Problem-based learning combined with realistic mathematics approach grade V elementary school

Salmia Salmia, S. Sudarmin, Y. Samsuddin
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Abstract

The study aimed to determine student learning outcomes with problem-based learning through a realistic mathematical approach in mathematics subjects for class V students. This type of research was quasi-experimental because in this study, no specific treatment (treatment) was given, but only revealed the symptoms that had been reported. It existed at the time this research was conducted, so there was no direct control over the independent variables. Data collection methods used are learning outcomes tests and documentation. The data analysis technique is the first using a descriptive statistical approach and paired sample test. The results showed that learning mathematics using problem-based learning through a realistic mathematics approach obtained an average of 80.00 students' mathematics learning outcomes, with students in the medium category with a percentage of 100%. The average normalized gain of 0.29 was convection into high, medium, and low categories, so the average normalized gain of students was in the medium category. This means that problem-based learning combined with a realistic mathematical approach to learning outcomes for fifth-grade students is in the medium category. The significance value of Asiymp. Sig. (2-tailed) is 0.09, which is greater than 0.05. Then according to the basis of decision-making in the Kolmogorov-Smirnov normality test above, it can be concluded that the data are normally distributed. Thus, the assumptions or requirements for normality distributed data in the regression model have been met.
问题学习与现实数学相结合的小学五年级教学方法
本研究的目的是在五年级学生的数学科目中,通过现实的数学方法来确定学生基于问题的学习效果。这种类型的研究是准实验的,因为在这项研究中,没有给予特定的治疗(治疗),而只是揭示了已经报告的症状。它在进行这项研究时已经存在,所以没有对自变量的直接控制。使用的数据收集方法是学习成果测试和记录。数据分析技术是第一次使用描述性统计方法和配对样本检验。结果表明,通过现实数学的方法,采用基于问题的学习方法学习数学,平均获得了80.00学生的数学学习成果,中等类别的学生比例为100%。0.29的平均归一化增益对流为高、中、低三类,因此学生的平均归一化增益处于中等类别。这意味着基于问题的学习与现实的数学方法相结合,对五年级学生的学习结果属于中等类别。Asiymp的显著性值。Sig.(双尾)为0.09,大于0.05。然后根据上面Kolmogorov-Smirnov正态检验中的决策依据,可以得出数据是正态分布的结论。从而满足回归模型中数据正态分布的假设或要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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