Implementation of POGIL model based ethnomathematics on students' mathematical communication ability.

Autor: Anim, Anim, Saragih, Sahat, Rahmadani, Elfira, Sari, Nilam, Batubara, Ismail Hanif, Suciawati, Hasni, Sari, Dwi Novita, Syafitri, Ely
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Zdroj: AIP Conference Proceedings; 2022, Vol. 2659 Issue 1, p1-7, 7p
Abstrakt: This study is aimed to determine whether there were the differences in the average pre-test and post-test results on students' mathematical communication ability through the ethnomathematics-based Process Oriented Guided Inquiry Learning (POGIL) model. It was conducted using Pre-Experimental Research with the research population being all students of Grade VIIE SMP Quran Kisaran. Class sample selection is done randomly and selectively. The instrument used was a test of students' mathematical communication ability with quadrilateral material. The data in this study were analyzed by using parametric statistical analysis. Statistical analysis of the data was carried out by using the Paired Sample T Test analysis. The results showed that (1) There was a significant difference between the results of the pre-test and post-test on students' mathematical communication ability through Ethnomathematical-based POGIL Learning; and the average pre-test and post-test were 26.17 in.the pre-test and 34.3667 in.the post-test. The findings obtained during the research on the application of the ethnomathematical-based POGIL model showed that students who were in the fast- understanding category were more active in groups and were better able to create ideas in the form of their own arguments compared to students who still did not understand or had difficulty understanding the problem, however, the data obtained was not valid enough, researchers only conduct observation and interview to determine the category of students who understand quickly or not, so it becomes a suggestion for further researchers to pay more attention to students' abilities in the high, medium, and low categories, so that later it will be concluded strongly that this model is more recommended for high, medium or low capabilities. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index