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All Journal AlphaMath: Journal of Mathematics Education Jurnal Teladan: Jurnal Ilmu Pendidikan dan Pembelajaran Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika (JRPIPM) Mosharafa: Jurnal Pendidikan Matematika Indonesian Journal of Mathematics Education Journal of Mathematical Pedagogy (JOMP)
Uripno, Gusti
Universitas PGRI Ronggolawe
Education Mathematics Social Sciences Other

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Students’ Combinatorial Thinking Processes in Solving Mathematics Problem Uripno, Gusti; Rosyidi, Abdul Haris
Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika (JRPIPM) Vol 2, No 2 (2019): JRPIPM April 2019 Volume 2 Nomor 2
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jrpipm.v2n2.p80-92

Abstract

Combinatorial thinking is a way of thinking in solving combinatory problems. Combinatory problems are one of the difficult problems for students to solve. This study aims to analyses students? combinatorial thinking processes in solving problems. Given two combinatory problems that consist of problems with multiplication rule and combination. The Problems were given to two 11th grade senior-high school students. The results obtained were that there was a tendency for male Participants to do the two different ways which are direct counting and using diagram. The female participants did the work with one way which is direct counting. On more complex issues, namely about combination, students' thinking models go through stages of set of outcomes. From this research, it is expected that combinatory material learning is emphasized on the discovery of formulas by students themselves inductively, especially deductively. So that in this case the students interpret the combinatory formula more.
Students Combinatorial Thinking Processes in Solving Mathematics Problem Gusti Uripno; Abdul Haris Rosyidi
Jurnal Riset Pendidikan dan Inovasi Pembelajaran Matematika (JRPIPM) Vol. 2 No. 2 (2019): JRPIPM April 2019 Volume 2 Nomor 2
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jrpipm.v2n2.p80-92

Abstract

Combinatorial thinking is a way of thinking in solving combinatory problems. Combinatory problems are one of the difficult problems for students to solve. This study aims to analyses students combinatorial thinking processes in solving problems. Given two combinatory problems that consist of problems with multiplication rule and combination. The Problems were given to two 11th grade senior-high school students. The results obtained were that there was a tendency for male Participants to do the two different ways which are direct counting and using diagram. The female participants did the work with one way which is direct counting. On more complex issues, namely about combination, students' thinking models go through stages of set of outcomes. From this research, it is expected that combinatory material learning is emphasized on the discovery of formulas by students themselves inductively, especially deductively. So that in this case the students interpret the combinatory formula more.
Students’ Combinatorial Thinking Error in Solving Combinatorial Problem Gusti Uripno; Tatag Yuli Eko Siswono; Endah Budi Rahaju; Arief Budi Wicaksono
Indonesian Journal of Mathematics Education Vol. 6 No. 1 (2023): Indonesian Journal of Mathematics Education
Publisher : Universitas Tidar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31002/ijome.v6i1.589

Abstract

Combinatorial thinking errors describe students’ difficulties and obstacles in solving combinatorial problems. This study aims to describe the errors experienced by students in solving combinatorial problems in terms of combinatorial thinking processes. This research involved two subjects who were 12th grade high school students at a school in Gresik, Indonesia. The students have already taken a combinatorics course. Data collection was conducted using the think-aloud observation method and task-based interviews. Both methods of data collection were conducted to validate the data using the triangulation method. The two subjects experienced similar errors. The research shows that the filling slots method is a simple and easy way for students to understand, but problems arise when students cannot understand the meaning of the questions and input the correct numbers for the problem. The combinatorial thinking error includes the general counting process and vertical upward formulas or expressions. The general counting process error is generating a number that represents the given aspects of the problem and the vertical upward formula/expression is identifying the concept that fits the problem. This research suggests enhancing students understanding of number representation when teaching the filling slot method. The teacher should illustrate some of the multiplication rule and addition rule examples to help students distinguish between these two fundamental rules. Further research is needed to provide solutions to the constraints experienced by students in solving combinatorial problems.
Berpikir Kombinatorik: Relevansi AI dengan Model Pembelajaran Matematika Uripno, Gusti; Yuliastuti, Rita; Nurfalah, Edy; Islami, Irma Fauztina
Jurnal Teladan: Jurnal Ilmu Pendidikan dan Pembelajaran Vol 9 No 2 (2024): Jurnal Teladan Vol.9. No.2 November 2024
Publisher : FKIP Unirow Tuban

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55719/jt.v9i2.1510

Abstract

This development study uses a qualitative approach and Didactic Engineering (DE) research methods. The aim of this research is to develop an AI-based learning model by combining discovery and problem based learning models involving mathematics students at PGRI Ronggolawe University, Tuban. AI or artificial intelligence is a tool that needs to be optimized in various fields, especially in the field of mathematics education. Meanwhile, mathematics education has issues related to problem solving on discrete mathematics topics. Starting from this issue, this research tries to offer a solution, the result of which is an AI-assisted blended learning model to improve combinatorial thinking. Through the combination of these models, a combination of syntax is obtained, namely: (1) Orientation; (2) Organization; (3) Exploration; (4) Execution; (5) Evaluation; (6) Generalization. This combination also considers the methods used, namely online and offline. Stages (1) and (2) are carried out offline via the LMS and quiz provider application. Meanwhile, Stages (3) and (4) were carried out involving Question AI. Stage (3) is carried out with the Geogebra alternative auxiliary application. Then stages (4) and (5) are carried out using technology-assisted presentations.
Bibliometrics Analysis of AI Integration in Mathematics Teaching Nasri Tupulu; Konstansia Hermiati; Gusti Uripno; Siti Suprihatiningsih; Rizki Kurniawan Rangkuti
Mosharafa: Jurnal Pendidikan Matematika Vol. 13 No. 2 (2024): April
Publisher : Department of Mathematics Education Program IPI Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31980/mosharafa.v13i2.1699

Abstract

Studi literatur ini bertujuan untuk menganalisis tren penelitian dengan menggunakan analisis bibliometrik yang terkait dengan Kecerdasan Buatan (AI) dalam pengajaran matematika. Pentingnya AI dalam pengajaran matematika tidak sesuai dengan banyaknya penelitian tentang hal tersebut. Sehingga penelitian ini disusun dengan tujuan untuk mengidentifikasi penelitian berkaitan dengan integrasi AI dalam pengajaran matematika selama 10 tahun terakhir.  Kata kunci yang digunakan untuk mengumpulkan artikel adalah “artificial intelligence” dan “mathematics teaching” dan diperoleh 460 dokumen di database scopus. Penelitian ini dilakukan dengan membatasi jumlah dokumen tergantung pada tahun, bahasa, dan jenis artikel. Batas tahun pada tahun 2014 hingga 2024, bahasa dibatasi hanya bahasa Inggris, dan dokumen dibatasi hanya pada jenis artikel. Jumlah dokumen dalam dekade terakhir meningkat dari 6 dokumen menjadi 26 dokumen. Zhongda Sun, yang berkecimpung dalam kecerdasan komputer, adalah penulis yang paling banyak dikutip. Negara paling produktif adalah Tiongkok yang menyalip jumlah publikasi Australia pada tahun 2021. Kecerdasan buatan dalam pengajaran matematika populer dalam ilmu sosial dan ilmu komputer dengan topik yang paling populer adalah siswa, kecerdasan buatan, dan guru. This literature study aims to analyze research trends by using bibliometrics analysis that related to Artificial Intelligence (AI) in mathematics teaching. The impact of AI in mathematics teaching did not match to the number of mathematics teaching research. So, this bibliometric study conducted in order to identify AI integration in mathematics teaching in last decade. Article gathered by two keywords, which are “artificial intelligence” and “mathematics teaching”and found 460 documents in scopus database. This study conducted by limiting the number of documents depend on years, language, and article type. The years limit in 2014 to 2024, languages limit to english only, and the documents limit to article type only. The number of documents in the last decade is increasing from 6 documents into 26 documents. Zhongda Sun, that concern in computer intelligence, is the most cited author. The most productive country was China that overtake Australia’s number of publications in 2021. Artificial intelligence in mathematics teaching was popular in social science and computer science and the most popular topics are students, artificial intelligence, and teacher.
Artificial Intelligence Integration: Error Self-Reflection in Solving Integral Problems Uripno, Gusti; Suprihatiningsih, Siti; Rangkuti, Rizki Kurniawan
AlphaMath : Journal of Mathematics Education Alphamath: Vol. 10, No. 2, November 2024
Publisher : Department of Mathematics Education, Universitas Muhammadiyah Purwokerto, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/alphamath.v10i2.23133

Abstract

Integrity has had plenty of impact on human civilization development, especially in the development of human technology. The primary role of an integral is not well supported by students’ skill in solving integral problems. Due to this fact, mathematics educators need solutions. Artificial Intelligence (AI) integration is one of the solutions that mathematics educators can choose. This qualitative descriptive research aims to explore students' mistakes in solving integral problems with the help of  Photomath. This research will describe student mistakes and explain how students realize mistakes during rework assisted by Photomath. This research involved ten mathematics students who joined an integral course at a university in Indonesia. The errors were analyzed based on Newman error analysis. Errors found based on research results include (1) Comprehension and transformation, (2) Process skills, and (3) Encoding. This research found that comprehension errors have implications for transformation. Students who make comprehension errors will cause transformation errors. Meanwhile, the subject's errors in the previous stage affect the encoding stage. Apart from the errors already mentioned, errors were also found due to carelessness, which was not a significant part of Newman's error analysis.
Analysis of Artificial Intelligence Assisted Proof Process Through Principle of Mathematical Induction in Real Analysis Course Lestari, Isnawati Lujeng; Sari, Mayang; Uripno, Gusti; Suprihatiningsih, Siti; Hariyanti, Firda; Bonyah, Ebenezer
Journal of Mathematical Pedagogy (JoMP) Vol. 6 No. 2: July 2025
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jomp.v6n2.p94-102

Abstract

The low proficiency of Mathematics Education students in constructing mathematical proofs, especially using the principle of mathematical induction, highlights the need for enhanced learning approaches. One promising method is the integration of Artificial Intelligence (AI) into the proof process within Real Analysis courses. This study aims to describe how students carry out mathematical induction proofs with the assistance of AI. Ten voluntary students enrolled in Real Analysis participated in an initial test involving divisibility problem. From this group, two students were selected through maximum variation sampling based on their answer diversity and communication skills. One student employed a modulo-based approach, while the other used the divisibility-definition concept. Overall, the results demonstrate that AI significantly supports students in understanding problems, planning proofs, implementing strategies, and revising their reasoning. AI played a critical role in concept generation, solution evaluation, and embedded reflection across each stage of Polya’s problem-solving framework, combined with the three aspects of AI-assisted proof: construction, evaluation, and revision
Co-Authors Abdul Haris Rosyidi Abdul Haris Rosyidi Arief Budi Wicaksono Bonyah, Ebenezer Edy Nurfalah Endah Budi Rahaju Firda Hariyanti Islami, Irma Fauztina Konstansia Hermiati Lestari, Isnawati Lujeng Mayang Sari Nasri Tupulu Rita Yuliastuti Rizki Kurniawan Rangkuti Siti Suprihatiningsih Tatag Yuli Eko Siswono