Abstract

A key question in the developmental sciences is whether developmental differences are quantitative or qualitative. For example, does age increase the speed in processing a task (quantitative differences) or does age affect the way a task is processed (qualitative differences)? Until now, findings in the domain of decision making have been based on the assumption that developmental differences are either quantitative or qualitative. In the current study, we took a different approach in which we tested whether development is best described as being quantitative or qualitative. We administered a judgment version and a choice version of a decision-making task to a developmental sample (njudgment = 109 and nchoice = 137; Mage = 12.5 years, age range = 9–18). The task, the so-called Gambling Machine Task, required decisions between two options characterized by constant gains and probabilistic losses; these characteristics were known beforehand and thus did not need to be learned from experience. Data were analyzed by comparing the fit of quantitative and qualitative latent variable models, so-called multiple indicator multiple cause (MIMIC) models. Results indicated that individual differences in both judgment and choice tasks were quantitative and pertained to individual differences in “consideration of gains,” that is, to what extent decisions were guided by gains. These differences were affected by age in the judgment version, but not in the choice version, of the task. We discuss implications for theories of decision making and discuss potential limitations and extensions. We also argue that the MIMIC approach is useful in other domains, for example, to test quantitative versus qualitative development of categorization, reasoning, math, and memory.

Highlights

  • A key question in the developmental sciences is whether development is best described as quantitative or qualitative (Jones & Dekker, 2018; Siegler, 2007)

  • Fit was better for the quantitative model with age included (BIC = 13813.1) than for the qualitative model with age included (BIC = 13950.8)

  • The first insight pertains to the main question of the current study: Are developmental differences in decision making quantitative or qualitative in nature? Current results provide support for quantitative conceptualizations, as implemented in information integration theory, cumulative prospect theory, and risk return theory (Anderson, 1980; Schlottmann & Tring, 2005; Tversky & Kahneman, 1992; Weber et al, 2004; Wilkening & Anderson, 1982)

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Summary

Introduction

A key question in the developmental sciences is whether development is best described as quantitative or qualitative (Jones & Dekker, 2018; Siegler, 2007). The developmental increase in the speed with which children solve simple additions may originate in qualitative changes in strategy use; young children use a slow counting strategy, whereas older children use a fast memory retrieval strategy (Ashcraft & Fierman, 1982). Quantitative development would signify that all people use the same strategy to arrive at a decision but that there would be quantitative developmental changes in the parameters describing such a strategy. Qualitative development, on the other hand, would imply that there would be developmental changes in strategies being used. The purpose of the current study was to test whether development of decision making is best characterized as quantitative or qualitative. We did so in a sample of 9- to 18-year-olds using a latent variable modeling approach tailored to differentiate between these two types of development

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