减少学生的误解:在缓冲溶液材料上化学表征的双pbl学习的应用

Latika Ulfah, M. Kusasi, A. Almubarak
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引用次数: 0

摘要

本研究通过多模型TTW-PBL学习对缓冲溶液的化学表征进行研究,以确定对化学表征的理解,减少学生的误解。使用的方法是准实验设计与非等效的对照组。自变量为化学表征中的TTW-PBL学习模型和化学表征中的PBL模型。相反,因变量是对化学表征和误解的理解。数据分析技术采用描述和推理分析技术。通过描述性分析,找出学生误解的差异。推论分析使用t检验来分析对化学表征的理解差异。结果表明,多模型TTW-PBL和PBL模型(tcount >表= 2.15 > 1.99)对班级化学表征的理解存在显著差异,误解率分别为16.57%和23.24%。最后,TTW-PBL化学表征学习可以减少学生的误解。
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REDUCTION OF STUDENT MISCONCEPTIONS: APPLICATION OF TTW-PBL LEARNING WITH CHEMICAL REPRESENTATION ON BUFFER SOLUTION MATERIALS
The research was conducted on the chemical representation of buffer solution learning through multi-model TTW-PBL learning to determine the understanding of chemical representation and reduce students' misconceptions. The method used is a quasi-experimental design with a non-equivalent control group. The samples of this study were students of class XI MIPA 1 as the experimental class and XI MIPA 3 as the control class at SMAN 11 Banjarmasin. The independent variables are the TTW-PBL learning model in chemical representation and the PBL model in chemical representation. In contrast, the dependent variable is the understanding of chemical representations and misconceptions. The data analysis technique used descriptive and inferential analysis techniques. Descriptive analysis was used to find out the differences in students' misconceptions. The inferential analysis uses a t-test to analyze differences in understanding of chemical representations. The results showed significant differences in the understanding of chemical representation in the class using the multi-model TTW-PBL and PBL model with a value of tcount > ttable = 2.15 > 1.99 and the percentage of misconceptions of 16.57% and 23.24%, respectively. Finally, TTW-PBL learning with Chemical Representation can reduce students misconception.
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自引率
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发文量
7
审稿时长
12 weeks
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