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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Stability of College Students' Fit with Their Academic Major and the Relationship Between Academic Fit and Occupational Fit

Ghandour, Louma 16 September 2013 (has links)
This study examines the fit between students’ interests and their academic choices at different stages of their college careers. Using image theory (Beach, 1990) as an integrated theory of person-vocation fit, this investigation focuses on the stability of academic fit during college and the relationship between fit with academic choice and fit with occupational choice. Participants, 257 students in their final year at Rice University, responded to questions about their interests as well as factors that may influence their career choices, such as parental support, work centrality, career efficacy, and employment potential. Results showed that students tend to improve their fit with their academic major during their first four semesters. And, students tend to maintain or improve their fit when they select their first occupation after college. Of the factors considered to influence career choices, work centrality, or the importance one places on work, moderated the relationship between academic and occupational fit.
2

Non-ability correlates of the science-math trait complex: searching for personality characteristics and revisiting vocational interests

Toker, Yonca 09 November 2010 (has links)
The trait complex approach (Ackerman&Heggestad, 1997) makes it possible to study the individual holistically by taking account of various individual differences at the same time, such as abilities, personality, motivation, and vocational preferences. Recently, Kanfer, Wolf, Kantrowitz, and Ackerman (2010) provided support for taking a whole-person approach in predicting academic performance. They also showed the incremental role of non-ability predictors over the role of ability predictors. Objectives of the present study were to further explore the non-ability variables of the science/math trait complex. Identifying the personality correlates of the science/math trait complex was the first objective. Investigation results yielded four personality factors as correlates of the complex, which play important roles for engineers and scientists at different stages of the vocational track: toughmindedness was the personality marker of the science/math trait complex and was associated with intending to pursue a STEM career; achievement and control were associated with academic success in STEM majors; and cognitively-oriented behavior was associated with more cognitively challenging pursuits, such as attending STEM competitions and planning to go on to graduate school. The second purpose was to revisit the vocational interests associated with the science/math trait complex and the Science, Technology, Engineering, and Mathematics (STEM) groups. A new measure was introduced, referred to as STEM Interest Complexity, which measures interests towards engaging in increasingly complex tasks in the Numerical, Symbolic, Spatial, and STEM-related Ideas domains. It was developed to assess the level of vocational interests, in addition to the traditionally assessed direction of vocational interests (Holland, 1985). Validation of the new STEM Interest Complexity measure showed adequate construct and concurrent criterion-related validities. Construct validity was established by demonstrating associations between the new measure and measures of the direction of interests, cognitive abilities, intelligence as personality, and learning goal orientations. Support for the new measure's criterion-related validity was found by demonstrating that the measure discriminates between majors, and predicts vocational criteria (i.e., college achievement in STEM, attachment to STEM fields, major satisfaction, and one's intentions to chose a complex STEM career). With dominance analyses, it was shown that STEM Interest Complexity was the most important vocational assessment in the prediction of criteria. Results support the assertion that vocational interest inventories can be improved by incorporating the level of complexity dimension. Finally, a science/math trait complex composite score, including the personality factors and STEM Interest Complexity, in addition to the previously determined ability, interest, and self-concept associates, showed moderate associations with STEM-related vocational criteria. The non-ability individual differences, which were the focus of the present study, added to the conceptualization and predictive utility of the science/math trait complex.

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