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All Journal SJME (Supremum Journal of Mathematics Education) Jurnal Pendidikan Matematika (Jupitek) Journal of Medives: Journal of Mathematics Education IKIP Veteran Semarang
Muhammad Nasir
Universitas Muhammadiyah Parepare
Education Mathematics Social Sciences Other

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Scaffolding on Sequence and Series Learning for Didactic Anticipation Buhaerah Buhaerah; Muhammad Nasir; Zulfiqar Busrah; Andi Aras
SJME (Supremum Journal of Mathematics Education) Vol 7 No 1 (2023): Supremum Journal of Mahematics Education
Publisher : Fakultas Keguruan dan Ilmu Pendidikan Universitas Singaperbangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/sjme.v7i1.7019

Abstract

The purpose of this study is to explain the doctrine expectations of learning mathematics. Data was collected through testing, interviews, and documentation. Researchers have designed a virtual learning trajectory (HLT) based on examining the obstacles students face when learning mathematics. Next, a didactic design was developed from HLT. The method of doctrine was implemented, and the results showed that the situation of the three principles expected by researchers was the doctrine of scaffolding strategy. When determining values ​​that correspond to a pattern of numbers, researchers want to learn lessons and provide instructions in the form of education to solve problems. The researcher's expectation of giving other examples of arithmetic progressions when choosing a definition and the arithmetic progression examples help students better understand collaborative learning. The value of the nth term and the sum of the first n math terms are sent to each shirt to confirm the work and interact directly.
Student Representation of Mathematical Thinking In Mathematical Problem Solving Buhaerah Buhaerah; Muhammad Nasir
Jurnal Pendidikan Matematika IKIP Veteran Semarang Vol 7 No 1 (2023): Journal of Medives : Journal of Mathematics Education IKIP Veteran Semarang
Publisher : Urogram Studi Pendidikan Matematika, Universitas IVET

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (524.743 KB) | DOI: 10.31331/medivesveteran.v7i1.2241

Abstract

The way students who want to become teachers represent their mathematical reasoning when they solve mathematical problems—using case studies and qualitative techniques. Data were gathered from the vignette results of student work. They are using snowball sampling for subject selection. Three third-semester mathematics education program participants served as the study's research subjects—ways for gathering data, such as interviewing and recording. Three steps of the analysis were completed: presentation of data, elaboration of conclusions and verification. As a consequence of meeting all markers of mathematical thinking representation, the S1 and S2 subjects with high and moderate academic talents had good mathematical thinking representation abilities. Because S3 students with limited intellectual skills cannot still represent mathematical ideas.
STUDENT’S MISTAKES IN SOLVING PROBLEM BASED ON WATSON’S CRITERIA AND LEARNING STYLE Buhaerah Buhaerah; Muhammad Nasir; M S Dangnga
Jurnal Pendidikan Matematika (JUPITEK) Vol 5 No 2 (2022): Jurnal Pendidikan Matematika
Publisher : Program Studi Pendidikan Matematika FKIP Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jupitekvol5iss2pp95-104

Abstract

This study aims to determine the types of errors students face when solving math problems. First, review the error types based on Watson's criteria and student learning styles. This study uses an explanatory sequential design model. Data analysis techniques include Quantitative data analysis techniques, descriptive statistics, and inferential statistics. At the same time, the qualitative data analysis techniques include; data reduction, data presentation, and conclusion. The results showed that the errors based on Watson's criteria and learning styles obtained were based on student responses, including; Inappropriate Data 40%, Omitted Conclusion 20%, Response Level Conflict 40%, and Above Other 40%. Furthermore, the types of errors obtained in classroom learning include Inappropriate Data 25%, Omitted Conclusion 50%, and Skill Hierarchy Problems 25%. In the visual learning pattern, there are five error classes: Inappropriate Data 9%, Omitted Conclusion 55%, Response Level Conflict 18%, Skill Hierarchy Problem 27%, and Above Other 18%. Several factors influence the error, including; the decline in students' motivation, interest, and thinking skills. Efforts can be made to minimize student errors, including increasing practice on story questions and eliminating students' negative mindset towards learning mathematics
Co-Authors Andi Aras Buhaerah Buhaerah M S Dangnga ZulFiqar Busrah