• Title/Summary/Keyword: Broken line graph Analysis

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A Study on The Analysis Method of Problem Solving Results of Linear Functions (일차함수의 문제해결 결과 분석 방법에 관한 연구)

  • Jang, Cheong Hee;Han, Ju-Wan
    • Journal of the Korean School Mathematics Society
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    • v.25 no.1
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    • pp.79-104
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    • 2022
  • It is very important to help students learn by examining how well students solve math problems. Therefore, in this study, four methods(error analysis by problem type, schematization analysis, area graph analysis, and broken line graph analysis) were constructed to analyze how the connectivity between concepts of middle school functions affects the problem solving results. The students' learning situation was visually expressed to enable intuitive understanding. This analysis method makes it easy to understand the evaluation results of students. It can help students learn by understanding their learning situation. It will be useful in mathematics teaching and learning as it can help students to monitor their own problems and make a self-directed learning plan.

High School Students' Errors in Constructing and Interpreting Science Graph (고등학생들의 과학 그래프 작성 및 해석 과정에서 나타난 오류)

  • Kim, You-Jung;Choi, Gil-Soon;Noh, Tae-Hee
    • Journal of The Korean Association For Science Education
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    • v.29 no.8
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    • pp.978-989
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    • 2009
  • In this study, we investigated high school students' errors in constructing and interpreting graph on experimental results by students' science achievement level. Two tests regarding constructing and interpreting graph about 'the relationship between the pressure and volume of a gas' were administered to 11th-graders (N=140). Analysis of the results revealed that most students exhibited many errors in the processes of constructing and interpreting graph. In the processes of constructing graph, there were 16 types of errors on the categories of 'misinterpreting the variables', 'mis-marking the graphical elements', and 'misusing the data'. The students of lower achievement level had more errors than those of higher achievement level in the four error types, that is, 'missing the variables', 'representing the best fit line using a broken line', 'adding the data', and 'neglecting the data'. However, the results were reversed in the error type of 'not marking the origin.' In the processes of interpreting graph, there were 9 types of errors on 'misreading the data', 'wrong interpolation and extrapolation', and 'establishing the wrong relationship'. The students of lower achievement level had more errors than those in the higher achievement level in the error types of 'wrong interpolation' and 'misdescribing the relationship between variables'. Educational implications of the findings are discussed.