Working Memory Load, Automaticity, and Problem Solving in College Engineering Students: Two Applications

The paper examined the relations among problem solving, automaticity, and working memory load (WML) by changing the difficulty level of task characteristics through two applications. In Study 1, involving 68 engineering students, a 2 (automaticity) × 2 (WML) design was utilized for arithmetic problems. In Study 2, involving 76 engineering students, a 2 (automaticity) × 2 (WML) design was used for linear algebra tasks. In both studies, there were statistically significant main effects and interaction effects of automaticity and WML on the variable of response time, concurring with the cognitive load theory. The simple effect of WML rendered a larger effect size under the conditions with low automaticity. When the testing condition was easy but contained more steps, the students were more accurate, and response times were faster. When the testing condition was difficult but contained fewer steps, the students were less accurate, and response times were slower. The findings underscore the important role of automaticity in helping engineering students bypass the limits of working memory.

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Publication Details

Journal
SAGE Open
Published
2024-10-01
DOI
https://doi.org/10.1177/21582440241305082
Primary Topic
Learning Styles and Cognitive Differences
Type
article
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0.00
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article

Working Memory Load, Automaticity, and Problem Solving in College Engineering Students: Two Applications

Xiantong Yang, Wei Hong, Ru‐De Liu, Yi Ding et al.
SAGE Open
Learning Styles and Cognitive Differences
article

Working Memory Load, Automaticity, and Problem Solving in College Engineering Students: Two Applications

Xiantong Yang, Wei Hong, Ru‐De Liu, Yi Ding, Qian Wang, Jiayi Wang, Shu Feng, Jolene Trimm
article en

Abstract

The paper examined the relations among problem solving, automaticity, and working memory load (WML) by changing the difficulty level of task characteristics through two applications. In Study 1, involving 68 engineering students, a 2 (automaticity) × 2 (WML) design was utilized for arithmetic problems. In Study 2, involving 76 engineering students, a 2 (automaticity) × 2 (WML) design was used for linear algebra tasks. In both studies, there were statistically significant main effects and interaction effects of automaticity and WML on the variable of response time, concurring with the cognitive load theory. The simple effect of WML rendered a larger effect size under the conditions with low automaticity. When the testing condition was easy but contained more steps, the students were more accurate, and response times were faster. When the testing condition was difficult but contained fewer steps, the students were less accurate, and response times were slower. The findings underscore the important role of automaticity in helping engineering students bypass the limits of working memory.

SAGE OpenVol. 14(4)
New Mexico State University (US), North Carolina State University (US), Fordham University (US), Simon Fraser University (CA), Beijing Normal University (CN), Manhattan University (US)
Openalex Percentile: Top 71%
Learning Styles and Cognitive Differences
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Working Memory Load, Automaticity, and Problem Solving in College Engineering Students: Two Applications — Xiantong Yang, Wei Hong, et al. · SAGE Open (2024) | TGRS Research Map | TGRS