Prediction of Students' Ability to Difficulty Level of Problem Based on Linear Method

Hervit Ananta Vidada, Eko Mulyanto Yuniarno, Supeno Mardi Susiki Nugroho, Umi Laili Yuhana
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Abstract

Knowing the ability of students is something that is important to formulate exam questions correctly, namely questions with the appropriate level of difficulty. However, in general, exam questions are prepared with the assumption that students' abilities are the same, so the results obtained do not reflect the actual abilities of students. This study focuses on predicting the ability of grade 6 students in mathematics. The data was obtained from 400 exam questions with 8 materials done by 23 students. Students' ability categories are grouped into 3, namely high ability, medium ability, and low ability. The difficulty of the questions is grouped into difficult questions, medium questions, and easy questions based on the assessments of 5 different class teachers. Our research uses the linear regression method and successfully shows that there is a close relationship between students' abilities and the level of difficulty of the questions. The difficulty level of the questions contributed 63% to the students' abilities. The standard error of 0.04905 means that the regression model is the right model in determining students' abilities.
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基于线性方法的学生对问题难易程度的能力预测
了解学生的能力对于正确出题,也就是选择合适的难度是很重要的。但是,一般情况下,试题是在假设学生的能力是相同的情况下准备的,所以得出的结果并不能反映学生的实际能力。本研究的重点是预测六年级学生的数学能力。数据来自23名学生的400道试题和8份材料。学生的能力类别分为3类,即高能力、中等能力和低能力。题目的难度根据5位不同的班主任的评估分为困难问题、中等问题和简单问题。我们的研究使用线性回归方法,成功地表明学生的能力与问题的难易程度之间存在密切的关系。题目的难度对学生的能力贡献了63%。标准误差为0.04905,说明回归模型是确定学生能力的正确模型。
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