Sri Rejeki
Universtias Muhammadiyah Surakata

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Improving Students’ Self-Confidence and Problem-Solving Ability Through RME Approach with TTW Type Cooperative Learning Model Setting Sri Adiningsih Utami Ningrum; Sri Rejeki
Numerical: Jurnal Matematika dan Pendidikan Matematika Vol. 7 No. 1 (2023)
Publisher : Institut Agama Islam Ma'arif NU (IAIMNU) Metro Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25217/numerical.v7i1.3093

Abstract

Students studying mathematics get training in developing their problem-solving skills. Cognitive capacity and self-confidence can have an impact on problem-solving skills. This study aims to increase students' confidence and mathematical problem-solving skills through the TTW-type cooperative learning model RME approach. Research this class action with the Kemmis & Taggart model that can cover several cycles. The implementation of this study is two cycles with the research subjects of 28 grade VII students at a junior high school in Surakarta in the 2022/2023 academic year. Data is obtained through observation and tests. Data analysis techniques are carried out with descriptive statistics and supported by qualitative analysis of student work results. Based on the results of data analysis, confidence, and mathematical problem-solving skills, students have improved in each cycle. Students' confidence average score increased from 35.7 in the pre-cycle to 67.8 in the first and 84.8 in the second cycles. Students' mathematical problem-solving skills increased from an average score of 60 pre-cycle to 72.7 in the first cycle and 78.3 in the second cycle. This study increased self-confidence and mathematical problem-solving skills for grade VII junior high school students by applying the RME approach to setting the TTW-type cooperative learning model seen from an increase in average scores that are quite significant with 49.1 and 18.3, respectively. This finding shows the need for further efforts to achieve improved mathematical problem-solving skills that are more optimal.
Improving Students’ Self-Confidence and Problem-Solving Ability Through RME Approach with TTW Type Cooperative Learning Model Setting Sri Adiningsih Utami Ningrum; Sri Rejeki
Numerical: Jurnal Matematika dan Pendidikan Matematika Vol. 7 No. 1 (2023)
Publisher : Institut Agama Islam Ma'arif NU (IAIMNU) Metro Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25217/numerical.v7i1.3093

Abstract

Students studying mathematics get training in developing their problem-solving skills. Cognitive capacity and self-confidence can have an impact on problem-solving skills. This study aims to increase students' confidence and mathematical problem-solving skills through the TTW-type cooperative learning model RME approach. Research this class action with the Kemmis & Taggart model that can cover several cycles. The implementation of this study is two cycles with the research subjects of 28 grade VII students at a junior high school in Surakarta in the 2022/2023 academic year. Data is obtained through observation and tests. Data analysis techniques are carried out with descriptive statistics and supported by qualitative analysis of student work results. Based on the results of data analysis, confidence, and mathematical problem-solving skills, students have improved in each cycle. Students' confidence average score increased from 35.7 in the pre-cycle to 67.8 in the first and 84.8 in the second cycles. Students' mathematical problem-solving skills increased from an average score of 60 pre-cycle to 72.7 in the first cycle and 78.3 in the second cycle. This study increased self-confidence and mathematical problem-solving skills for grade VII junior high school students by applying the RME approach to setting the TTW-type cooperative learning model seen from an increase in average scores that are quite significant with 49.1 and 18.3, respectively. This finding shows the need for further efforts to achieve improved mathematical problem-solving skills that are more optimal.