References of "Greiff, Samuel 50001890"
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See detailDiscussant. In Q. Liu (Ed.), Complex problem solving
Greiff, Samuel UL

Scientific Conference (2015, December)

Detailed reference viewed: 81 (3 UL)
See detailNew avenues for educational large-scale assessments. The use of log-file data in PISA
Greiff, Samuel UL; Avvisati, F.

Scientific Conference (2015, December)

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See detailValidating the PISA 2015 collaborative problem solving approach
Herborn, Katharina UL; Mustafic, Maida UL; Greiff, Samuel UL

Presentation (2015, November 04)

Detailed reference viewed: 119 (37 UL)
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See detailNeed for Cognition bei Kindern und Jugendlichen: Korrelate und Zusammenhänge mit Intelligenz und schulischer Leistung
Strobel, Anja; Luong, Cäcilia; Greiff, Samuel UL et al

Scientific Conference (2015, September)

Detailed reference viewed: 47 (2 UL)
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See detailATC21S and OECD PISA. Comparative approaches to the assessment of collaborative problem solving in Germany and Australia
Griffin, P.; Greiff, Samuel UL; Care, E. et al

Scientific Conference (2015, September)

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See detailExamining students’ mathematics attitudes across time: A test of the theory of planned behavior.
Niepel, Christoph UL; Greiff, Samuel UL; Preckel, Franzis et al

Scientific Conference (2015, August)

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See detailAssessment of 21st century skills
Greiff, Samuel UL

Scientific Conference (2015, July)

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See detailThe transversal skills that underlie modern human capital
Greiff, Samuel UL

Scientific Conference (2015, July)

Detailed reference viewed: 35 (3 UL)
See detailMicroDYN and MicroFIN
Herde, Christophe UL; Mustafic, Maida UL; Greiff, Samuel UL

Presentation (2015, June 06)

Detailed reference viewed: 84 (1 UL)
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See detailDeterminants of individual occupational careers in the 21st century. Does complex problem solving matter beyond general mental ability?
Mainert, Jakob UL; Kretzschmar, André UL; Neubert, Jonas UL et al

Scientific Conference (2015, May 21)

Purpose Complex problem solving (CPS) describes the interaction with dynamic and nonroutine tasks, and has been included in PISA 2012 as a factor for employability. This study examines whether CPS can ... [more ▼]

Purpose Complex problem solving (CPS) describes the interaction with dynamic and nonroutine tasks, and has been included in PISA 2012 as a factor for employability. This study examines whether CPS can also contribute to the prediction of career advancement in jobs beyond general mental ability (GMA) as one of the best predictors. Design/Methodology Using latent structural equation modeling (SEM), we analyzed a sample of technicians, service/trade workers, and assemblers (n=245) at a German automotive company. A computer-based assessment measured participants' CPS and GMA levels. The dependent variables were the participants’ job level (ISCO-08) and professional training days. Results CPS and GMA both correlated significantly with career advancement (from .18 to .26, all p < .01). The models showed good fit and indicated that CPS explained incremental variance in one of two indicators (β = .14 for trainings, p < .05; ΔR2 = .02) in comparison with GMA alone (β = .24, p < 0.01; R2= .06). Limitations Analyses did not include processes information from CPS assessment as potential advantage. The company-based sample and cross-sectional data restrict inferences. Research Implications Our findings suggest positive relations between CPS and career advancement even when controlling for GMA. Hence, CPS could be a valuable addition for the study of careers and personnel selection test batteries. Originality/Value The first evaluation of CPS in career research gave a general indication of an as-yet-to-be-defined role of CPS, especially when considering the task characteristics compared to complex and demanding jobs, and process data available through CPS. [less ▲]

Detailed reference viewed: 116 (2 UL)