Moderators of learning and performance trajectories in microworld simulations: Too soon to give up on intellect!?

Birney, D.P.; Beckmann, J.F.; Beckmann, N.; Double, K.S.; Whittingham, K.

Abstract

The burgeoning increase in the importance given to non-cognitive factors in complex decisions making, has led to calls to question intelligence as the primary explanatory model of success. Features of a business microworld simulation were experimentally manipulated to investigate the incremental value of 20 cognitive and non-cognitive predictors of learning and performance trajectories. Using a combined experimental-differential paradigm and mixed-level modelling, it was predicted that of these, facilitating personality traits (e.g., openness and extraversion), growth/motivational mindsets (e.g., learning goals, need for cognition, and beliefs of malleability), and tentatively, emotion-regulation (e.g., managing and facilitating emotions) would moderate the impact of microworld complexity and experience on performance. Results from 142 experienced business managers replicate the pervasive importance of general and domain-specific reasoning. Contrary to expectations, of the 16 non-cognitive factors investigated, only three mindset variables showed incremental value, and only performance-goal orientations moderated effects above reasoning. These findings give prima facie reason to question the purported importance of conative factors, over and above intellect. However, rather than discount non-cognitive factors entirely, our analyses suggest that with refinement, microworlds and mixed-level modelling may well-support the experimental methods needed to understand moderators of real-world problem solving.

Citation

Birney, D., Beckmann, J., Beckmann, N., Double, K., & Whittingham, K. (2018). Moderators of learning and performance trajectories in microworld simulations: Too soon to give up on intellect!?. Intelligence, 68, 128-140. https://doi.org/10.1016/j.intell.2018.03.008

• Journal Article Type: Article
• Acceptance Date: Mar 17, 2018
• Online Publication Date: Apr 17, 2018
• Publication Date: May 1, 2018
• Deposit Date: Mar 22, 2018
• Publicly Available Date: Apr 17, 2020
• Journal: Intelligence
• Print ISSN: 0160-2896
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 68
• Pages: 128-140
• DOI: https://doi.org/10.1016/j.intell.2018.03.008
• Public URL: https://durham-repository.worktribe.com/output/1363778