OPTIMIZATION OF GUIDED DISCOVERY LEARNING MODELS TO INCREASE STUDENTS' INTEREST IN MATHEMATICS

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Published: Feb 3, 2020
DOI: https://doi.org/10.22460/infinity.v9i1.p69-80
Keywords:
Guided Discovery Learning Learning Interest Mathematics Education

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Nurhayani Nurhayani
Universitas Negeri Yogyakarta, Indonesia
Raden Rosnawati
Universitas Negeri Yogyakarta, Indonesia
Tuslikhatun Amimah
Universitas Negeri Yogyakarta, Indonesia

Abstract

Student interest in learning is a very important factor in determining student success in learning mathematics. Various attempts were made by educators and educational researchers to increase student interest in learning. This research is a classroom action research model by Kemmis and Mc Taggart that aims to describe the application of Guided Discovery learning in optimizing students' interest in learning mathematics. The increase in students' interest in learning mathematics is also supported by the results of student achievement. The research data consisted of students' interest in learning mathematics, learning achievement data, and observations of learning outcomes. Data on learning interest in mathematics is obtained through a questionnaire, data on learning achievement is obtained through tests and data on the results of observations of learning achievement are obtained through observation sheets during learning. In general, the results of the study showed that the average student interest in learning mathematics at 83.93 reached the good category. The completeness of student achievement test results reached 83.87% of students achieving the minimum completeness criteria with an average student score of 85.61. The percentage of teacher and student learning outcomes respectively at 83.80% and 76.91% reached the good category. Therefore it can be concluded that the Guided Discovery learning model can be applied to optimize students' interest in mathematics learning especially by paying attention to the results of reflections from this study.

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Vol. 9 No. 1 (2020): Volume 9, Number 1, Infinity
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Articles
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