Analysis of Student Errors in Solving Numeracy Literacy Problems of Graph Representation Model in Elementary School

This study aims to describe the types of student errors in solving numeracy literacy problems of graph representation models. This study used a mixed methods research design with a sequential exploratory type. The data collection techniques used were tests and interviews. The participants in this st...

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Bibliographic Details
Published in:Al Ibtida: Jurnal Pendidikan Guru MI
Main Authors: Intan Sari Rufiana, Slamet Arifin, Mohammad Yusuf Randy, Fierda Nursitasari Amaliya
Format: Article
Language:English
Published: Institut Agama Islam Negeri (IAIN) Syekh Nurjati Cirebon 2024-10-01
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Online Access:https://syekhnurjati.ac.id/jurnal/index.php/ibtida/article/view/18720
Description
Summary:This study aims to describe the types of student errors in solving numeracy literacy problems of graph representation models. This study used a mixed methods research design with a sequential exploratory type. The data collection techniques used were tests and interviews. The participants in this study were 30 elementary school students tested and six students selected by purposive sampling to be interviewed. The results showed that students experienced conceptual errors and procedural errors. In conceptual errors, 40% of students make errors in reading data, 43% between data, and 60% of students make errors beyond data. Conceptual errors occur when students cannot understand the context of the problem, cannot read the data, do not master the basic concepts of statistics, and do not understand number patterns. In procedural errors, 63% of students make errors in reading data, 73% of students make errors in reading between data, and 80% of students make errors in reading beyond data. Procedural errors occur when students are wrong in choosing the solution procedure, calculating, and predicting. Therefore, educators need to design appropriate learning strategies to minimize errors made by students in numeracy literacy questions on graph representation models, such as applying contextual learning-based numeracy problems.
ISSN:2442-5133
2527-7227