navigate these problems. Such studies are generally designed so that the goal is to evaluate the relationships between individual differences in basic task performance or related markers on the one hand, and individual differences in intellectual abilities on the other hand. Issues discussed in this paper include: restriction-of-range in talent, method variance and facet theory; speed vs. power; regression to the mean; extreme-groups designs; difference scores; differences in correlations; significant vs. meaningful correlations; factor- pure tests; and criterion variables. A list of representative “do” and “don’t” recommendations is provided to help guide the design and evaluation of laboratory studies.

A primer on assessing intelligence in laboratory studies

Effort as a concept, whether momentary, sustained, or as a function of different task conditions, is of critical importance to resource theories of attention, fatigue/boredom, workplace motivation, career selection, performance, job incentives, and other applied psychology concerns. Various models of motivation suggest that there is an inverted-U-shaped function describing the personal utility of effort, but there are expected to be individual differences in the optimal levels of effort that also are related to specific domain preferences. The current study assessed the disutility of effort for 125 different tasks/activities and also explored individual differences correlates of task preferences, in a sample of 77 undergraduate participants. The participants rated each activity in terms of the amount of compensation they would require to perform the task for a period of 4 h. They also completed paired comparisons for a subset of 24 items, followed by a set of preference judgments. Multidimensional scaling and preference scaling techniques were used to determine individual differences in task preference. Personality, motivation, and interest traits were shown to be substantially related to task preferences. Implications for understanding which individuals are oriented toward or away from tasks with different effort demands are discussed, along with considerations for the dynamics of attentional effort allocations during task performance.

Subjective (dis)utility of effort: Mentally and physically demanding tasks

The years since World War II have seen remarkable progress in the field of cognitive fatigue. Many fascinating and encouraging lines of research have been explored, including performance effects associated with cognitive fatigue; task characteristics leading to fatigue; feelings, motivational determinants, biological, and neuropsychological aspects of cognitive fatigue; and drug effects on cognitive fatigue. However, in all this time there has been no book-length treatment of cognitive fatigue, and little effort to bring together these diverse research strands into an integrated whole. In this long-awaited book, editor Phillip L. Ackerman has gathered a group of leading experts to assess both basic research and future applications relevant to cognitive fatigue.

Broad in scope, the book covers:
• human factors and ergonomics
• clinical and applied differential psychology
• applications in industrial, military, and non-work domains

A balance of theoretical and empirical research, reviewed from several different countries, makes this a truly multinational and interdisciplinary collection. Each chapter concludes with a lively discussion among authors, and the book itself concludes with a provocative open panel discussion regarding promising avenues for research and application. The result is a book that displays the breadth and the emerging unity of the field of cognitive fatigue today.
2011. 360 pages. Hardcover.

Cognitive Fatigue

“Learning and Individual Differences” spans a diverse range of topics, focusing on those research areas that facilitate the exchange of ideas across different approaches. Research areas covered include experimental, differential, developmental, and instructional/educational psychology as well as the integration of cognitive and differential approaches. Research in each area is placed in its proper historical perspective, giving readers a feel for the processes that lead to scientific advances.

Learning and Individual Differences

Diverse developments in ability and motivation research, and in the derivations of new methodological techniques have often run on parallel courses. The editors of this volume felt that communication across domains could be vastly improved through intensive interaction between researchers. This interaction was realized in The Minnesota Symposium on Learning and Individual Differences, which directly addressed ability, motivation and methodology concerns. This book, compiled as a result of the Symposium, unites theoretical and empirical advances in learning and individual differences.

Abilities Motivation and Methodology

Researchers from the United States and seven other countries present leading-edge research and theory concerning the topic of learning and individual differences, which continues to be a vibrant area for multidisciplinary investigation. Developments in several areas, including cognitive, experimental, instructional, quantitative methodology, and differential psychology provide key insights for understanding both the characteristics of the learner and the characteristics of the learning situation. Of particular value is new research on information processing, ability traits, and knowledge as they pertain to adult learning and individual differences.

Learning and Individual Differences: Process, Trait, and Content Determinants

Space limitations do not allow me to fully address Ericsson’s comments. Instead, I limit mydiscussion to five of the most salient issues upon which there are significant differences in theevaluation of the existing theory, methodological issues, and data. These relate to Ericsson’suse of the construct “innate talent;” his misapplication of Ackerman’s (1987, 1988) theoryof individual differences during skill acquisition; inadequate attention to selection of testsand consideration of Brunswik Symmetry; oversights and misinterpretations in evaluatingthe results from Masunaga and Horn (2001); and differences in interpretations of several otherstudies. In the final analysis, although there has not been a definitive longitudinal study ofdeliberate practicewith randomselection/assignment and a control group, there is ample evidencefromover 100 years of research supporting the conclusion that abilities are significantly related toindividual differences in the attainment of expert performance.

Facts are stubborn things

Controversies surrounding nature and nurture determinants of expert/elite performance havearisen many times since antiquity, and remain sources of concern in the present day. Extremepositions on this controversy are fundamentally silly — both nature and nurture are necessarydeterminants of expert/elite performance, but neither alone represents a sufficient causalfactor. The central issues surrounding the so-called “talent myth” and the “deliberate practicetheory (also referred to as the “10,000 h rule”) are reviewed. Also provided is a discussion ofthe science of individual differences related to talent, the fundamental characteristics of talentand the role of talent in predicting individual differences in expert/elite performance. Finally, areview of the critical psychometric and statistical considerations for the prediction ofindividual differences in the acquisition of expert/elite performance is presented. Conclusionsfocus on how these various issues fit together, to provide an integrated view of the importanceof talent, but also the limitations of talent identification procedures for discovering whichindividuals will ultimately develop expert/elite levels of performance.

Nonsense, common sense, and science of expert performance: Talent and individual differences

Extant measures that purport to assess overclaiming of an individual’s knowledge provide checklistsof real and bogus items, and typically assess overclaiming on the basis of the number of bogus itemsendorsed by the respondents. Such measures have two salient shortcomings. First, the procedurefor selecting foils (e.g., that may sound familiar to respondents) may influence the likelihood ofendorsement — such as the use of ‘attractive distractors.’ Second, real items endorsed by therespondents are not necessarily ‘true’ indicators of the individual’s knowledge, but confoundknowledge with self-enhancement, because there is no assessment of the individual’s actualknowledge. We present a study of overclaiming of vocabulary knowledge that provides a signaldetection theory assessment, including self-claimed knowledge and an objective test of knowledge.Ability, personality, self-concept and other predictorswere assessed, alongwith gender. Self-claimedvocabulary knowledge was highly correlated with objectively assessed knowledge. In contrast toinvestigations without explicit checks on actual knowledge, current results indicated that higherability individuals evidenced slightly greater overclaiming than lower ability individuals.

Vocabulary overclaiming — A complete approach: Ability, personality, self-concept correlates, and gender differences

Traditional approaches to intelligence have mainly evolved from Spearman’s theory of general intelligence, whichviews intelligence as general and fixed, and from applications of Binet’s approach, which views intelligence amongchildren and adolescents as normally increasing with age. The study of adult intellect and intellectual developmentindicates that neither approach well represents the depth and breadth of skills and knowledge that make up the adultintellectual repertoire. A framework for examining individual differences in intellectual development from adolescencethrough middle adulthood is discussed, along with a series of empirical investigations on the ability and non-ability (e.g.,personality, interests, self-concept) determinants of domain knowledge. Implications for understanding intelligenceduring adulthood and college-major choices are discussed from a perspective that combines intelligence as process,personality, and interests as they determine the development of intelligence as knowledge.

Adolescent and Adult Intellectual Development

We investigated the frequency and duration of distractions and media multitasking among college students engaged in a 3-h solitary study/homework session. Participant distractions were assessed with three different kinds of apparatus with increasing levels of potential intrusiveness: remote surveillance cameras, a head-mounted point-of-view video camera, and a mobile eyetracker. No evidence was obtained to indicate that method of assessment impacted multitasking behaviors. On average, students spent 73 min of the session listening to music while studying. In addition, students engaged with an average of 35 distractions of 6 s or longer over the course of 3 h, with an aggregated mean duration of 25 min. Higher homework task motivation and self-efficacy to concentrate on homework were associated with less frequent and shorter duration multitasking behaviors, while greater negative affect was linked to longer duration multitasking behaviors during the session.We discuss the implications of these data for assessment and for understanding the nature of distractions and media multitasking during solitary studying.

What else do college students “do” while studying? An investigation of multitasking

Cognitive or intellectual investment theories propose that the development of intelligence is partially influenced by personality traits, in particular by so-called investment traits that determine when, where, and how people invest their time and effort in their intellect. This investment, in turn, is thought to contribute to individual differences in cognitive growth and the accumulation of knowledge across the life span. We reviewed the psychological literature and identified 34 trait constructs and corresponding scales that refer to intellectual investment. The dispositional constructs were further classified into 8 related trait categories that span the construct space of intellectual investment. Subsequently, we sought to estimate the association between the identified investment traits and indicators of adult intellect, including measures of crystallized intelligence, academic performance (e.g., grade point average), college entry tests, and acquired knowledge. A meta-analysis of 112 studies with 236 coefficients and an overall sample of 60,097 participants indicated that investment traits were mostly positively associated with adult intellect markers. Meta-analytic coefficients ranged considerably, from 0 to .58, with an average estimate of .30. We concluded that investment traits are overall positively related to adult intellect; the strength of investment–intellect associations differs across trait scales and markers of intellect; and investment traits have a diverse, multifaceted nature. The meta-analysis also identified areas of inquiry that are currently lacking in empirical research. Limitations, implications, and future directions are discussed.

Investment and Intellect: A Review and Meta-Analysis

Background/Context: The past few decades have seen an explosive growth in high-school student participation in the Advanced Placement program® (AP), with nearly two million exams completed in 2011. Traditionally, universities have considered AP enrollment as an indicator for predicting academic success during the admission process. However, AP exam performance may be predictive of future academic success; a related factor in gender differences in major selection and success; and instrumental in predicting STEM persistence.

Purpose: This study focused on determining the influence of patterns of AP exam completion and performance on indicators of post-secondary academic achievement. These patterns were examined in the context of gender differences and for the prediction of grades, STEM persistence and graduation rates. Subjects: The sample consisted of 26,693 students who entered the Georgia Institute of Technology (Georgia Tech) as first-year undergraduate students during the period of 1999-2009.

Research Design: Archival admissions records and college transcripts were obtained for entering first-year (non-transfer) students, to examine patterns of AP exams completed and performance on the exams, as they related to indicators of college academic performance, TCR, 115, 100305 Advanced Placement and College Performance 2 BACKGROUND The Advanced Placement program has been in existence since the 1950s (DiYanni, 2009), but the program has markedly changed over time, especially in the past decade. Although the original goals of the program (to allow students to obtain college-level credit for advanced study during high school) have not changed, the program has expanded in scope, from an initial set of 10 exams in core areas of study (e.g., “English composition, literature, Latin, French, German, Spanish, mathematics, biology, chemistry, and physics” [DiYanni, 2009]) to 33 exams that span the original areas, but also other diverse domains such as Art History, Environmental Science, Human Geography, and Macroeconomics. In addition, there has been an explosive growth in the number of AP exams administered, from about 10,000 in 1960 to a half-million exams in 1990, inflow and outflow STEM majors and non-STEM majors, and attrition/time-to-degree criteria. For predicting college performance, patterns of AP exams were examined in isolation, exams grouped by domain, and instances of multiple examinations completed (e.g., three or more AP exams in the STEM area). These patterns of AP exams were evaluated for predictive validity in conjunction with traditional predictors of post-secondary performance (e.g., high-school GPA and SAT scores). College course enrollment patterns were also examined, in conjunction with AP exam patterns, to determine the associations between AP exam performance and course-taking patterns in post-secondary study.

Data Collection and Analysis: Admissions records were obtained from Georgia Tech, including high-school grade point average information, along with college transcripts, including initial and final major declaration, attrition, and graduation data. Course enrollments were classified by level and by domain. Advanced Placement exam and SAT records were obtained from the College Board, and matched to the Georgia Tech records.

Conclusions/Recommendations: Although student completion of AP exams was positively related to post-secondary grades and graduation rates, this overall pattern masks the relation between AP exam performance and post-secondary success. Students who did not receive credit tended to perform at a level similar to those students who did not complete any AP exams. Increasing numbers of AP-based course credits were associated with higher GPAs at Georgia Tech for the first year and beyond. Students with greater numbers of AP-based course credits tended to complete fewer lower-level courses and a greater number of higher-level courses. Such students graduated at a substantially higher rate and in fewer semesters of study. Average AP exam score was the single best predictor of academic success after high school GPA (HSGPA). The most important predictors of STEM major persistence were receiving credit for AP Calculus and if the student had successfully completed three or more AP exams in the STEM areas. Men had substantially higher rates of these AP exam patterns, compared to women. Given that slightly over half of the AP exams are now completed by high school students prior to their senior year, it is recommended that admissions committees consider use of actual AP exam performance data, in addition to, or instead of AP enrollment data as indicators for predicting post-secondary academic performance.

High School Advanced Placement and Student Performance in College: STEM Majors, Non-STEM Majors, and Gender Differences

Prediction of academic success at postsecondary institutions is an enduring issue for educational psychology. Traditional measures of high-school grade point average and high-stakes entrance examinations are valid predictors, especially of 1st-year college grades, yet a large amount of individual-differences variance remains unaccounted for. Studies of individual trait measures (e.g., personality, self-concept, motivation) have supported the potential for broad predictors of academic success, but integration across these approaches has been challenging. The current study tracks 589 undergraduates from their 1st semester through attrition or graduation (up to 8 years beyond their first semester). Based on an integrative trait-complex approach to assessment of cognitive, affective, and conative traits, patterns of facilitative and impeding roles in predicting academic success were predicted. We report on the validity of these broad trait complexes for predicting academic success (grades and attrition rates) in isolation and in the context of traditional predictors and indicators of domain knowledge (Advanced Placement [AP] exams). We also examine gender differences and trait complex by gender interactions for predicting college success and persistence in science, technology, engineering, and math (STEM) fields. Inclusion of trait-complex composite scores and average AP exam scores raised the prediction variance accounted for in college grades to 37%, a marked improvement over traditional prediction measures. Math/Science Self-Concept and Mastery/Organization trait complex profiles were also found to differ between men and women who had initial STEM major intentions but who left STEM for non-STEM majors. Implications for improving selection and identification of students at-risk for attrition are discussed.

Trait Complex, Cognitive Ability, and Domain Knowledge Predictors of Baccalaureate Success, STEM Persistence, and Gender Differences

Intelligence and personality share many common features other than their seminal role in individual differences research. First, they both refer to cognitive, affective, and behavioral differences that are quantifiable through the use of standardized psychometric instruments (Funder, 2001). Second, they are both genetically determined, albeit to different degrees (e.g., Spinath & Johnson, 2011: this volume).

Re-Visiting Intelligence-Personality Associations

(from the chapter) Philosophers (e.g., Kant, 1790) and psychologists traditionally separate traits (i.e., relatively stable and transsituational sources of individual differences) into three major categories: affective, cognitive, and conative traits. Affective traits are personality characteristics (such as need for achievement, neuroticism, conscientiousness). Cognitive traits include traditional concepts of broad abilities (such as intelligence), narrower ability constructs (e.g., verbal comprehension, math ability), and even more narrow abilities and skills (reaction time to simple stimuli and typing speed). Conative or volitional traits include motivation and interests. More generally, conation is characterized as will. For much of the twentieth century, with a few notable exceptions, researchers were typically concerned with only a single category of traits, such as personality or abilities, and there were relatively few studies of the interactions between and interrelations among these different categories of traits. In the last two decades, this kind of isolated research has been augmented by investigations of how these different categories of traits relate to one another. In this chapter, I will briefly review some of these streams of integrative research. First, however, a few general considerations and qualifications are needed.

Personality and cognition

Experimental and statistical methods for examining individual differences in dual-task performance and time-sharing ability are reviewed and criticized. Previous data and analysis procedures are generally inadequate to evaluate a time-sharing ability. Errors resulting from unsophisticated use of correlational and factor analytic procedures are described. Four previous studies that concern time-sharing are considered in detail. The nature of task selection, scoring methods, and control of practice and reliability issues are discussed. Based on a reanalysis of available data, a time-sharing ability is not rejected. Simulation, incorporation of theory in planning models, and crucial tests of the hypotheses are proposed as methods for assessing the time-sharing ability.

Deciding the existence of a time-sharing ability: A combined theoretical and methodological approach

A conceptual theory for predicting the relations between intellectual abilities and performance during task practice is proposed and evaluated. This macro-theory integrates modern hierarchical theories of intellectual abilities with information-processing theories of automatic and controlled processing (Schneider & Shiffrin, 1977) and performance-resource functions (Norman & Bobrow, 1975). An empirical evaluation of the theory is provided from an experiment with high school and college students. Subjects practiced for several hours on verbal and spatial memory tasks with consistent and varied information-processing manipulations. Derived correlations between ability factors and task performance measures indicate support for the theory and support for linkage of the concepts of intellectual abilities and attentional resources.

Individual differences in information processing: An investigation of intellectual abilities and task performance during practice

In this article, I reexamine the nature of individual differences in novel and practiced performance on skill learning tasks from an information processing framework that incorporates concepts derived from automatic and controlled information processing and attentional resources perspectives. I also use developments in quantitative analysis procedures to approach previous data in a single, unbiased framework for evaluation. Two major sources of data and discussion are reanalyzed and critically evaluated. One source concerns the changes in interindividual between-subjects variability with task practice. The other main source of data and theory pertains to associations between intellectual abilities and task performance during skill acquisition. Early studies of practice and variability yielded mixed results regarding the convergence or divergence of individual differences with practice. Other studies regarding intelligence and skill learning indicated small or trivial correlations between individual differences in intelligence and “gain” scores. More recent studies indicated small correlations between performance measures on skill learning tasks and standard intellectual and cognitive ability measures, as well as increasing amounts of task-specific variance over learning trials. On the basis of this reanalysis and reexamination, these data confirm the proposition that individuals converge on performance as tasks become less dependent on attentional resources with practice. Further, it is determined that when appropriate methodological techniques are used and crucial task characteristics are taken into account, intellectual abilities play a substantial part in determining individual differences in skill learning.

Individual differences in skill learning: An integration of psychometric and information processing perspectives

Interactions of stimulus consistency and type of responding were examined during perceptual learning.  Subjects performed hybrid memory-visual search tasks over extended consistent and varied mapping practice.  Response conditions required subjects to respond to both the presence and absence of a target, only when a target was present or only when a target was not present.  After training, the subjects were transferred to a different response condition.  The results indicate that: (1) performance on search tasks with stimuli that are variably mapped show no qualitative changes attributable to manipulation of response format; (2) improvement due to consistent mapping (CM) practice is attenuated in the no-only response condition; (3) yes-only CM training attenuates the subjects’ ability to transfer to no-only responding; and (4) yes/no CM training leads to the greatest improvement and transfer when compared with other responding conditions.  The practice and transfer data support and extend previous research investigation effects of response set in memory/visual search and help to delineate factors that facilitate or inhibit reduction of load effects in memory and visual search.

Effects of type of responding on memory/visual search: Responding just “yes” or just “no” can lead to inflexible performance

An integrative theory that links general models of skill acquisition with ability determinants of individual differences in performance is presented. Three major patterns of individual differences during skill acquisition are considered: changes in between-subjects variability, the simplex pattern of trial intercorrelations, and changing ability-performance correlations with practice. In addition to a review of previous theory and data, eight experimental manipulations are used to evaluate the cognitive ability demands associated with different levels of information-processing complexity and consistency. Subjects practiced category word search, spatial figure, and choice reaction time tasks over several hundred trials of task practice. An air traffic controller simulation was used to show generalization to a complex task. Examinations of practice-related between-subjects variance changes and ability-performance correlations are used to demonstrate that an equivalence exists between three broad phases of skill acquisition and three cognitive-intellectual determinants of individual differences.

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

Two central constructs of applied psychology, motivation and cognitive ability, were integrated within an information-processing framework. This theoretical framework simultaneously considers individual differences in cognitive abilities, self-regulatory processes of motivation, and information-processing demands. Evidence for the framework is provided in the context of skill acquisition, in which information-processing and ability demands change as a f function of practice, training paradigm, and timing of goal setting. Three field-based lab experiments were conducted with 1,010 U.S. Air Forces trainees. In Experiment 1 the basic ability-performance parameters of the air traffic controller task and goal-setting effects early in practice were evaluated. In Experiment 2 goal setting later in practice was examined. In Experiment 3 the simultaneous effects of training content, goal setting, and ability-performance interactions were investigated. Results support the theoretical framework and have implications for notions of ability-motivation interactions and design of training and motivation programs.

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

Recently, there has been increased interest in the role of stable individual differences in so-called personal constructs (e.g. motivation, affect) as determinants of work performance.  This study examines: (1) parent-child resemblance in achievement motivation and locus of control, and (2) generational differences in these variables using the WOFO and I-E scales.  Results offer convincing evidence for the lack of direct relationship between parent achievement motivation and locus of control on child ratings for these scales.  The results are discussed in light of the importance of discovering the antecedents of achievement motivation and locus of control dispositions, especially as they affect behavior in the workplace.

Generational differences and parent-child resemblance in achievement motives and locus of control: A cross-sectional analysis

>Recent discussion by Henry and Hulin (1987) about the implications of stability and change in skilled performance are questioned on several counts. First, the presentation reflects an inadequate review of previous data pertaining to the influences of skill acquisition on ability-performance covariance. Furthermore, the authors made untenable assumptions that equate ability with job sample measures. Their conclusions about universal decline in predictive validity coefficients are inconsistent with both theory and data in the literature. As a result, misleading generalizations were made to other issues in the prediction of individual differences. This article notes deviations from historical literature and outlines the problems of this approach. Discussion of theoretical frameworks for predicting individual differences in skill acquisition and skilled performance is also presented, along with an overview of data in support of these frameworks. The conclusions reached differ from those of Henry and Hulin, lead to different interpretations of past research and practice, and propose very different directions for future research.

Within-task intercorrelations of skilled performance: Implications for predicting individual differences?

Skill specificity, the notion that task performance is based on unique underlying information-processing components at skilled levels of performance, is examined from the perspective of the ability determinants of individual differences in task performance during skill acquisition. The current investigation uses a dynamic ability-skill theoretical perspective to evaluate how individual differences in procedural learning for a complex criterion task relate to learning of procedures for other more basic tasks such as choice and simple reaction time. An experiment with 86 college students was performed using a simulated Air Traffic Controller (ATC) task for assessment of procedural learning, along with practice on several perceptual speed measures and assessment of reference abilities. When subjects are allowed to practice tests of perceptual speed and psychomotor ability, some measures increase in their power to predict skilled performance on the complex ATC criterion task, a direct disconfirmation of the skill-specificity thesis. Discussion is devoted to the use of individual-differences approaches to address general transfer and skill specificity issues.

A correlational analysis of skill specificity: Learning, abilities, and individual differences

Relations between personality and intelligence were investigated in the context of the distinction between intelligence as typical engagement and intelligence as maximal engagement. The traditional approach to investigating the association between intelligence as maximal performance and personality was reviewed, and suggestions were made, including the suggestion that intelligence as typical engagement and related to typical intellectual performance were operationalized. Relations found were modest, yet several personality scales differentially related to fluid and crystallized classes of intelligence. Relations between the personality constructs surrounding typical intellectual engagement and the broad personality domain are investigated.

Personality-intelligence relations: Assessing typical intellectual engagement

Substantial controversy exists about ability determinants of individual differences in performance during and subsequent to skill acquisition. This investigation addresses the controversy. An information-processing examination of ability-performance relations during complex task acquisition is described. Included are ability testing (including general, reasoning, spatial, perceptual speed, and perceptual/psychomotor abilities) and skill acquisition over practice on the terminal radar approach controller simulation. Results validate and extend Ackerman’s (1988) theory of cognitive ability determinants of individual differences in skill acquisition. Benefits of ability component and task component analyses over global analyses of ability-skill relations are demonstrated. Implications are discussed for selection instruments to predict air traffic controller success and for other tasks with inconsistent information-processing demands.

Predicting individual differences in complex skill acquisition: Dynamics of ability determinants

An example of combining laboratory-and field-based study to develop a selection battery for field implementation s described. The procedure provides advantages in comparison with sole use of construct validity data, and fewer field demands for cross-validation. Two experiments were conducted that converge on development of a test battery for selection of air traffic controllers (ATCs). The laboratory study (N=112) used an ATC simulator (terminal radar approach control, or TRACON) for initial development and evaluation of the selection battery. The field study of 206 Federal Aviation Administration ATC trainees provided cross-validation data as a precursor to implementation of the battery. Implications for developing ability-based and self efficacy-based selection measures for complex job performance are discussed, as are general issues for new election research and application.

Integrating laboratory and field study for improving selection: Development of a battery for predicting air traffic controller success

Hypotheses regarding the influence of goal assignments on performance of a novel, complex task under varying conditions of practice were derived from a cognitive resource allocation model. Goals and type of practice interacted in their effects on two key performance measures. In the massed-practice conditions, trainees assigned specific, difficult goals tended to perform poorer than trainees in the control (do your best goal) condition. In the spaced-practice conditions, goal trainees performed marginally better than control trainees. Self-report measures of goal commitment, and on-task, off-task, and affective thoughts during breaks and task performance provide additional evidence for the independent and interactive effects of goals and practice conditions on motivation and performance. Results provide further support for the resource allocation framework. Implications for research and practice are discussed.

Goal Setting, Conditions of practice, and task performance: A resource allocation perspective

T. Rocklin (1994) examined the relations between our (M. Goff & P.L. Ackerman, 1992) measure of Typical Intellectual Engagement (TIE) and a personality test measure of Openness. We examine Rocklin’s arguments in the context of three themes: philosophical issues, TIE and Openness from a facet perspective, and the bandwidth-fidelity dilemma. Although Rocklin raised important issues about these constructs, we demonstrate that measures of TIE and Openness, although significantly related, are theoretically and empirically distinguishable.

Typical intellectual engagement and personality: Reply to Rocklin (1994)

The way that cognitive abilities, learning task characteristics, and motivational and volitional processes combine to explain individual differences in performance and learning was investigated. A substitution task was studied over practice, and it was discovered that students used strategy in which students persisted in scanning items. Five experiments investigated strategy differences and the ability and motivational correlates of task performance. First, ability correlates of performance and strategy use were demonstrated. Next, reducing task difficulty increased use of the learning strategy. With periodic memory tests, effective reliance on the learning strategy was increased, and task performance correlations with reasoning ability were lowered. Finally, a combination of self-focus and goal-setting interventions increased both general performance levels and use of the learning strategy. Results are discussed in terms of the goal of developing a more comprehensive understanding of learner differences.

Determinants of learning and performance in an associative memory/substitution task: Task constraints, individual differences, and volition

Integration of multiple perspectives on the determinants of individual differences in skill acquisition is provided by examination of a wide array of predictors: ability (spatial, verbal, mathematical, and perceptual speed), personality (neuroticism, extroversion, openness, conscientiousness, and agreeableness), vocational interests (realistic and investigative), self-estimates of ability, self-concept, motivational skills, and task-specific self-efficacy. Ninety-three trainees were studied over the course of 15 hr (across 2 weeks) of skill acquisition practice on a complex, air traffic controller simulation task (Terminal Radar Approach Controller; TRACON; Wesson International; Austin, TX). Across task practice, measures of self-efficacy, and negative and positive motivational thought occurrence were collected to examine prediction of later performance and communality with pretask measures. Results demonstrate independent and interactive influences of ability tests and self-report measures in predicting training task performance. Implications for the selection process are discusses in terms of communalities observed in the predictor space.

Cognitive and noncognitive determinants and consequences of complex skill acquisition

An individual-differences approach to social competence is presented. People generated a large number of operational indicators of social competence. The dimensions that underlie those indicators were then determined. Seven interpretable dimensions of social competence were identified, each with a distinct pattern of correlations with personality and cognitive ability variables. Major personality dimensions are closely related to social competence, whereas cognitive ability (as operationalized by academic performance indicators) is less related to social competence. A profile approach to social competence is proposed because (a) social competence is a compound trait, all of whose dimensions do not covary, and (b) some social competence dimensions may be curvilinear such that, after an ideal point has been reached, higher standing on the dimension may hinder rather than enhance socially competent performance.

To "act wisely in human relations:" Exploring the dimensions of social competence. Personality and Individual Differences

The authors describe an approach to adult intellect on the basis of content, unlike the traditional approach, which is mostly based on process. Thirty-two academic knowledge scales were rated by 202 college students, who also completed ability, vocational interest, and personality scales. Analyses of knowledge clusters and individual scales were used to evaluate commonality across ability constructs (verbal and spatial ability), vocational interests (realistic, investigative, and artistic), and personality (typical intellectual engagement and openness). The results support knowledge differentiation across fluid and crystallized abilities, show a pattern of positive correlations of arts and humanities knowledge with typical intellectual engagement and openness, and show correlations between math and physical sciences knowledge and realistic and investigative interests. Implications for the study of adult intelligence are discussed.

Self-report knowledge: At the crossroads of ability, interest, and personality

This article has 2 goals: first, to present and test a hierarchical representation of personality that jointly incorporates both situational and personality (e.g., Big Five) factors into a trait conception, and second, to explicate the dimensions along which situations differ in their effect on responses, providing the conceptual and empirical groundwork for the development of a joint taxonomy of traits and situations. A study of the effects of situational differences on trait self-reports indicated that conscientiousness and agreeableness can be represented hierarchically, with lower levels jointly constrained by both personality content and situational breadth. This representation establishes a methodological framework allowing for the explanation of the ways that situations interact with personality to affect responses. Implications of this representation for personality theory and prediction to and from personality inventories are discussed.

Towards an interactionist taxonomy of personality and situations: An integrative situational-dispositional representation of personality traits

We report a series of investigations that focus on the nature of motivational skills and self-regulation for learning as traits, in contrast to consideration of self-regulation as resulting from particular interventions. In this context, we consider how self-report measures of motivational and self-regulation skills relate to other traits, such as ability, personality, interests, academic self-concept, self-ratings of abilities. In addition, we discuss how such trait measures are associated with task-specific self efficacy across tasks of varying complexity-from simple and information processing to complex air traffic controller tasks. Self-regulatory and motivational skills show substantial overlap with other trait measures, as do measures of learning strategies. Motivational and domain-specific self-concepts, along with trait anxiety, appear to be strongly related to task-specific self-efficacy.

Motivational skills & self-regulation for learning: A trait perspective

The issues of skill specificity and transfer of training were examined from an aptitude-treatment interaction approach. The current investigations extended A.M. Sullivan’s (1964) approach by using a procedural transfer task and training conditions that differed in the amount of training task practiced and the degree of training task similarity to the transfer task. Tow experiments were conducted with 232 college students. Experiment 1 examined the effects of a length-of -training manipulation on reasoning ability and transfer task performance relationships, and on the amount of transfer. Experiment 2 evaluated the effects of 2 training tasks that differed in terms of similarity to the transfer task on ability-performance relationships and the amount of transfer. Results suggest that Sullivan’s approach partially generalizes to the acquisition of procedural knowledge.

An aptitude-treatment interaction approach to transfer within training

The development of adult intelligence assessment early in this century as an upward extension of the Binet-Simon approach to child intelligence assessment is briefly reviewed. Problems with the use of IQ measures for adults are described, along with a discussion of related conceptualizations of adult intellectual performance. Prior intelligence theories that considered adult intelligence (Cattell, 1943, 1971/1987; Hebb, 1941, 1942, 1949; Vernon, 1950) are reviewed. Based on extensions of prior theory and new analyses of personality-ability and interest-ability relations, a developmental theory of adult intelligence is proposed, called PPIK. The PPIK theory of adult intellectual development integrates intelligence-as-process, personality, interests, and intelligence-as-knowledge. Data from the study of knowledge structures are examined in the context of the theory, and in relation to measures of content abilities (spatial and verbal abilities). New directions for the future of research on adult intellect are discussed in light of an approach that integrates personality, interests, process, and knowledge.

A theory of adult intellectual development: process, personality, interests, and knowledge

Evaluation of overlap among correlational construct families provides a basis for cross-fertilization in each of the four separate individual-differences domains. This article provides some new insights on Thorndike’s claim that superiority in one trait implies superiority in other traits. Definitions and methodological differences among correlational domains of inquiry are reviewed from modern investigations of personality, self-concept, interests, and intelligence. Sources of overlap between personality and other trait families are discussed and four trait complexes are reviewed: social, clerical/conventional, science/math, and intellectual/cultural. Implications of the trait-complex approach and challenges to integrative research approaches to applied problems are presented.

Personality, self-concept, interests, and intelligence: Which construct doesn’t fit?

The authors review the development of the modern paradigm for intelligence assessment and application and consider the differentiation between intelligence-as-maximal performance and intelligent-as-typical performance. They review theories of intelligence, personality, and interest as a means to establish potential overlap. Consideration of intelligence-as-typical performance provides a basis for evaluation of intelligence – personality and intelligence – interest relations. Evaluation of relations among personality constructs, vocational interests, and intellectual abilities provides evidence for communality across the domains of personality of J. L. Holland’s (1959) model of vocational interests. The authors provide an extensive meta-analysis of personality – intellectual ability correlations, and a review of interests – intellectual ability associations. They identify 4 trait complexes: social, clerical/conventional, science/math, and intellectual/cultural.

Intelligence, personality, and interests: Evidence for overlapping traits

Twenty academic knowledge tests were developed to locate domain knowledge within a nomological network of traits. Spatial, numerical, and verbal aptitude measures and personality and interest measures were administered to 141 undergraduates. Domain knowledge factored along curricular lines; a general knowledge factor accounted for about half of knowledge variance. Domain knowledge exhibited positive relations with general intelligence (g), verbal abilities after g was removed, Opennes, Typical Intellectual engagement, and specific vocational interests. Spatial and numerical abilities were unrelated to knowledge beyond g. Extraversion related negatively to all knowledge domains. Results provide broad support for R.B. Cattell’s (1971/1987) crystallized intelligence as something more than verbal abilities and specific support for P.L. Ackerman’s (1996) intelligence-as-process, personality, interests, and intelligence-as-knowledge theory of adult intelligence.

Assessing individual differences in knowledge: Knowledge structures and traits

Some intelligence theorists (e.g., R. B. Cattell, 1943; D. O. Hebb, 1942) have suggested that knowledge is one aspect of human intelligence that is well preserved or increases during adult development.  Very little is known about knowledge structures across different domains or about how individual differences in knowledge relate to other traits.  Twenty academic and technology-oriented tests were administered to 135 middle-aged adults.  In comparison with younger college students, the middle-aged adults knew more about nearly all of the various knowledge domains.  Knowledge was partly predicted by general intelligence, by crystallized abilities, and by personality, interest, and self-concept.  Implications of this work are discussed in the context of a developmental theory that focuses on the acquisition and maintenance of intelligence-as-knowledge, as well as the role of knowledge for predicting the vocational and avocational task performance of adults.

The locus of adult intelligence: Knowledge, abilities, and nonability traits

Assessment of psychomotor abilities for prediction of human performance is briefly reviewed. Reasons for the abandonment of psychomotor testing for section applications are described. We review innovation in touch-sensitive computer monitors as a methodology for relatively low-cost, highly flexible test development, validation, and application of standard psychomotor tests. The development and evaluation of 5 psychomotor test types are described including discrete response tests (choice-simple reaction time [RT], serial RT, and tapping) and continuous-response tests (maze tracing and mirror tracing). Two empirical studies of the new psychomotor tests are presented, with a broad array of perceptual speed and cognitive abilities providing evidence for construct validity. In addition, some of the psychomotor tests are validated against a real-time simulation criterion (the Kanfer-Ackerman Air Traffic Controller Task). We argue that these new innovations provide a means toward revisiting psychomotor testing to augment employee section batteries.

Psychomotor abilities via touch-panel testing: Measurement innovations, construct, and criterion validity

Empirical evidence on the conceptual and construct validity of the motivational trait taxonomy proposed by Kanfer and Heggestad is presented. 228 adults completed a shortened form of the Motivational Trait Questionnaire (MTQ), along with a battery of personality and ability measures. Relationships of the MTQ with personality measures show evidence of convergent and discriminant validity for trait constructs of Personal Mastery, Competitive Excellence, and Motivation Related to Anxiety. In addition, MTQ scale scores were generally unrelated to composite measures of fluid and crystallized intelligence. Examination of age differences showed a pattern of developmental decline in the achievement trait complex, but not the anxiety complex.

Individual differences in work motivation: Further explorations of a trait framework

The prediction of individual differences in skilled performance has been a source of substantial theory and empirical research over the past 100 years. Developments in the statistical evaluation of individual differences data, and progress in the investigation of a wide range of human abilities (such as general, perceptual speed, and psychomotor abilities) have contributed to a better understanding of the role of ability in the acquisition of skills. This article presents a reappraisal of the theoretical and empirical approaches to questions regarding the ability determinants of skilled performance, describes progress that has been made, and discusses enduring problems and future challenges.

A reappraisal of the ability determinants of individual differences in skilled performance

An enduring controversy in intelligence theory and assessment, the argument that middle-aged adults are, on average, less intelligent than young adults, is addressed in this study. A sample of 228 educated adults between ages 21 and 62 years was given an array of tests that focused on a broad assessment of intelligence-as-knowledge, traditional estimates of fluid intelligence (Gf) and crystallized intelligence (Gc), personality, and interests. The results indicate that middle-aged adults are more knowledgeable in many domains, compared with your adults. A coherent pattern of ability, personality, and interest relations is found. The results are consistent with a developmental perspective of intelligence that includes both traditional ability and non-ability determinants of intelligence during adulthood. A reassessment of the nature of intelligence in adulthood is provided, in the context of lifelong learning and investment model, called PPIK, for intelligence-as-Process, Personality, Interests, and intelligence-as-Knowledge (Ackerman, 1996).

Domain-specific knowledge as the "dark matter" of adult intelligence: gf/gc, personality and interest correlates

Examined gender differences in the overlooked context of individual adoption and sustained usage of technology in the workplace using the theory of planned behavior. User reactions and technology usage behavior were studied over a 5-mo period among 355 workers being introduced to a new software technology application. When compared to women’s decisions, the decisions of men were more strongly influenced by their attitude toward using the new technology. In contrast, women were more strongly influenced by subjective norm and perceived behavioral control. Sustained technology usage behavior was driven by early usage behavior, thus fortifying the lasting influence of gender-based early evaluations of the new technology. These findings were robust across income, organization position, education, and computer self-efficacy levels.

A longitudinal field investigation of gender differences in individual technology adoption decision making processes

An attempt is made to reconcile two historically important tools for the assessment of intelligence and the prediction of academic achievement with extant theories of verbal-crystallized-knowledge aspects of adult abilities. A study of 167 adults (aged 18-69 yrs) reasserts the importance of individual differences in completion test and cloze test performance in accounting for both measures of crystallized intelligence (Gc) and four scales of knowledge (biology, US history, US literature, and technology). The completion tests were found to account for all of the variance in Gc and knowledge that the cloze tests accounted for, and resulted in incremental predictive validity for both domains. In addition, completion and cloze tests were found to have a suppressor effect on the relationship between Gc and Age. We note that C. Spearman’s (1927) assertion, namely that the completion test had higher correlations with intelligence than any other measure. Our results suggest that abstract reasoning may be far less useful in predicting learning and performance than the completion test is.

Explorations of crystallized intelligence: Completion tests, cloze tests and knowledge

The authors describe a series of experiments that explore 3 major ability determinants of individual differences in skill acquisition in the context of prior theory (e.g., P. L. Ackerman, 1988) and subsequent empirical and theoretical research. Experiment 1 assessed the predictability of individual differences in asymptotic skill levels on the Kanfer-Ackerman Air Traffic Controller (ATC) task. Experiment 2 provided an exploration of the construct space underlying perceptual-speed abilities. Experiment 3 concerned an evaluation of theoretical predictions for individual differences in performance over skill development in a complex air traffic control simulation task (TRACON) and the ATC task, with an extensive battery of general and perceptual-speed measures, along with a newly developed PC-based suite of psychomotor ability measures. Evidence addressing the predictability of individual differences in performance at early, intermediate, and asymptotic levels of practice is presented.

Cognitive, perceptual speed, and psychomotor determinants of individual differences during skill acquisition

This study expanded the scope of knowledge typically included in intellectual assessment to incorporate domains of current-events knowledge from the 1930s to the 1990s across the areas of art/humanities, politics/economics, popular culture, and nature/science/technology.  Results indicated that age of participants was significantly and positively related to knowledge about current events.  Moreover, fluid intelligence was a less effective predictor of knowledge levels than was crystallized intelligence.  Personality (i.e., Openness to Experience) and self-concept were also positively related to current-events knowledge.  The results are consistent with an investment theory of adult intellect, which views development as an ongoing outcome of the combined influences of intelligence-as-process, personality, and interests, leading to intelligence-as-knowledge

Current-events knowledge in adults: An investigation of age, intelligence, and nonability determinants

The authors investigated the abilities, self-concept, personality, interest, motivational traits, and other determinants of knowledge across physical sciences/technology, biology/psychology, humanities, and civics domains.  Tests and self-report measures were administered to 320 university freshmen.  Crystallized intelligence was a better predictor than was fluid intelligence for most knowledge domains.  Gender differences favoring men were found for most knowledge domains.  Accounting for intelligence reduced the gender influence in predicting knowledge differences.  Inclusion of nonability predictors further reduced the variance accounted for by gender.  Analysis of Advanced Placement test scores largely supported the results of the knowledge tests.  Results are consistent with theoretical predictions that development of intellect as knowledge results from investment of cognitive resources, which, in turn, is affected by a small set of trait complexes.

Determinants of individual differences and gender differences in knowledge

It has become fashionable to equate constructs of working memory (WM) and general intelligence (g). Few investigations have provided direct evidence that WM and g measures yield similar ordering of individuals. Correlational investigations have yielded mixed results. The authors assess the construct space for WM and g and demonstrate that WM shares substantial variance with perceptual speed (PS) constructs. Thirty-six ability tests representing verbal, numerical, spatial, and PS abilities; the Raven Advanced Progressive Matrices; and 7 WM tests were administered to 135 adults. A nomological representation for WM is provided through a series of cognitive and PS ability models. Construct overlap between PS and WM is further investigated with attention to complexity, processing differences, and practice effects.

Individual differences in working memory within a nomological network of cognitive and perceptual speed abilities

Previous research on basic information processing tasks has suggested that there may be a dissociation between the underlying process determinants of task performance and associations with ability measures. The current study investigates this dissociation in the context of a complex skill learning task — an air traffic control simulation called TRACON. A battery of spatial, numerical, and perceptual speed ability tests was administered, along with extensive task practice. After practice, manipulations of task requirements and system consistency were introduced. Ability correlations with performance revealed a dissociation between some manipulations that have effects on performance means and the corresponding correlations with reference abilities. Implications for integrating experimental and differential approaches to explaining performance, and possible avenues for improved selection measures are discussed.

Ability and task constraint determinants of complex task performance

Recent research has only documented the experimental side of the scientific divide (which focuses on means and ignores individual differences) regarding what individuals know about their abilities and knowledge level. The current paper shows that research from the other side of the scientific divide, namely the correlational approach (which focuses on individual differences), provides a very different perspective for people’s views of their own intellectual abilities and knowledge. Previous research is reviewed, and an empirical study of 228 adults (aged 21-62 yrs) is described where self-report assessments of abilities and knowledge are compared with objective measures. Correlations of self-rating and objective-score pairings show both substantial convergent and discriminant validity, indicating that individuals have both generally accurate and differentiated views of their relative standing on abilities and knowledge.

What we really know about our abilities and our knowledge

Ten areas of health knowledge were investigated in 2 studies, 1 of college students (N=169) and 1 of adults from the community (ages 19-70; N=176). Measures assessed knowledge of aging, orthopedic/ dermatological concerns, common illnesses, childhood/early life, serious illnesses, mental health, nutrition, reproduction, safety, and treatment of illness/disease. Significant gender differences favoring women were found for most areas of health knowledge, especially reproduction and early life. Results showed that cognitive ability accounted for the most variance in health knowledge with nonability (personality and interest traits) and demographic variables accounting for smaller but significant amounts of variance across most knowledge domains.

Determinants of health knowledge: An investigation of age, gender, abilities, personality, and interests

Historically, many researchers have considered the domains of intellectual abilities, personality, and interests to be both distince and distant from one another. Recent meta-analytic reviews and new empirical research suggest that there are fundamental communalities among particular measures of cognition, affect, and conation. These communalities, in turn, yield a relatively small set of trait complexes – groups of traits that are related to one another and that appear to be differentially related to career choices and adult intellectual development. Derivation of trait complexes is described; empirical data on trait complexes, career choice, and domain-specific knowledge are reviewed; and implications for developments in vocational and educational couseling are suggested.

Intelligence, personality, and interests in the career choice process

Traditional approaches to understanding individual differences determinants of domain-specific expertise have focused on individual trait components, such as ability or topic interest. In contrast, trait complex approaches consider whether combinations of cognitive, affective, and conative traits are particularly facilitative or impeding of the development of domain knowledge. This article reviews an investment theory and empirical research concerning a relatively small set of trait complexes that appear to be instrumental correlates of both individual and group differences in expertise across several academic domains. Implications for academic counseling and instructional interventions are discussed.

Cognitive ability and non-ability trait determinants of expertise

The origins and development of the concept of aptitude complexes are reviewed. Initial empirical success in demonstrating interactions between aptitude complexes and instructional complexes by Richard E. Snow and his students are followed by an inductive approach to finding broader trait complexes. Three empirical studies of college students and adults up to age 62 are described, where trait complexes were correlated with domain knowledge and ability measures. Differentiated profiles of trait complex-knowledge-ability correlations were found and replicated across the three studies. Evidence for trait complexes that are supportive or impeding for the development of domain knowledge is reviewed. The aptitude complex/trait complex approach is viewed as important means toward reseraching and reevaluating the nature of aptitude-treatment interactions.

Aptitude complexes and trait complexes

We describe a framework for understanding how age-related changes in adult development affect work motivation, and, building on recent life-span theories and research on cognitive abilites, personality, affect, vocational interests, values, and self-concept, identify four intraindiviual change trajectories (loss, gain, reorganization, and exchange). We discuess implications of the integrative framework for the use and affectivesness of different motivational strategies with midlife and older workers in a varity of jobs, as well as abiding issues and future research directions.

Aging, adult development, and work motivation

This paper examines the relationship between span memory [e.g., immediate memory, short-term memory (STM), simple span] and general ability (g) though a reanalysis of two data sets [Christal, R. E. (1959). Factor analytic study of visual memory. Psychological Monographs: General and Applied, 72 (13, Whole No. 466); (see record 1959-09796-001); Kelley, H.P. (1964). Memory abilities: A factor analysis. Psychometric Monographs, No. 11]. Because of their large sample sizes and the multiple measures used to identify each construct, the Christal and Kelley studies were examined within a “best evidence synthesis” framework. Modern structural equation modeling (SEM) techniques were used to examine the relationship between immediate memory and g. Results indicated that in both studies, the relationship between immediate memory and g was quite substantial (.71 and .83), and that this relationship was essentially reduced by half when the common content variance of the tests was accounted for (e.g., verbal, spatial, numerical). Results are discussed within the context of recent research examining the relationship between working memory (WM) and g.

A reappraisal of the relationship between span memory and intelligence via "best evidence synthesis."

Aspects of the Ackerman and Heggestad (1997) meta-analysis were updated and expanded to address the complex, contradictory findings of the extraversion–intelligence relation. Although the estimated effect sizes in the current study remained slightly positive, there was a decrease in the magnitude of the effect across extraversion–intelligence pairs in comparison to the 1997 meta-analytic results. Correlations between the date of publication of the study and the observed extraversion–intelligence correlations were generally negative, which suggested a change in the magnitude of the extraversion–intelligence relation over time. Furthermore, the estimated effect size between extraversion and intelligence for studies conducted in the year 2000 and later was (p < .05), indicating that not only has the magnitude of the correlation decreased, but also that the direction of the correlation has changed from positive to slightly negative. Trends associated with two potential moderator variables are also discussed: the use of different measures and the average age of the samples.

Extraversion and intelligence: A meta-analytic investigation.

The authors address agreements and disagreements with the M. J. Kane, D. Z. Hambrick, and A. R. A. Conway (2005; see record 2004-22408-004) and K. Oberauer, R. Schulze, O. Wilhelm, and H.-M. Süß (2005; see record 2004-22408-003) commentaries on P. L. Ackerman, M. E. Beier, and M. O. Boyle (2005; see record 2004-22408-002). They discuss the following issues: (a) the relationship between working memory (WM) and general intelligence (g), (b) the reanalyses included in the comments, (c) the use of a fixed-effects model versus a random-effects model for the meta-analysis, (d) the use of structural equation modeling analyses and structural coefficients as equivocal evidence for the relationship between WM and intelligence, and (e) the problem of confirmation bias in research on WM. Although the authors disagree with their commentators about the magnitude of the relationship between WM and g, in the final analysis it appears that all concerned parties agree that WM and intelligence are different constructs.

Working memory and intelligence: Different constructs

At the most fundamental level, the relationship between intelligence and learning is close and convincing. Indeed, the modern era of intelligence assessment is identified with the critical success of Binet and Simon (1905) in their development of a set of scales that provided valid predictions of school success. These scales, or similar assessments inspired by this approach (such as the Wechsler Intelligence Scale for Children; Wechsler, 1949), continue to represent the best predictors of school success. School success, at least for children and adolescents, is considered by many to be the indicator of learning achievement. While this analysis works quite well for global measures of learning, there is far less utility of omnibus IQ-type measures for predicting individual differences in narrower domains of learning. If we want to predict which students will excel in learning a musical instrument, mastering power tools, or becoming adept at a particular sport, or even which students will become the fastest typists, the relationship between intelligence and learning appears to be much more complicated.

Part of the reason why IQ-type measures are less valid for predicting individual differences in skilled performance has to do with the relative “bandwidth” of the assessment instrument and the breadth of the criterion, or what has been referred to as a lack of Brunswik symmetry (Wittmann & Süß, 1999). That is, IQ tests have high bandwidth — they are typically constructed from as many as a dozen different scales (e.g., memory, reasoning, vocabulary, math, etc.).

Ability determinants of individual differences in skilled performance

Prior knowledge, fluid intelligence (Gf), and crystallized intelligence (Gc) were investigated as predictors of learning new information about cardiovascular disease and xerography with a sample of 199 adults (19 to 68 years). The learning environment included a laboratory multimedia presentation (high-constraint-maximal effort), and a self-directed at-home study component (low-constraint-typical performance). Results indicated that prior knowledge and ability were important predictors of knowledge acquision for learning.Gc was directly related to learning from the video for both domains. Because the trajectory of Gc stays relativley stable throughout the life span, these findings provide a more optimistic perspective on the relationship between aging and learning than that offered by theroies that focus on the role of fluid abilities in learning.

Age, ability and the role of prior knowledge on the acquisition of new domain knowledge

Several investigators have claimed over the past decade that working memory (WM) and general intelligence (g) are identical, or nearly identical, constructs, from an individual-differences perspective. Although memory measures are commonly included in intelligence tests, and memory abilities are included in theories of intelligence, the identity between WM and intelligence has not been evaluated comprehensively. The authors conducted a meta-analysis of 86 samples that relate WM to intelligence. The average correlation between true-score estimates of WM and g is substantially less than unity (p=0.479). The authors also focus on the distinction between short-term memory and WM with respect to intelligence with a supplemental meta-analysis. The authors discuss how consideration of psychometric and theoretical perspectives better informs the discussion of WM-intelligence relations.

Working Memory and intelligence: The same or different constructs?

Comments on the original article “Sex Differences in Intrinsic Aptitude for Mathematics and Science?: A Critical Review,” by E. S. Spelke (see record 2005-15840-001). Spelke considered “three claims that cognitive sex differences account for the differential representation of men and women in high-level careers in mathematics and science.” The focus of this comment is on the claim regarding gender differences in mean levels of cognitive abilities. Spelke claimed (p. 954) that “most investigators of sex differences have concluded that males and females have equal cognitive ability, with somewhat different profiles.” There are two major components to this comment. The first is mainly theoretical, and the second is both theoretical and empirical.

Cognitive sex differences and mathematics and science achievement

The incremental validity of the Typical Intellectual Engagement (TIE) scale as a predictor of academic performance (AP) was tested over and above other established determinants of AP, namely, psychometric g (as extracted from 5 cognitive ability tests) and the Big Five personality traits, assessed by the Neuroticism-Extraversion-Openness Five Factor Inventory. One hundred four British students were tested on arrival to university, and AP measures were collected longitudinally throughout a 3-year period. TIE, g, and Conscientiousness were the highest correlates of AP. A series of multiple-hierarchical regressions showed that TIE had significant incremental validity (over and above g and the Big Five) in the prediction of AP. Implications are discussed in light of the investment theory of intellectual competence and the utility of self-report inventories as predictors of academic achievement.

Incremental validity of typical intellectual engagement as predictor of different academic performance measures

The ability (fluid and crystallized intelligence) and nonability (personality, interests, self-concept, etc.) determinants of domain knowledge before and after an independent learning opportunity were evaluated in the context of a study of 141 adults between the ages of 18 and 69. The domain knowledge under consideration included an array of financial issues, including financial planning, retirement planning, debt management, and educational savings accounts. Crystallized intelligence was a stronger predictor than fluid intelligence of domain knowledge prior to learning, and nonability traits provided significant incremental predictive validity. After learning, fluid intelligence showed a marked increase in the prediction of domain knowledge, but the final correlation did not exceed that of crystallized intelligence. Implications for optimizing the prediction of educational success of adults are discussed.

Determinants of domain knowledge and independent study learning in an adult sample

The relationship of general knowledge (GK) with ability (IQ and abstract reasoning) and personality (Big Five traits and Typical Intellectual Engagement [TIE]) was investigated in a sample of 201 British university students. As predicted, GK was positively correlated with cognitive ability (more so with IQ [r=.46] than with abstract reasoning [r=.37]), TIE (r=.36) and Openness to Experience (r=.16), and negatively related to Neuroticism (r=-.18) and Extraversion (r=-.16). A total of 26% of GK variance was explained by measures of intelligence, though personality traits (particularly Neuroticism and Extraversion) showed incremental validity (5%) in the prediction of GK. Applied and theoretical implications are discussed.

Ability and personality correlates of general knowledge

Skilled performance, whether it involves rapid and accurate motor movements (such as playing a video game or using a scalpel in the operating room) or a high degree of domain knowledge (such as finding a small tumor in an X-ray or writing a journal article) typically involves learning and practice over an extended period of time. In light of recent theory and empirical research, I consider two enduring issues associated with skill acquisition: whether individuals become more alike in performance or more different over the course of skill acquisition, and what the determinants of individual differences in skilled performance are. Two broad classes of tasks are considered: tasks that involve speed and accuracy of motor movements and tasks that primarily involve domain knowledge. Issues of practice, ability, and other determinants of skilled performance such as gender and aging are discussed.

New developments in understanding skilled performance

During my term as editor of JEP: Applied, I have been very impressed with the quality and scope of the papers that have been submitted to the journal. I consider myself fortunate to have been able to work with the many authors who have submitted papers for publication in the journal. That said, the job of the editor is much more frequently associated with giving bad news to authors than it is to giving good news. With this in mind, I would like to review some of the enduring issues that have come up in reviewing the several hundred papers submitted during my tenure as editor of JEP: Applied. It is my hope that consideration of these issues will make it possible for authors to have a better conception of what constitutes building a bridge between science and application.

Bridging science and application

Dr. Geary presents an impressive framework for the evolutionary aspects of abilities and their implications for education. While there is much positive to take from this work, there are a few major concerns about the basis for both the underlying theoretical and empirical justification of the framework, and there are some concerns about whether this framework provides any new insights into the content and conduct of the educational enterprise.

Knowledge, abilities, and will

(from the chapter) The term aptitude, according to most dictionaries, is derived from the Latin term aptitudo, meaning fitness. The psychological use of the term is similar in that it has traditionally referred to a potential for acquiring knowledge or skill. Traditionally, aptitudes are described as sets of characteristics that relate to an individual’s ability to acquire knowledge or skills in the context of some training or educational program. There are two important aspects of aptitude to keep in mind. First, aptitudes are present conditions (i.e., existing at the time they are measured). Second, there is nothing inherent in the concept of aptitudes that says whether they are inherited or acquired or represent some combination of heredity and environmental influences. Also, aptitude tests do not directly assess an individual’s future success; they are meant to assess aspects of the individual that are indicators of future success. That is, these measures are used to provide a probability estimate of an individual’s success in a particular training or educational program. While the meaning of aptitude is well delineated, there is much controversy over how to distinguish aptitude tests from other kinds of psychometric measures, specifically intelligence and achievement tests, partly because the major salient difference between intelligence, aptitude, and achievement tests has to do with the purpose of testing rather than with the content of the tests. What makes an assessment instrument an aptitude test rather than an intelligence or achievement test is mainly the future orientation of the predictions to be made from the test scores.

Aptitude Tests

Measures of perceptual speed ability have been shown to be an important part of assessment batteries for predicting performance on tasks and jobs that require a high level of speed and accuracy. However, traditional measures of perceptual speed ability sometimes have limited cost-effectiveness because of the requirements for administration and scoring of paper-and-pencil tests. There have also been concerns about the validity of previous computer approaches to administering perceptual speed tests (e.g., see Mead & Drasgow, 1993). The authors developed two sets of computerized perceptual speed tests, with touch-sensitive monitors, that were designed to parallel several paper-and-pencil tests. The reliability and validity of the tests were explored across three empirical studies (N = 167, 160, and 117, respectively). The final study included two criterion tasks with 4.67 and 10 hours of time-on-task practice, respectively. Results indicated that these new measures provide both high levels of reliability and substantial validity for performance on the two skill-learning tasks. Implications for research and application for computerized perceptual speed tests and are discussed.

Further explorations of perceptual speed abilities, in the context of assessment methods, cognitive abilities and individual differences during skill acquisition

The relationship between abilities and skill acquisition has been the subject of numerous controversies in psychology. However,while most researchers implicitly or explicitly accept the idea that abilities and skill acquisition should be related, empirical research has failed to provide evidence for a consistently strong correlation between the two constructs. Based on the reanalysis of a study on skill acquisition using the air traffic controller task TRACON [Ackerman, P. L., Kanfer, R., and Goff, M. (1995).Cognitive and Noncognitive Determinants and Consequences of Complex Skill Acquisition. Journal of Experimental Psychology. Applied, 1(4), 270–304], it will be shown how latent growth curve modeling can help to gain a better understanding of the relationship between human abilities and skill acquisition. A brief introduction into the basic concepts of latent growth curve modeling will be given, particularly with regard to the advantages for the analysis of skill acquisition and its determinants. The goal is thereby to provide evidence for a much closer association than commonly assumed and to offer a new, differential, perspective formerly obscured by traditional between-subject analyses.

Abilities and skill acquisition: A latent growth curve approach

Standard statistics texts indicate that the expected value of the F ratio is 1.0 (more precisely: N/(N-2)) in a completely balanced fixed-effects ANOVA, when the null hypothesis is true. Even though some authors suggest that the null hypothesis is rarely true in practice (e.g., Meehl, 1990), F ratios < 1.0 are reported quite frequently in the literature. However, standard effect size statistics (e.g., Cohen’s f) often yield positive values when F < 1.0, which appears to create confusion about the meaningfulness of effect size statistics when the null hypothesis may be true. Given the repeated emphasis on reporting effect sizes, it is shown that in the face of F < 1.0 it is misleading to only report sample effect size estimates as often recommended. Causes of F ratios < 1.0 are reviewed, illustrated by a short simulation study. The calculation and interpretation of corrected and uncorrected effect size statistics under these conditions are discussed. Computing adjusted measures of association strength and incorporating effect size confidence intervals are helpful in an effort to reduce confusion surrounding results when sample sizes are small. Detailed recommendations are directed to authors, journal editors, and reviewers.

Effect sizes and F-ratios below 1.0: Sense or nonsense

(from the chapter) The goal of this chapter is to examine the linkages between applied cognitive psychology and personnel selection and to provide an overview of personnel selection. However, personnel selection is a broad field and includes the treatment of non-ability traits such as personality, motivational states, vocational interests, applicant reactions to selection systems, and so on. Because we aim to focus on ability and selection, an in-depth treatment of these aspects of personnel selection is outside of the scope of this chapter, the interested reader is referred to Schmitt and Chan (1998) and Guion (1998), who provide comprehensive overviews of the field of personnel selection.

Cognitive abilities in personnel selection and testing

How accurate are self-estimates of cognitive abilities? An investigation of verbal, math, and spatial abilities is reported with a battery of parallel objective tests of abilities. Self-estimates were obtained prior to and after objective ability testing (without test feedback) in order to examine whether self-estimates change after direct objective testing experience. Self-estimates showed small to large effect-size correlations with objective tests–larger for math and smaller for verbal. The construct space of self-estimates of abilities was explored in the context of self-concept, self-esteem, self-efficacy, personality, interests, motivational traits, and trait complexes. Self-efficacy and self-esteem variables showed the highest correlations with self-estimates of abilities. In general, trait complexes showed the highest correlations with verbal ability self-estimates and the lowest correlations with math ability self-estimates. Results are discussed in relation to the principle of aggregation, the influences of self-evaluative judgements, and uses for self-estimates of abilities measures.

Determinants and validity of self-estimates of abilities and self-concept measures

(from the chapter) After Ryle (1949/2000), experimental and cognitive psychologists traditionally parse the nature of knowledge into two forms–declarative knowledge (or knowing that) and procedural knowledge (knowing how). However, it has been argued (e.g., Polanyi, 1966/1983) that there is a third type of knowledge called “tacit” knowledge, that is not well incorporated by these former two types of knowledge. Broudy (1977) for example, has claimed that this form of knowledge, which he referred to as “knowing with,” is an especially important aspect of an individual’s knowledge base; it is of particular interest in terms of what the individual learns in school, and what the individual can bring to bear on novel problems. A more precise description of these types of knowledge should be the first order of business.

Knowledge and cognitive aging

(from the chapter) In developed countries around the World such as Germany, Japan, the United Kingdom, and the United States, midlife (aged 45-65) and older (aged 65 and older) persons represent the fastest growing segments of the active workforce. Several factors contribute to this trend. Although mean age of retirement has declined by about 5 years over the past 5 decades, the rapid rise of life expectancy (by about 7 years over the same period) means that there is a much larger population of older individuals. In addition, recent changes in economic conditions, advances in health care, and significant shifts in sociocultural attitudes toward work and associated legislation have encouraged more individuals to engage in paid work well into their 7th decade of life. At the same time, low birthrates during the late 20th century and longer periods of educational training have contributed to a decline in the number of available younger workers, particularly in positions that require extensive training or work experience. As a practical consequence of these trends, organizations, of necessity, have focused increasing attention on midlife and older workers and on age-related influences on motivation, performance, and productivity. In response, a small but growing number of organizational scholars have examined the effects of aging and an age-diverse workforce for the development of a diverse array of human resource functions including the attraction, training, management, and retention of older workers. The purpose of this chapter is to provide an overview of age-related influences on work motivation and its outcomes. In the first section, we provide a brief overview of the key constructs and mechanisms involved in work motivation. In the second section, we discuss two major sources of age-related influences on motivation: (a) social-contextual influences and (b) changes in person characteristics over the life span. In the third section, we discuss four age-related change patterns in person attributes that influence key determinants of motivation and performance. In the fourth section, we consider indirect influences on motivation associated with age bias in managerial decision making and worker perceptions of age discrimination. In the fifth and final section, we describe how age-related factors may influence workplace motivation, and we describe implications of theory and research for the development of effective practices to sustain and promote work motivation in an aging workforce.

Aging and work motivation

The SAT® has changed in several ways over the eight decades that it has been administered to college-bound high school students, including changes in both content and format (for a review, see Lawrence, Rigol, Van Essen, and Jackson, 2002). The original test administered in 1926 contained both verbal and mathematics content and was highly speeded, with a total time limit of 97 minutes. Subsequent modifications and additions to the SAT have resulted in testing times ranging from 120 to 180 minutes. Prior to the most recent revision in 2005, the SAT involved 180 minutes (3 hours) of testing across a total session of about 3½ hours (to accommodate instructions, short breaks, and administration time). In 2005, the most recent significant change in both content and format has been the introduction of an essay section and some modifications in the other sections (e.g., the elimination of verbal analogy items). The addition of the essay section has resulted in an SAT test that involves 225 minutes (3 hours, 45 minutes) of total test time spread over a period of about 4½ hours (that includes instructions, short breaks, and administration time). Examinees arrive at the place of testing before 8 a.m. to check in, and do not complete the SAT session until approximately 12:30 p.m. The high-stakes nature of the test, coupled with the increased total testing time, has resulted in speculation from a variety of sources, especially in the popular press (e.g., FairTest, 2006; FOXNews.com, 2006; Hildebrand, 2007; Lewin, 2005; MacDonald, 2005) that (a) performance on the SAT is negatively affected by the additional testing time; (b) examinee fatigue increases as a function of the increased total testing time; and, by implication, (c) that examinee fatigue is an influential factor in performance on the SAT. The current study was designed to examine performance effects and fatigue effects associated with different total SAT testing times. In addition, we examined personality, motivation, and other determinants of individual differences in examinee fatigue before, during, and after testing.

Effects of total SAT test time on performance and fatigue

Cattell set out a set of conditions for how one might ‘distinguish’ among ‘modalities of traits’, which he referred to as ‘dynamic’ ‘temperament’ and ‘abilities’. Cattell made the most fundamental point that analysis of any single behavior will not, in and of itself, allow one to infer the influence of a unique trait, because each behavior varies, to a greater or lesser extent, as a function of all three different trait domains. Cattell argued that by the integration of experimental psychology methods (e.g. by presenting the individuals with a constant task, but different incentives), one could use the associations between different tests and the recently developed tools of factor analysis, to reveal the underlying hypothetical motivational construct factor or factors. Similarly, he argued that one could reveal ability factors by changing the complexity of the test. Finally, he proposed that personality factors could be revealed only by exclusion—these traits could be identified by their resistance to changes in the other two domains (incentives and test complexity).

On weaving personality into a tapestry of traits

In any discussion of personality and intelligence, it must be acknowledged that the traditional conditions for assessment of these two domains are quite different. On the one hand, as Cronbach (1949) noted, personality traits are assessed by asking an individual how he or she ‘typically’ behaves; that is, to assess a personality trait like Extroversion, the individual might be asked to agree or disagree with a statement like ‘I enjoy going to parties’. In other words, the traditional goal of personality assessment is to determine how an individual would behave when there is little or no environmental press on his/her behaviour (i.e., weak situations). Part of the rationale that underlies this approach is that the variability in behaviour across different individuals is expected to be much more restricted when the environmental press or situation is a strong one. For example, if a group of randomly-selected individuals were each offered US $1,000,000 (a strong environmental press) to jump out of an airplane with a parachute (and a spare), one might reasonably predict that a substantial majority of the group would ‘jump’ at the opportunity. In contrast, if the same group of individuals were simply offered the chance to skydive without any monetary incentive (a weak environmental press), one might reasonably predict that there would be relatively few individuals who agree to jump, and furthermore, that an assessment of personality characteristics such as thrill-seeking might provide a good prediction of which individuals are more or less likely to jump. Therefore, the domain for personality is perhaps best thought of as a tendency to behave in a certain way, especially when there is only a weak environmental press. Intellectual abilities, on the other hand, are traditionally assessed under ‘maximal’ performance conditions; that is, the individual being assessed is not asked to complete an ability test as if there were no environmental press. In fact, the key concept to most modern ability assessments is that the individual needs to either internalize or be provided with explicit instructions to treat the test as if performing well was a highly valued goal (Ackerman 1996). In selection contexts (whether for occupational or educational purposes), where the goal is to get the job or to be admitted into a desirable school, the environmental press for maximal performance is very strong — indeed, in some cases, the test situation may lead to anxiety or subjective distress because the press is so strong that it may distract the individual from performing his/her best. Ultimately the goal of ability assessment is not to determine how the individual behaves when there is no environmental press, but rather determine the limits of the individual’s performance if he/she is trying as hard as possible to succeed. This difference between the traditional approaches to personality and intelligence assessments sets the stage for a mismatch of constructs, in a manner that would be expected to minimize the associations between the two constructs (see e.g., Wittmann and Süß 1999). However, there is no inherent reason why one cannot consider personality in a maximal performance context, such as when one asks whether individuals are capable of public speaking, regardless of whether they might prefer staying home with a cold compress over the eyes to getting up to talk in front of a large group of people (e.g., see Wallace 1966; Willerman, Turner and Peterson 1976). Similarly, intelligence can be considered in a typical behaviour context (see e.g., Ackerman 1994 for a discussion of this issue). In later discussion, a construct of ‘typical intellectual engagement’ will be discussed in some detail.

Personality and intelligence

Person and situational determinants of cognitive ability test performance and subjective reactions were examined in the context of tests with different time-on-task requirements. Two hundred thirty-nine first-year university students participated in a within-participant experiment, with completely counterbalanced treatment conditions and test forms. Participants completed three test sessions of different length: (a) a standard-length SAT test battery (total time 41⁄2 hr), (b) a shorter SAT test battery (total time 31⁄2 hr), and (c) a longer SAT test battery (total time 51⁄2 hr). Consistent with expectations, subjective fatigue increased with increasing time-on-task. However, mean performance increased in the longer test length conditions, compared with the shorter test length condition. Individual differences in personality/interest/motivation trait complexes were found to have greater power than the test-length situations for predicting subjective cognitive fatigue before, during, and at the end of each test session. The relative contributions of traits and time-on-task for cognitive fatigue are discussed, along with implications for research and practice.

Test length and cognitive fatigue: an empirical examination of performance effects and examinee reactions

Students (n = 328) from US and UK universities completed four self-report measures related to intellectual competence: typical intellectual engagement (TIE), openness to experience, self-assessed intelligence (SAI), and learning approaches. Confirmatory data reduction was used to examine the structure of TIE and supported five major factors: reading and information seeking, intellectual avoidance, directed complex problem solving, abstract thinking, and intellectual pursuits as a primary focus. These factors were significantly and positively associated with deep learning, openness, and SAI, and negatively related to surface learning. Other correlates of TIE were more factor-dependent. In general, correlations suggested that TIE is related to, but different from, the other intellectual competence constructs examined. Results are discussed in relation to the typical performance approach to intelligence and the importance of TIE with regards to the intrinsic motivation to learn.

Typical intellectual engagement as a byproduct of openness, learning approaches, and self-assessed intelligence

(from the chapter) How long a period can an individual put forth maximal effort before there are negative behavioral consequences, attitudinal consequences, or both? Objective assessments of some aspects of physical fatigue have been possible since the development of the ergograph in the late 1800s by Mosso (e.g., see Mosso, 1906). The ergograph provides a record of muscular contractions, for example, when the individual repeatedly lifts a weight. Even in the case of muscular fatigue, however, it was clear to Mosso (1906) that numerous factors result in changes in patterns of fatigue, including arousal effects, time-of-day differences, motivational aspects of social facilitation, and so on. Mental or cognitive effort is clearly different from physical effort, in character, physiological activity, and time scale. The research literature on cognitive fatigue makes it clear that maximal cognitive effort can be sustained for a period longer than the few minutes that maximal physical effort can be maintained. In this chapter, I review a variety of issues that are central for considerations of cognitive fatigue in their historical and modern context. Topics to be treated include how performance aspects of cognitive fatigue are assessed, along with the myriad of task characteristics and situational characteristics that have been identified as contributing factors to cognitive fatigue. In addition, I review major theories of the mechanisms and processes that underlie the development and expression of cognitive fatigue in terms of performance and subjective fatigue. Finally, I present an integrated conceptual model of fatigue that addresses both performance and subjective fatigue. I also propose a heuristic framework of the major sources of fatigue and their probable loci of effects.

100 Years without Resting

The hallmark characteristics of well-learned skills are that they tend to be fast and accurate and can often be performed with little attentional effort. Normal adults have countless numbers of such skills, ranging in complexity from very simple (e.g., brushing one’s teeth) to relatively complex (e.g., reading a novel). In the absence of such skills, the process of getting from one’s bed to work would be an exhausting and error-prone challenge. The question of how people acquire skills has been central to psychology for more than 100 years. For many intents and purposes, though, it is useful to separate two different kinds of knowledge and skills. Ryle (1949/2000) suggested that there are fundamental differences between procedural knowledge and declarative knowledge. Procedural knowledge is described as ”knowing how,” and declarative knowledge is defined as “knowing that.”

Skill acquisition

The Advanced Placement® (AP®) program represents a highly sought-after set of opportunities for accelerated study among talented high school students. However, little is known about the ingredients for success in the AP programs beyond some general information regarding student aptitudes and abilities. One central question is whether individual differences in personality, interest, and motivational traits can be used in combination to predict individual differences in success on an AP test. The ultimate practical aim of this research is to develop a brief self-assessment instrument that can be used by various stakeholders (e.g., students, parents, teachers, and counselors) to provide an efficient and accurate prediction of future AP test performance, from measures administered prior to course enrollment, so that students and AP courses can be more optimally matched. The other issue addressed in this research was to examine how personal traits related to the student self-perceptions during the AP course, namely: how stressed the students felt about the course, how conident they were about their performance in the course, their self-efficacy for good AP test performance, and their perceived preparation for the AP Exam. To address these questions, this study involved an assessment of a small set of key cognitive, affective, and conative trait complexes and a set of monthly questionnaires of student behaviors, attitudes, and self-evaluations in a sample of 128 students enrolled in AP Biology courses, across IO different high schools, during 2007-2008 academic year. Evidence was found for changes in students perceptions and attitudes during the academic year, but also evidence was found for substantial consistency of individual differences in the same measures. In the final analysis, three variables were found, such that when combined, provided an excellent prediction of AP Biology Exam performance. These variables were student cumulative grade point average (GPA), student interest in Biology, and student self-efficacy for AP Biology Exam performance.

Trait and process determinants of Advanced Placement test performance

We investigated the training effects and transfer effects associated with 2 approaches to cognitive activities (so-called brain training) that might mitigate age-related cognitive decline. A sample of 78 adults between the ages of 50 and 71 completed 20 one-hr training sessions with the Nintendo Wii Big Brain Academy software over the course of 1 month and, in a second month, completed 20 one-hr reading sessions with articles on 4 different current topics (order of assignment was counterbalanced for the participants). An extensive battery of cognitive and perceptual speed ability measures was administered before and after each month of cognitive training activities, along with a battery of domain-knowledge tests. Results indicated substantial improvements on the Wii tasks, somewhat less improvement on the domain knowledge tests, and practice-related improvements on 6 of the 10 ability tests. However, there was no significant transfer of training from either the Wii practice or the reading tasks to measures of cognitive and perceptual speed abilities. Implications for these findings are discussed in terms of adult intellectual development and maintenance.

Use it or lose it? Wii brain exercise practice and reading for domain knowledge

What are the consequences of testing over an extended period? We report a study of 4 hr of nearly continuous testing on two verbal tests (Cloze and Completion). Prior to the testing session, participants completed a series of nonability trait measures, including selected personality and motivation scales. During the study, participants (N = 99) were also administered a series of subjective fatigue and affect measures. We examined the effect of increasing time-on-task on performance and subjective fatigue, along with the relative influences of trait measures in predicting individual differences in subjective fatigue as time-on-task increased. In addition, we examined whether performance strategy differences were associated with either performance or subjective fatigue measures. Results indicated a dissociation between subjective fatigue (increasing over time-on-task) and performance measures (which were stable or showed slight improvements as time-on-task increased). Trait complexes accounted for significant amounts of variance in subjective fatigue and positive affect over the course of the test session. Performance strategies of overactivity, withdrawal, and mixed overactivity and withdrawal were identified, and correlates of the strategies were examined. Implications for analyzing performance strategies to evaluate reactions to cognitive fatigue, and the prediction of individual differences in cognitive fatigue during testing are discussed.

Cognitive fatigue during testing: An examination of trait, time-on-task, and strategy influences

A battery of cognitive ability, knowledge, and non-ability measures were administered to 105 college students enrolled in a cooperative school-work program and used to predict academic and job performance. Composite scores for each domain were derived from factor analyses of 11 measures of verbal, numerical, and spatial abilities, four measures of domain knowledge, and 27 measures of personality and motivational traits, vocational interests, and self-assessments. Both ability and non-ability trait composites were significant predictors of academic performance, but only the non-ability trait composites predicted job performance. Implications for the integrative assessment of individual differences and their predictive validities for performance in different active work contexts, as well as the importance of trait composites across contexts, are discussed.

Ability and trait complex predictors of academic and job performance: A person-situation approach

When people choose a particular occupation, they presumably make an implicit judgment that they will perform well on a job at some point in the future, typically after extensive education and/or on-the-job experience. Research on learning and skill acquisition has pointed to a power law of practice, where large gains in performance come early in practice, with diminishing returns with greater experience. However, it is not clear whether young adults understand the nature of job learning and performance over time. In the current study, 153 university students were provided with job descriptions and video clips for 20 different jobs. They were asked to estimate the shape of their learning curves for each job, and to provide judgments of their performance levels from the first day on the job to a point after six months of job experience. We investigated the patterns of expected learning/performance curves, and explored the role of personality, interests, self-concept, self-estimates of abilities, entity/incremental theories of intelligence, and gender in prediction of the patterns of expected curves. Participants generally expected a power function or a linear function of improvement across the jobs, with notable differences in anticipated performance depending on job characteristics of gender dominance, ability demands, and interest themes. Traits and job engagement variables provided significant predictive power for accounting for individual differences in expected job performance over time. Implications for implicit theories of intelligence and occupational choice are discussed.

Subjective estimates of job performance after job preview: Determinants of anticipated learning curves

Personality, time of day, and day of the week were assessed as predictors of state fatigue. After completing an in-lab questionnaire, 172 participants (N = 172) reported their state subjective fatigue three times a day for 8 days. Trait neuroticism, conscientiousness, positive affect, and negative affect were predictive of aggregate state subjective fatigue at different points in the day and over the course of the study. Results indicated mean differences in subjective fatigue at different points in the day and week. Personality traits displayed incremental validity over time and day in predicting subjective fatigue states. Multilevel analyses demonstrated that personality traits have an impact on both between individual and within individual sources of state fatigue variance. The relative contribution of personality traits to state subjective fatigue is discussed.

The relative impact of trait and temporal determinants of subjective fatigue

This chapter discusses intelligence and expertise, beginning with definition of terms, followed by historical and current notions of crystallized intelligence, methods of study in individual differences in expertise, acquisition of expertise, expert short/long memory, to what degree fluid intellectual skills are a limiting factor, maintenance of expertise, and tacit knowledge expertise. The study of intelligence and expertise is a much more recent focus for researchers than is the study of, say, intelligence and academic performance. Nonetheless, based on research from experimental psychology that has focused on understanding the development and expression of expertise, and a small number of studies that have examined individual differences in expertise, a relatively consistent pattern of results has been found.

Intelligence and expertise

This chapter discusses intelligence and expertise, beginning with definition of terms, followed by historical and current notions of crystallized intelligence, methods of study in individual differences in expertise, acquisition of expertise, expert short/long memory, to what degree fluid intellectual skills are a limiting factor, maintenance of expertise, and tacit knowledge expertise. The study of intelligence and expertise is a much more recent focus for researchers than is the study of, say, intelligence and academic performance. Nonetheless, based on research from experimental psychology that has focused on understanding the development and expression of expertise, and a small number of studies that have examined individual differences in expertise, a relatively consistent pattern of results has been found.

Intelligence and expertise

Comments on an article by C. A. Scherbaum et al. (see record 2012-12566-002). Scherbaum et al. have aptly noted many challenges facing industrial–organizational (I-O) psychology in the consideration of modern research on intelligence. Yet, the source of the problems they identified is present in the title and first line of their abstract. Namely, the implication that “intelligence” is the same thing as “g” or “general mental ability.” As noted by the authors, g is typically considered to represent the source of common variance among ability measures. In addition to examining the contributions of other areas of psychology to the study of intelligence, we implore I-O psychologists to study the rich history of applied research in intelligence and intellectual abilities that took place before validity generalization effectively put an end to new sources of inquiry. Intelligence assessment and applications have a rich history in I-O psychology since the early part of the twentieth century, and there remains much progress that can be made by considering where the field has been in moving forward. Finally, do not be afraid to try something new. Aspects of I-O psychology are much like engineering. One can derive a satisficing solution to many engineering problems by referring to extant textbook knowledge, but this is not the source of innovation or notable progress.

The problem is in the definition: g and Intelligence in I-O Psychology

(from the chapter) From an individual-differences perspective in psychology, a complex represents some combination of traits (i.e., relative stable individual characteristics) that share common variance. That is, a complex would represent two or more characteristics of individuals that are found to “go together” in the sense that they are positively correlated with one another. The term “aptitude complex” was developed by Snow (1963) in the context of a hypothesis that specific combinations of abilities might be “particularly appropriate or inappropriate for efficient learning.”

Aptitude-trait complexes

(from the chapter) Fatigue can be decisively defined for physical materials because the resulting failure from fatigue is typically preceded by dislocations and deformations that can be observed with the proper tools. For humans, physical fatigue can also be indexed with physiological measurements, as first identified by Mosso (1906). In contrast, psychological fatigue, whether identified as “mental” or “cognitive” fatigue, can be revealed in a variety of ways that are often uncorrelated or only minimally correlated with one another. The most obvious domain where one would want to identify cognitive fatigue is for criteria of task performance. Direct methods of measuring cognitive fatigue often involve examining patterns of performance over time on-task (eg. Noll, 1932; Thorndike, 1926). The problem with such measures is that they are also affected by other factors, such as learning or inhibition, that are often associated with increasing time on-task, making the delineation of fatigue from other factors problematic. Another method for assessing cognitive fatigue is to ask the individuals who are performing the task to report subjective feelings of fatigue. The extant research base of measures for assessing fatigue is substantial (eg. Chalder et al., 1993; Hockey, Maule, Clough & Bdzola, 2000; Michielsen et al., 2004), and the consensus of this research is that there are several dimensions of subjective experience that are related to fatigue. However, none of these dimensions are unequivocally identifiable as fatigue, independent of other factors. For the current chapter, we will include both performance effects and subjective ratings of fatigue as indicators of cognitive fatigue.