Linking complex problem solving and general mental ability to career advancement: Does a transversal skill reveal incremental predictive validity?

Abstract

Transversal skills, such as complex problem solving (CPS) are viewed as central twenty-first-century skills. Recent empirical findings have already supported the importance of CPS for early academic advancement. We wanted to determine whether CPS could also contribute to the understanding of career advancement later in life. Towards this end, we conducted a study (n = 245) at a large German automobile company in which we predicted career advancement and related criteria with CPS in addition to general mental ability (GMA). A computer-based assessment served as a measure of CPS. The dependent variables were the participants’ job level in accordance with the international standard classification for occupations (ISCO-08) and the number of professional training days as a proxy for lifelong learning efforts. The data were analysed using a structural equation modelling approach. CPS and GMA showed correlations (from .18 to .26, p < .01) with indicators of career advancement. All regression models showed good fit and indicated that CPS explained incremental variance in one of two indicators (β was .14 for trainings, p < .05). Our findings suggest an increment of CPS for predicting career advancement beyond GMA. Hence, CPS could complement GMA in methodologies for the study of professional development.

Keywords:

• complex problem solving
• general mental ability
• career advancement
• lifelong learning
• predictive validity

Acknowledgements

We are grateful to the TBA group at DIPF (http://tba.dipf.de) for providing the authoring tool CBA Item Builder and technical support. We would like to express our gratitude to Zeppelin University, Friedrichshafen, Germany, and in particular to Prof. Dr. Peer Ederer for providing the contact to the participating enterprises, for giving valuable support in data collection, and for making the data available to us. Also of indispensable support in data collection and data preparation was Dr. Sascha Wüstenberg of the University of Luxembourg.

Additional information

Funding

This work was supported by the Fonds National de la Recherche Luxembourg [grant number ATTRACT “ASK21”]; the European Union [grant number 290683; LLLight’in’Europe].

Notes on contributors

Jakob Mainert

Jakob Mainert is research assistant and PhD student at University of Luxembourg since Sept. 2013. He is member of the psychometricians’ team responsible for the assessment of complex problem-solving skills led by ATTRACT research fellow Dr Samuel Greiff.

André Kretzschmar

André Kretzschmar is research assistant and PhD student at the University of Luxembourg since 2012. He is member of the psychometricians’ team responsible for the assessment of complex problem-solving skills led by ATTRACT research fellow Dr Samuel Greiff.

Jonas C. Neubert

Jonas Neubert is research assistant at Brandenburg University of Technology [since 2015] and PhD student at University of Luxembourg since 2012.

Samuel Greiff

Samuel Greiff is research group leader principal investigator, and ATTRACT fellow at University of Luxembourg. He holds a PhD in cognitive and experimental psychology from the University of Heidelberg (passed with distinction).