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The Effectiveness of the Learning Devices Using Investigation-Based Multiple Representation to Improve Students' Problem-solving Ability on Reflection and Refraction Materials

机译:学习设备使用基于调查的多种表示的有效性,提高学生对反射和折射材料的解决能力

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The aim of this study was to explain the effectiveness of the Investigation-Based Multiple Representation (IBMR) learning model to improve the physics problem-solving abilities of high school students on reflection and refraction of light. The effectiveness of the learning device was analysed based on the results of tests of problem-solving abilities and student responses. The trial was conducted on 62 students from grade eleventh at State Senior High School 1 of Waru (East Java, Indonesia), using a one-group pre-test-post-test design. The data collection in this study was used test and survey techniques. The data collection instrument was used as a problem-solving ability test consisting of seven problem descriptions and student response questionnaires. The data were analysed quantitatively using inferential statistics, i.e. paired t-test and independent t-test for problem-solving ability data and descriptive statistics using the percentage of students for student response data. The results of the data analysis were showed a significant increase in the ability to solve physical problems with an average N-Gain score of the high category (i.e. 0.72 for students of class IPA 1 and 0.73 for students of class IPA 2) and there was a consistency in the increase in grades N-gain in both replication classes. The results of the analysis of student responses showed that students were responded to learning activity very positively with a percentage of 85.84%. These results indicate that learning using the IBMR model is effective for improving students' physics problem-solving abilities in reflection and refraction material.
机译:本研究的目的是解释基于调查的多个代表(IBMR)学习模型的有效性,以改善高中生对光线反射和折射的物理问题解决能力。根据问题解决能力和学生反应的测试结果分析了学习设备的有效性。该试验是在沃鲁(东爪哇省东爪哇省)高中1年级第11级的62名学生进行,使用一组预先测试后设计。本研究中的数据收集是使用测试和调查技术。数据收集仪器被用作解决七个问题描述和学生响应问卷的问题解决能力测试。使用推动统计来定量地分析数据,即配对T检验和独立的T检验,用于解决问题的能力数据和描述性统计数据,使用学生的学生响应数据的百分比。数据分析的结果显示出在高级N-GAIN评分的平均N-GAIN评分(即IPA类级别的学生为0.73的0.72的物理问题的能力显着增加了复制类中的N-GAIN等级增加的一致性。学生反应分析结果表明,学生因百分比为85.84%的百分比积极地回应学习活动。这些结果表明,使用IBMR模型的学习对于改善学生的物理问题解决反射材料的能力有效。

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