Does language really matter when solving mathematical word problems in a second language? A cognitive load perspective

Moussa-Inaty, Jase; Causapin, Mark; Groombridge, Timothy

doi:10.1080/03055698.2018.1516629

Cited by 2 publications

(1 citation statement)

References 60 publications

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“…In line with the literature (e.g. Brünken, Plass & Leutner, 2004;Herrlinger et al, 2017;Kalyuga, et al1999;Leahy & Sweller, 2016;Moreno & Mayer, 2002;, Moussa-Inaty, Causapin, Groombridge, 2018 cognitive load theory principles, when understood, can translate into appropriate learning environments, which will enable learners to achieve improved performance. As far as practical implications, the results of this study highlight that the design of materials for learners should take into account considerations of mental constraints, rather than considerations of learners' preferred learning styles.…”

Section: Implications Of the Studysupporting

confidence: 58%

Instructional Mode: A Better Predictor of Performance Than Student Preferred Learning Styles

Moussa-Inaty¹,

Atallah²,

Causapin³

2019

INT J INSTRUCTION

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This study sought to investigate the link between preferred learning styles, performance, and cognitive load. After determining learning styles (visual or auditory), undergraduate students were assigned to three instructional formats, namely: Listen Only, Read Only, and Read + Listen. A pretest was administered to assess students' prior knowledge on lightning. During acquisition, students received instructions specific to the instructional format they were assigned to. For example, students in the Read Only group received written materials only while those in the Listen Only group received auditory materials only. The acquisition phase was followed by a posttest phase. Based on cognitive load theory, it was hypothesized that different instructional formats would result in differences in student performances. Two-way between-groups ANOVA results confirm the hypotheses, in that student's cognitive load was a better predictor of student performance than student learning styles. Educational implications and limitations are also discussed.

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Section: Implications Of the Studysupporting

confidence: 58%

Instructional Mode: A Better Predictor of Performance Than Student Preferred Learning Styles

Moussa-Inaty¹,

Atallah²,

Causapin³

2019

INT J INSTRUCTION

Self Cite

View full text Add to dashboard Cite

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Predicting Math Performance of Middle Eastern Students: The Role of Dispositions

et al. 2022

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The present research examines the contribution of individual differences in chronotype and self-efficacy to the math performance of male and female students in STEM and no-STEM majors. Questionnaires assessing the selected individual differences were distributed to students of Middle Eastern descent enrolled in math courses of the general education curriculum. Summative assessment indices were used to measure performance comprehensively across the entire semester (course grades) and as a one-time occurrence (final test grades). The contribution of morningness and self-efficacy to both course and test performance of STEM students was sensitive to the interaction of gender and major. Instead, neither factor contributed to no-STEM students’ course and test performance. These findings were used to plan improvements in the instruction and advising of students in STEM majors, thereby complying with a key tenet of action research.

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Does language really matter when solving mathematical word problems in a second language? A cognitive load perspective

Cited by 2 publications

References 60 publications

Instructional Mode: A Better Predictor of Performance Than Student Preferred Learning Styles

Instructional Mode: A Better Predictor of Performance Than Student Preferred Learning Styles

Predicting Math Performance of Middle Eastern Students: The Role of Dispositions

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