The dimensionality of reasoning: Inductive and deductive inference can be explained by a single process.

Abstract

Three-experiments examined the number of qualitatively different processing dimensions needed to account for inductive and deductive reasoning. In each study, participants were presented with arguments that varied in logical validity and consistency with background knowledge (believability), and evaluated them according to deductive criteria (whether the conclusion was necessarily true given the premises) or inductive criteria (whether the conclusion was plausible given the premises). We examined factors including working memory load (Experiments 1 and 2), individual working memory capacity (Experiments 1 and 2), and decision time (Experiment 3), which according to dual-processing theories, modulate the contribution of heuristic and analytic processes to reasoning. A number of empirical dissociations were found. Argument validity affected deduction more than induction. Argument believability affected induction more than deduction. Lower working memory capacity reduced sensitivity to argument validity and increased sensitivity to argument believability, especially under induction instructions. Reduced decision time led to decreased sensitivity to argument validity. State-trace analyses of each experiment, however, found that only a single underlying dimension was required to explain patterns of inductive and deductive judgments. These results show that the dissociations, which have traditionally been seen as supporting dual-processing models of reasoning, are consistent with a single-process model that assumes a common evidentiary scale for induction and deduction. (PsycINFO Database Record

A test of two processes: The effect of training on deductive and inductive reasoning

“…More importantly for our current interest in instructions, Experiment 1 did not replicate the effects sometimes observed that 1) validity has a larger effect on deduction than induction and 2) believability has a larger effect on induction than deduction (e.g., Hayes et al, 2018;Rips, 2001;Rotello & Heit, 2009).…”

“…Therefore, future experiments could stick with induction and deduction judgments as the core dependent variables or tasks, but manipulate other combinations of independent variables, such as the emotional content of arguments, argument difficulty, working memory, cognitive ability, or decision time. Note however, that Hayes et al (2018) examined working memory load, working memory capacity, and decision time for induction and deduction judgments about simple arguments, and still found no evidence to support multiple processes based on state-trace analysis.…”

“…In the sections that follow, we review evidence based on state-trace analysis of reasoning data and on formal reasoning models tested via signed difference analysis (i.e., Hayes, Stephens, Ngo, & Dunn, 2018;Rips, 2001;Singmann & Klauer, 2011;. This review shows that although the simplest single-process models can be rejected, a more complex version based on the signal detection framework can successfully account for induction and deduction judgmentsthis is a viable model against dual-process competitors.…”

“…They found that the model closely approximated the data, so there was no clear evidence for more than one kind of argument strength assessment. Similarly, Hayes et al (2018) applied state-trace analysis to three experiments where people made deduction or induction judgments about arguments varying in validity and believability. Notably, these experiments tested several factors relevant to important theoretical distinctions between Type 1 and 2 processing: working memory load, working memory capacity, and decision time (e.g., De Neys, 2012;Handley & Trippas, 2015).…”

“…Notably, these experiments tested several factors relevant to important theoretical distinctions between Type 1 and 2 processing: working memory load, working memory capacity, and decision time (e.g., De Neys, 2012;Handley & Trippas, 2015). Although there were clear dissociations between argument endorsement rates in induction and deduction, Hayes et al (2018) found the data could be explained by variations in a single latent variable (again, based on CMR tests).…”