What Makes Mental Modeling Difficult? Normative Data for the Multidimensional Relational Reasoning Task

Abstract

Relational reasoning is a complex form of human cognition involving the evaluation of relations between mental representations of information. Prior studies have modified stimulus properties of relational reasoning problems and examined differences in difficulty between different problem types. While subsets of these stimulus properties have been addressed in separate studies, there has not been a comprehensive study, to our knowledge, which investigates all of these properties in the same set of stimuli. This investigative gap has resulted in different findings across studies which vary in task design, making it challenging to determine what stimulus properties make relational reasoning—and the putative formation of mental models underlying reasoning—difficult. In this article, we present the Multidimensional Relational Reasoning Task (MRRT), a task which systematically varied an array of stimulus properties within a single set of relational reasoning problems. Using a mixed-effects framework, we demonstrate that reasoning problems containing a greater number of the premises as well as multidimensional relations led to greater task difficulty. The MRRT has been made publicly available for use in future research, along with normative data regarding the relative difficulty of each problem.

Sensemaking and Scientific Modeling: Intertwined processes analyzed in the context of physics problem solving

“…The assembling of the task-related information in both cases contributed to the participants' interaction with their mental models. The co-occurrence of mental modeling with assembling of contextual information is consistent with the current literature as researchers have noted mental modeling as a key feature of making sense of the given task [17] using the essential pieces of information from the problem statement [83,84].…”

Predictive effects of creative abilities and attitudes on performance in university-level computer science courses.

“…Participants completed a variety of three term syllogistic reasoning problems with different model structures that use spatial and nonspatial language. This task, known as the Multidimensional Relational Reasoning Task (Cortes et al, 2021), involves relations along multiple dimensions to make the problems more difficult than syllogistic reasoning tasks that only involve relations along a single dimension. Participants see two premises and must determine whether a certain conclusion is true or false.…”

Generating distant analogies facilitates relational integration: Intermediary role of relational mindset and cognitive load

“…Relation integration performance was measured by the MRRT ( Cortes et al, 2021 ). Each problem consisted of two or three premises and a conclusion, and these problems systematically manipulated the following properties: number of premises (two or three), number of dimensions (one or two), and order of premises (continuous or discontinuous).…”