The role of domain-general attention and domain-specific processing in working memory in algebraic performance: An experimental approach.

Ünal, Zehra E.; Forsberg, Alicia; Geary, David C.; Cowan, Nelson

doi:10.1037/xlm0001117

Cited by 5 publications

(2 citation statements)

References 85 publications

(170 reference statements)

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“…Indeed, the problem type is an internal difficulty to the task and might not be seen consciously by the participants whereas the Dot Memory Task is external to the task and its difficulty might be immediately understood. Unal et al (2022) used a similar external load task in the context of math problem solving. They showed that the difficulty of the load task has a consistent influence on performance.…”

Section: Discussionmentioning

confidence: 99%

Reasoning More Efficiently with Primary Knowledge Despite Extraneous Cognitive Load

Lespiau,

Tricot

2024

Evol Psychol

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Geary's evolutionary approach in educational psychology differentiates between primary (low cognitive costs and motivational advantage) and secondary knowledge (high cognitive costs and no motivational benefit). Although these features have been well demonstrated in previous work, the underlying mechanisms remain unclear. To investigate it, in a reasoning task, the present study varies (i) the content of the problems (primary knowledge vs. secondary; e.g., food vs. grammar rules), (ii) the intrinsic cognitive load (conflict or non-conflict syllogism, the former requiring more cognitive resources to be properly processed than the latter) and (iii) the extraneous cognitive load (via a Dot Memory Task with three modalities: low, medium and high cognitive load). Analyses assessed the influence of these variables on performance, problem solving speed and perceived cognitive load. Results confirmed the positive impact of primary knowledge on efficiency, particularly when intrinsic cognitive load was high. Surprisingly, the extraneous cognitive load did not influence the performance in secondary knowledge content but that in primary knowledge content: the higher the additional load was, the better the performance was, only for primary knowledge and especially for syllogisms with high intrinsic load. Findings support evolutionary theory as secondary knowledge would overload cognitive resources, preventing participants from allocating sufficient resources to solve problems. Primary knowledge would allow participants to process the additional load and to increase their performance despite this. This study also raises the hypothesis that a minimum cognitive load is necessary for participants to be invested in the task.

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Section: Discussionmentioning

confidence: 99%

Reasoning More Efficiently with Primary Knowledge Despite Extraneous Cognitive Load

Lespiau,

Tricot

2024

Evol Psychol

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“…Using arithmetic as an example seems like a reasonable choice because arithmetic is one of the most common types of mental algorithms that many of us use daily, even in the smartphone era, and yet even simple arithmetic algorithms could be quite demanding. Correspondingly, the critical role of WM (and other executive functions) in mental arithmetic was demonstrated repeatedly DeStefano & LeFevre, 2004;Hubber et al, 2014;Ünal et al, 2022). Specifically, WM and executive functions play an important role in multi-digit arithmetic algorithms (Archambeau & Gevers, 2018;Hitch, 1978;Lemaire, 2023;Logie et al, 1994;Peng et al, 2016;Raghubar et al, 2010;Zhang et al, 2023) in multiplication but also in addition and subtraction, in particular to implement the carry and borrow operations (Fürst & Hitch, 2000;Seitz & Schumann-Hengsteler, 2002).…”

Section: The Challenge Of Mental Algorithmsmentioning

confidence: 97%

The temporal dynamics of information flow in working memory when executing a mental algorithm: The case of multi-digit arithmetic

Dotan,

Nir

2023

Preprint

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The importance of working memory (WM) in executing mental algorithms is well-established in cognitive theories and empirical evidence. However, many of the precise ways in which WM operates during a mental algorithm are still poorly understood. Here, we used the classical example of mental arithmetic to examine how information is managed in WM during the algorithm execution. Participants added, in their head, pairs of two-digit numbers with a decade crossing either at the decades (82+74) or at the units (28+47). They used either of two 3-stage algorithms: [1] add the decades, [2] add the units, [3] merge their sums (20+40; 8+7; 60+15=75); or [1] add-units, [2] add-decades, [3] merge. Addition (stages 1-2) was harder when the sum of the two digits exceeded 10, a situation that increases the WM demands. Importantly, this decade crossing effect was larger in stage 1 than in stage 2. We conclude that the addends of stage-1 were removed from WM once this stage was completed and they were no longer needed; this reduced the WM load in stage 2, leading to better performance. Additionally, the performance in stage 3 (merge) was modulated by the order of the preceding stages (1-2): stage 3 was faster in the decades-then-units case than in the units-then-decades case. We conclude that WM stores data (the decade and unit sums) in an ordered manner by default, even when this is not needed for the task. We discuss the importance of WM management processes, of the kind shown here, for mental algorithms.

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Relative contributions of g and basic domain-specific mathematics skills to complex mathematics competencies

Ünal,

Kartal,

Ulusoy

et al. 2023

Intelligence

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The role of domain-general attention and domain-specific processing in working memory in algebraic performance: An experimental approach.

Cited by 5 publications

References 85 publications

Reasoning More Efficiently with Primary Knowledge Despite Extraneous Cognitive Load

Reasoning More Efficiently with Primary Knowledge Despite Extraneous Cognitive Load

The temporal dynamics of information flow in working memory when executing a mental algorithm: The case of multi-digit arithmetic

Relative contributions of g and basic domain-specific mathematics skills to complex mathematics competencies

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