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Wati Susilawati
Prodi Pendidikan Matematika, UIN Sunan Gunung Djati Bandung
Religion Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Economics, Econometrics & Finance Education Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

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The Role of Geogebra Software in Stimulating Students' Mathematical Problem Solving Ability Muhammad Tandhimul Haq; Wati Susilawati; Iyon Maryono; T. Tutut Widiastuti, A
Gunung Djati Conference Series Vol. 12 (2022): Mathematics Education on Research Publication (MERP I)
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (266.118 KB)

Abstract

The reasoning ability of students in terms of solving mathematical problems, especially those related to the side of everyday life, is still very low. So that when face-to-face learning is suddenly replaced with online learning, it makes education actors, especially teachers as educators, difficult. Which causes the decline in students' reasoning abilities to solve problem solving problems due to changing learning activities due to the pandemic. This literature study research aims to show an increase in students' mathematical problem solving ability using Geogebra Software as a help application that can be a solution for teacher confusion and to improve problem solving abilities. The method that will be used in the research is literature study. The stages used are taking and collecting various sources that can support from books, websites, journals, theses and others, whose validity can be justified and then processed into a theoretical and accurate conclusion. Results Based on the analysis of the data obtained, the results show that the use of software with the help of the Geogebra application is considered effective and can be a solution to improve abilities in terms of solving mathematical problems
Student Problems in Mathematics Learning in Solving Mathematical Problems Lutfia Dwi Jayanti; Wati Susilawati; T. Tutut Widiastuti, A; Ida Nuraida
Gunung Djati Conference Series Vol. 12 (2022): Mathematics Education on Research Publication (MERP I)
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (218.412 KB)

Abstract

The objective of this research was to determine and assess students' struggles with mathematical knowledge construction. The methodology employed in this study is based on literature study by reading or researching various sources that are considered relevant such as books, national journals, and others related to research studies. The findings of this literature review reveal that students' problem-solving abilities in mathematics education are still somewhat limited. As evidenced by a few of the students' problems in learning mathematics, especially in solving math problems, includes a sense of enthusiasm for mathematics on the side of students, the lack of precise use of learning methods by teachers in delivering material, and there are still many student errors in answering math problem solving problems
Efektivitas Problem Based Deep Learning dalam Mengembangkan Kemampuan Pemecahan Masalah Matematis Siswa Indonesia Dina Syarifatul Maula; Reyhana Latifatunnisa; Fathiya Kamila Azhar Shaumy; Shaumy Shaumy; Yayu Nurhayati Rahayu; Wati Susilawati
Jurnal Mercumatika : Jurnal Penelitian Matematika dan Pendidikan Matematika Vol 10 No 2 (2026)
Publisher : Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26486/dt4sz561

Abstract

This study aims to examine the effectiveness of the Problem Based Deep Learning (PBDL) model in developing Indonesian students' mathematical problem-solving skills through the Systematic Literature Review (SLR) approach. The background of this study is the low ability of students to link mathematical concepts to everyday contextual situations, especially in the aspect of problem solving. Analysis was conducted on accredited articles from databases such as Sinta, Google Scholar, and ResearchGate published in the last five years. The results of the study indicate that the implementation of PBDL is consistently more effective than conventional methods in improving critical, creative, collaborative thinking skills, and deep mathematical understanding. The success of PBDL implementation is influenced by contextual problem design, small group-based learning strategies, and student independent reflection. However, several limitations were also identified, such as teacher readiness in implementing this approach, variations in research designs that make it difficult to generalize results, limited access to technology in certain areas, and the lack of research examining students' affective and metacognitive aspects. Therefore, systematic integration of PBDL into the mathematics curriculum and teacher training based on Higher Order Thinking Skills (HOTS) is highly recommended. Further studies are recommended to explore the long-term effectiveness of PBDL across educational levels and socio-cultural contexts.
Problematika Adaptasi Pendekatan Deep Learning Dalam Pembelajaran Matematika Di Indonesia : Jurnal Penelitian Matematika dan Pendidikan Matematika Dhelinda Nuriatul Ainie; Muhammad Alfaf Aghnia Muthmain; Ida Nuraida; Wati Susilawati
Jurnal Mercumatika : Jurnal Penelitian Matematika dan Pendidikan Matematika Vol 10 No 2 (2026)
Publisher : Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26486/kps2c272

Abstract

The digital transformation in education has encouraged the integration of artificial intelligence technologies, including the deep learning approach in mathematics learning. This study aims to identify the challenges in adapting deep learning in Indonesia through a Systematic Literature Review (SLR) method. The findings indicate that while this approach offers great potential for enhancing personalization and effectiveness in mathematics education, its implementation is hindered by limited infrastructure, low teacher competency in technology, and resistance to innovative methods. The study also reveals that institutional readiness and teacher training are crucial for successful implementation. Therefore, a contextual, gradual, and collaborative adaptation model is needed to optimize the integration of deep learning into mathematics education in Indonesia
Hubungan Literasi Sains dan Berpikir Kritis dengan Self-Awareness Siswa pada Materi Pencemaran Lingkungan Lusy Fajarwati; Neneng Windayani; Wati Susilawati
Jurnal BIOEDUIN : Program Studi Pendidikan Biologi Vol 15 No 1 (2025): Bioeduin Februari
Publisher : Department of Biology Education UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/bioeduin.v15i1.44146

Abstract

This study aims to analyze the relationship between science literacy, critical thinking skills, and students' self-awareness in learning about environmental pollution. The research method used is a quasi-experiment involving 32 seventh-grade students as respondents. Data were collected through a problem-based test consisting of 20 multiple-choice questions to measure science literacy and critical thinking skills, as well as a Likert scale questionnaire to evaluate self-awareness. Data analysis was performed using multiple regression techniques. The results of the study show that science literacy and critical thinking skills have a positive and significant relationship with students' self-awareness. The better the students' science literacy and critical thinking skills, the higher their self-awareness, especially in understanding and addressing environmental issues. The conclusion of this study is that improving science literacy and critical thinking skills significantly enhances students' self-awareness, which is an important element in issue-based environmental learning. This research provides insights for educators to integrate science literacy and critical thinking skills into relevant and contextual learning strategies. This effort is expected to create a generation of students who are more aware of their roles and responsibilities in preserving the environment.
Enhancing Students’ Mathematical Problem-Solving Ability Through The Problem Posing and Solving Learning Model Assisted by Heyzine Ria Setiani Habbinnur Rizki; Wati Susilawati; T. Tutut Widiastuti A; Ika Puspitawati
Mathline : Jurnal Matematika dan Pendidikan Matematika Vol. 10 No. 4 (2025): Mathline : Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/mathline.v10i4.1047

Abstract

The integration of problem posing and problem-solving learning facilitates problem situations that require students to actively engage in tackling non-routine mathematical challenges. However, some students are still not well-adapted to this type of problem-solving, making it potentially less effective when applied simultaneously. This study aims to analyze students’ mathematical problem-solving abilities through problem-posing and problem-solving learning assisted by Heyzine. This research employed a quasi-experimental method. The population consisted of eleventh-grade students from a senior high school in Bandung Regency, with classes XI D1, XI D2, and XI E1, each comprising 37 students selected through random sampling. The findings of this study include: (a) the design of the Jucama learning model was successfully implemented, resulting in a Heyzine-assisted student worksheet (LKPD) that met the criteria of being highly valid and suitable for use; (b) the implementation process of the Jucama learning activities assisted by Heyzine improved significantly and achieved a very good category; (c) there was a notable increase in problem-solving ability among students who received Heyzine-assisted Jucama learning compared to those who received Jucama learning without Heyzine.
Kecerdasan Buatan dalam Pendidikan Matematika: Tinjauan Sistematis tentang Pemecahan Masalah Matematika dan Pembelajaran Mandiri Siswa Ridho Mudjib; Rifa Rizqiyani; Tika Karlina Rachmawati; Wati Susilawati
SJME (Supremum Journal of Mathematics Education) Vol 10 No 2 (2026): 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.v10i2.13331

Abstract

Artificial Intelligence (AI) is increasingly integrated into mathematics education to support personalized, adaptive, and student-centered learning. However, evidence concerning its simultaneous contribution to students’ mathematical problem-solving skills and self-directed learning remains fragmented. This study aimed to systematically analyze publication trends, forms of AI implementation, contributions to mathematical problem solving and self-directed learning, and research gaps in AI-supported mathematics education. A Systematic Literature Review was conducted following the PRISMA 2020 guidelines. Relevant journal articles published between 2021 and 2025 were retrieved from Scopus, OpenAlex, and Google Scholar using predefined search strings. Studies were selected using the PICOC framework and evaluated through quality assessment based on methodological clarity, the explicit description of AI technologies, and their relevance to the research questions. Of 121 initially identified records, 53 eligible open-access articles were included and analyzed thematically. The findings revealed a substantial increase in publications, from one article in 2021 to 25 articles in 2025. AI chatbots were the most frequently examined technology, followed by other AI-based platforms, adaptive learning systems, intelligent tutoring systems, and machine-learning applications. AI supported mathematical problem solving by providing scaffolding, immediate feedback, strategy guidance, and systematic visualization of solution processes. It also promoted self-directed learning through personalized pathways, flexible access, adaptive feedback, learning-pace regulation, and increased confidence. Nevertheless, only a limited number of studies examined both outcomes simultaneously. Significant challenges included teachers’ insufficient digital literacy, unequal access, additional instructional workload, students’ overreliance on AI, data-privacy concerns, and algorithmic hallucinations. Future research should develop empirically validated pedagogical models, conduct meta-analyses, and establish ethical guidelines to ensure that AI functions as a safe, inclusive, and sustainable cognitive facilitator in mathematics learning.
Co-Authors Akhmad Nurul Mutamam Amelia Muhibatul Milah Annisa Eka Fitriani Hidayat Dhelinda Nuriatul Ainie Dina Syarifatul Maula Fathiya Kamila Azhar Shaumy Hamdan Sugilar Ika Puspitawati Islah Nurul Fadillah Juariah Juariah Lusy Fajarwati Lutfia Dwi Jayanti M N Abdullah Maryono, Iyon Muhammad Alfaf Aghnia Muthmain Muhammad Tandhimul Haq Nabila Dwi Utari Nuraida, Ida Rahayu Kariadinata Rahayu, Yayu Nurhayati Reyhana Latifatunnisa Ria Setiani Habbinnur Rizki Ridha Abdullah Ridha Abdullah Ridho Mudjib Rifa Rizqiyani Riva Lesta Ariany Rozadira Haqi Shaumy Shaumy T. Tutut Widiastuti, A Tika Karlina Rachmawati Tutut Widiastuti Tutut Widiastuti Anisa