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Characteristics of Students Cognitive Load in Mathematics Learning
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This study aims to describe the characteristics of students’ cognitive load in mathematics learning, particularly in the topic of Gauss–Jordan elimination, and to identify the factors influencing intrinsic cognitive load, extraneous cognitive load, and germane cognitive load. This research employed a descriptive qualitative approach conducted with students of the Informatics Technology Study Program who were enrolled in a linear algebra course. The research subjects consisted of 15 students selected using purposive sampling. Data were collected through classroom observations, a cognitive load questionnaire, and in-depth interviews. The data were analyzed using the Miles and Huberman model, which includes data reduction, data display, and conclusion drawing. The results indicate that students’ intrinsic cognitive load was categorized as high, with 72% of students experiencing difficulties in understanding concepts, requiring substantial mental effort, and needing considerable time to determine solution steps. Extraneous cognitive load was categorized as moderate, with 46% of students showing difficulties related to the presentation of materials and symbolic representations. Meanwhile, germane cognitive load was categorized as high, with 74% of students demonstrating active efforts to understand concepts, applying systematic strategies, and reflecting on their problem-solving processes. These findings suggest that although students experienced a high level of intrinsic cognitive load, they were still able to construct conceptual understanding through active engagement in learning. This study implies that structured and systematic instructional design can help manage students’ cognitive load and enhance the effectiveness of mathematics learning in higher education
Universitas PGRI Argopuro Jember
Title: Characteristics of Students Cognitive Load in Mathematics Learning
Description:
This study aims to describe the characteristics of students’ cognitive load in mathematics learning, particularly in the topic of Gauss–Jordan elimination, and to identify the factors influencing intrinsic cognitive load, extraneous cognitive load, and germane cognitive load.
This research employed a descriptive qualitative approach conducted with students of the Informatics Technology Study Program who were enrolled in a linear algebra course.
The research subjects consisted of 15 students selected using purposive sampling.
Data were collected through classroom observations, a cognitive load questionnaire, and in-depth interviews.
The data were analyzed using the Miles and Huberman model, which includes data reduction, data display, and conclusion drawing.
The results indicate that students’ intrinsic cognitive load was categorized as high, with 72% of students experiencing difficulties in understanding concepts, requiring substantial mental effort, and needing considerable time to determine solution steps.
Extraneous cognitive load was categorized as moderate, with 46% of students showing difficulties related to the presentation of materials and symbolic representations.
Meanwhile, germane cognitive load was categorized as high, with 74% of students demonstrating active efforts to understand concepts, applying systematic strategies, and reflecting on their problem-solving processes.
These findings suggest that although students experienced a high level of intrinsic cognitive load, they were still able to construct conceptual understanding through active engagement in learning.
This study implies that structured and systematic instructional design can help manage students’ cognitive load and enhance the effectiveness of mathematics learning in higher education.
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