拼图模型和数字头一起(NHT)解决作文功能的核心材料的有效性

Debi Cinta Marito Ritonga, F. Faisal, Raudhatul Husna
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引用次数: 0

摘要

本研究旨在了解拼图和编号头在一起(NHT)学习模式在破解Langsa高中学生HOTS组成函数问题中的有效性。学生在使用拼图模型和编号头像(NHT)后的学习结果、学习过程中的学生活动和教师活动以及学生对学习模型的反应。这种类型的研究是定性的。本研究的对象为Langsa Muhammadiyah高中X MIPA班的学生,共25名学生。使用的数据收集技术有测试、观察和探针。在数据分析方面采用了学习成果测试分析、学生活动和教师活动数据分析、学生反应分析等方法。应用拼图模型和编号头像(NHT)完成HOTS物质组成函数后,88%的学生完成了研究结果。在学习过程中的学生活动中,类别的平均百分比为81.75%,然后在教师活动中,每个类别(RTK)的平均评分为良好标准,平均得分为4.0分。最后,学生在学习后的反应平均百分比为77.6%,表明学生对应用学习模式的反应较好。然后我们可以得出结论,拼图和其他竞争头一起学习模型有效地用于解决组合函数的HOTS问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efektivitas Model Pembelajaran Jigsaw dan Numbered Head Together (NHT) dalam Pemecahan Soal-Soal HOTS Materi Pokok Fungsi Komposisi
The study was intended to learn the effectiveness of jigsaw's and Numbered Heads Together (NHT) learning models in breaking the matter of HOTS composition function in Muhammadiyah high school Langsa from; The results of student learning after using the jigsaw model and Numbered Heads Together (NHT), student activity and teacher activity during the learning process, and student response to the learning model. This type of research is qualitative. The subject of this study was the Langsa Muhammadiyah high school student at X MIPA class with a total of 25 students. The data collection techniques used are tests, observations, and angkets. As for the data analysis used by the study results test analysis, the student activity and teacher activity data analysis, and the student response analysis. The results of the study were 88% of all students completed after the application of the jigsaw model and Numbered Heads Together (NHT) to complete the HOTS matter composition function. On student activities in the learning process the average percentage is 81.75% high in category, then on teacher activity gets an average of each category (RTK) rated within good criteria with an average score of 4.0. And finally, students response after learning shows an average percentage of 77.6%, it shows that students respond favorably to the applied learning model. We can then conclude that the jigsaw and other competing heads together learning models are effectively used to solve the HOTS matter of composition function.
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