In short
Relational reasoning is how we distinguish and interpret the underlying structure of a scenario or data. This is linked to a individual's logic and ability to solve problems. It's our brains' capacity to reason about abstract relationships among elements within a system, and in one famous task, a group of images. It enables us to make sense of complex patterns in various contexts.
Relational reasoning tasks
In tasks exploring relational reasoning, participants carefully observe the displayed image puzzle, noting any obvious details. They may identify the key elements such as colours or shape and note these features for comparison. Participants are presented with four different image response options, which they must assess for similarities and differences. Following this, participants must determine any patterns or sequences in how the elements are related, for example spatial relationships. Based on these patterns, they would attempt to formulate a theory about the rules connecting the images. Once a pattern has been identified, one of the response options that fit the pattern will be selected.
What is relational reasoning?
In general, relational reasoning is an important indicator of academic ability and is a vital component of fluid intelligence. A participant's performance on this assessment improves notably across childhood into adulthood. With age, strategies to solve these puzzles adapt, such as increased scanning of rows and columns. Eyetracking technology can be utilised to observe this.
Relational reasoning theory
One theory suggests there is a unitary system for relational reasoning. This suggests that over time, from infancy to adulthood, this system develops. The essence of the adult system, known as structure mapping, is innate and present from the outset of development.
An opposing theory argues that we have multiple systems. Early Systems are tied to cognitive domains such as mental attribution. These systems don't support high-level reasoning, but can produce behaviours that mimic it, to an extent. From around age 3 to adolescence, a Late System develops separately, which is domain-general. In adulthood, the Early and Late systems coexist: Early System outputs can be used by Late System in abstract forms.
Can I use relational reasoning tasks in online research?
Yes, absolutely! In fact, other researchers have used a relational reasoning matrix in studies with adolescents and adults (Chierchia, et al., 2019).
How does it work in Gorilla?
You can try out and clone our relational reasoning task. You can also tweak this sample to use your own stimuli.
Have a look: Try a Relational Reasoning task in Gorilla
Are there any papers Gorilla users have written about relational reasoning?
Yes, there are! Have a look at the following article:
References
Chierchia, G., Fuhrmann, D., Knoll, L. J., Pi-Sunyer, B. P., Sakhardande, A. L., & Blakemore, S. J. (2019). The matrix reasoning item bank (MaRs-IB): Novel, open-access abstract reasoning items for adolescents and adults. Royal Society Open Science, 6(10), 190232. https://doi.org/10.1098/rsos.190232
Crone, E. A., Wendelken, C., Van Leijenhorst, L., Honomichl, R. D., Christoff, K., & Bunge, S. A. (2009). Neurocognitive development of relational reasoning. Developmental Science, 12(1), 55-66. https://doi.org/10.1111/j.1467-7687.2008.00743.x
Holyoak, K. J., & Lu, H. (2021). Emergence of relational reasoning. Current Opinion in Behavioral Sciences, 37, 118-124. https://doi.org/10.1016/j.cobeha.2020.11.012
Niebaum, J., & Munakata, Y. (2023). The development of relational reasoning: An eyetracking analysis of strategy use and adaptation in children and adults performing matrix completion. Open Mind, 7, 197-220. https://doi.org/10.1162/opmi_a_00078
This page was written in collaboration with Lizzie Drury
