Simulating the Process Overlap Theory of Intelligence - A Unified Framework Bridging Psychometric and Cognitive Perspectives

Abstract

Traditional theories of intelligence either prioritize a psychometric or a cognitive perspective, but their limitations and incompatibilities hinder a comprehensive understanding. Contemporary theories, like the process overlap theory (POT; Kovacs & Conway, 2016; 2019), aim to bridge the gap between both perspectives, by explaining inter-individual differences in intelligence through intra-individual psychological processes. The current study investigates POT as a unified framework for understanding human intelligence, incorporating psychometric and cognitive theories. POT proposes a novel psychometric structure and cognitive architecture that explains individual differences in cognitive abilities. We developed dynamics to simulate potential correlational or causal structures of cognitive processes involved in human cognitive activities based on POT, examining how these structures align with psychometric models. Test scores were generated from a sampling of simulated cognitive processes and fitted by typical latent factor models. Despite the absence of a general cognitive ability in generating the data, results showed that a standard higher-order “general intelligence” model fit the data well. As POT rejects the notion of a general factor of intelligence (g) psychometric network models (Borsboom et al., 2021; Epskamp et al., 2018) were also implemented to simulated test scores, as they align better with the theory. Finally, we implemented a network structure at the latent factor level to retain latent factor models' benefits in accounting for measurement errors. Estimated factor scores for simulated broad abilities from the three different models are compared and discussed. This study demonstrates POT’s compatibility with standard psychometric models, including the general intelligence factor, without assuming a common cognitive cause. The results support POT and provide an alternative theoretical and statistical framework for contemporary research on human cognition, combining psychometric and cognitive theories of intelligence.