Analysis of Error in Working of Questions on the Semester Final Exam of Mathematics Statistics for Students of UIN Saizu Purwokerto

Paradikma: Jurnal Pendidikan Matematika Pub Date : 2023-06-29 DOI:10.24114/paradikma.v16i1.46530

Mutijah Mutijah

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Abstract

Learning evaluation of the certain subject is important to be done in university. It is to be able to see, improve and increase the quality of learning outcomes. One form of evaluation for a Mathematics Statistics course is the final semester exam, abbreviated as UAS. Purpose of this article to determine the error type of students in working the final semester exam, percentage of students who do mistakes and amount of error on each type, as well the most mistakes . Research used a quantitative descriptive method imposed on all of population as many as 98 respondents. Data collection used documentation and the data analysis that is statistics descriptive. Research results showed that as many as 14 type of error with one among them is findings a new of error type. Percentage of students do error on each type is the concept error 96.94%, principle 92.86%, fact 20.41%, conclusion no used correct reasoning 8.16% , error because procedure or algoritm 4.08%, skill error 21.43%, error without pattern 37.76%, technical 3.06%, and error in mark 5.1%, and successive types of error that is data error , operation , write the exact same long answer to two different questions, language interpretation, as well finishing error each of which is 1.02%. The same as in according of the type errors are found percentage of the number of errors that is 40.12%, 28, 09%, 6.17%, 2.47% , 1.23%, 6.48%, 11.42%, 0.93%, 1.54%, and the others is 0.31% respectively. Most mistakes is the concept error.

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南京大学学生数学统计学期期末考试出题错误分析

某一学科的学习评价是大学教学中一项重要的工作。它是能够看到、改善和提高学习成果的质量。数学统计课程的一种评估形式是期末考试，简称为UAS。本文的目的是确定学生在期末考试中犯的错误类型，学生犯错误的百分比和每种类型的错误数量，以及最多的错误。研究采用了定量描述方法，对所有人口施加了多达98名受访者。数据收集使用了文档和数据分析，即统计描述性。研究结果表明，错误类型多达14种，其中一种是新发现的错误类型。学生在各类错误中，概念错误占96.94%，原理错误占92.86%，事实错误占20.41%，结论错误占8.16%，程序或算法错误占4.08%，技能错误占21.43%，无模式错误占37.76%，技术性错误占3.06%，标记错误占5.1%，数据错误、操作错误、对两个不同的问题写出完全相同的长答案、语言解释错误以及整理错误各占1.02%。同样的，根据类型错误分别发现的错误次数百分比分别为40.12%、28%、09%、6.17%、2.47%、1.23%、6.48%、11.42%、0.93%、1.54%，其他分别为0.31%。大多数错误是观念上的错误。

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Paradikma: Jurnal Pendidikan Matematika

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