Occupational attainment as a function of abilities and interests: A longitudinal analysis using Project TALENT data.

Abstract

Ability, interest, gender, and family socioeconomic status of 13,248 tenth-grade participants in Project TALENT were studied as they relate to occupational attainment by using discriminant analysis. Individuals were classified into 12 broad categories reported 11 years after graduation. Accuracy analyses indicated correct classifications significantly above chance for all except the Technical and Sales categories. Within-category classification percentages were higher for all groups except Construction. Five canonical discriminant functions that jointly accounted for 96.8% of the between-groups variance were interpreted. The first 2 accounted for 81.9% of the variance. Function 1 was a general ability function; Function 2 differentiated the categories on the basis of mathematics ability and gender. Functions 3 through 5 accounted for 14.9% of the between-groups variance. Some implications of these findings are discussed.

Intelligence–personality associations reconsidered: The importance of distinguishing between general and narrow dimensions of intelligence

“…Sophisticated sampling and careful instrument development ensure reliable and valid data (see Tiedeman, 1972 for details), making the PT battery well suited for this study, as well as others in the past (e.g., Austin & Hanisch, 1990;Reeve & Hakel, 2000). Descriptive statistics and intercorrelations for the ability and personality scales are shown in Table 2 (for space considerations, descriptive statistics shown are based on the full sample; tables with the data separated by gender are available from the first author).…”

“…Both of which posit that one's "raw" abilities, personality, and conative dispositions work in concert to form "trait complexes." This perspective not only suggests that intelligence and personality are correlated, but also the way in which they are correlated may have a substantive impact on knowledge acquisition (e.g., Reeve & Hakel, 2000), information processing (Matthews, 1999), environment selection (e.g., Austin & Hanisch, 1990;Reeve & Heggestad, 2004) and overall world view (Lubinski, 2004).…”

A Heuristic Framework of Spatial Ability: a Review and Synthesis of Spatial Factor Literature to Support its Translation into STEM Education

“…Project TALENT also included longitudinal data taken 1, 5 and 11 years after graduation from high school (Wise et al 1979). A number of longitudinal studies based on Project TALENT's 11-year follow-up emphasise the importance of spatial ability for accomplishments in STEM disciplines (Austin and Hanisch 1990;Gohm et al 1998;Humphreys et al 1993;Humphreys and Yao 2002). One specific study comparing this data to modern longitudinal findings is especially relevant (Wai et al 2009).…”

Spatial ability: A neglected dimension in talent searches for intellectually precocious youth.

“…Following this reasoning, there is an important sociological corollary to adding spatial reasoning measures to talent identification procedures for intellectually precocious youth: Because the normative correlation between socioeconomic status (SES) and mathematical ability, like SES and verbal ability, is around .40, whereas the normative correlation between SES and spatial ability is around .30 (cf. Austin & Hanisch, 1990), spatial ability measures will identify more students from lower SES levels than do verbal and mathematical abilities currently. attending top U.S. universities-individuals who had already made a commitment to pursue high-level STEM careers.…”