Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal JPPM (JURNAL PENELITIAN DAN PEMBELAJARAN MATEMATIKA) Pendas : Jurnah Ilmiah Pendidikan Dasar
Ilmiyati Rahayu
Universitas Sultan Ageng Tirtayasa
Mathematics Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
PENGARUH MODEL PEMBELAJARAN BERBASIS MASALAH DAN KEMANDIRIAN BELAJAR TERHADAP KEMAMPUAN PEMECAHAN MASALAH MATEMATIKA DENGAN MENGONTROL PENGETAHUAN AWAL SISWA Yuyu Yuhana; Ilmiyati Rahayu
JPPM (Jurnal Penelitian dan Pembelajaran Matematika) Vol 14, No 2 (2021): JPPM (Jurnal Penelitian dan Pembelajaran Matematika) Volume 14 Nomor 2 Agustus
Publisher : Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (372.613 KB) | DOI: 10.30870/jppm.v14i2.12980

Abstract

The purpose of this study in general is to determine the effect of the implementation of problem-based learning models and independent learning on mathematical problem solving abilities by controlling students' prior knowledge. This research was conducted in class X semester 1 (one) of the 2015/2016 academic year at SMA Negeri 2 Kota Serang and SMA Negeri 1 Ciruas. This study uses an experimental method with a 2×2 factorial design or a treatment by level 2 x 2 design, because of the treatment and the level. The affordable population in this study were all students of class X MIA (Mathematics and Natural Sciences) SMA Negeri 2 Kota Serang and SMA Negeri 1 Ciruas. Sampling was taken by multistage random sampling. The research data include: Data analysis was carried out both descriptively and inferentially. The results of this study indicate that there is an effect of problem-based learning model and independent learning on mathematical problem solving ability by controlling students' prior knowledge with a significance level of 0.00.
SYSTEMATIC LITERATURE REVIEW: PERAN AI SEBAGAI STIMULAN SRL SISWA DAN KEMAMPUAN PEMECAHAN MASALAH MATEMATIS PADA TAHUN 2024-2026 Fahri Zulkarnain Pardamean Pane; Heni Pujiastuti; Ilmiyati Rahayu
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 11 No. 02 (2026): Volume 11 No. 2, Juni 2026 Release
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i02.47796

Abstract

This systematic literature review aims to analyze the role of Artificial Intelligence (AI) as a stimulus for students' self-regulated learning (SRL) and mathematical problem-solving abilities, given the persistent gap between the demand for 21st-century problem-solving skills and traditional instructional methods that make students passive. The study employs a Systematic Literature Review (SLR) following PRISMA guidelines, with article searches conducted on Google Scholar using Publish or Perish software and keywords combining "Artificial Intelligence," "Self-Regulated Learning," and "Mathematical Problem Solving." From an initial 200 articles, 15 were selected based on inclusion criteria, including publication years 2024-2026, full-text availability, and focus on at least two of the three main variables. The results indicate that AI significantly enhances SRL by enabling personalized, adaptive learning and providing instant feedback, visualizations, and step-by-step guidance, thereby improving students' initiative and problem-solving skills. However, the findings also reveal critical gaps: without metacognitive mediation, AI risks becoming an "answer provider" rather than a "thinking partner," leading to overreliance. Additionally, most studies lack rigorous designs (e.g., RCT), have limited sample sizes, neglect teacher readiness and infrastructure constraints, and rarely examine specific SRL dimensions such as metacognition or help-seeking behavior. AI tools like ChatGPT, Gemini, Mathos AI, and Photomath dominate the literature, yet valid and reliable instruments to measure AI-assisted problem-solving behavior remain underdeveloped. This review concludes that while AI holds transformative potential, its effectiveness depends on integrating metacognitive strategies, strengthening teacher digital literacy, improving infrastructure, and conducting longitudinal or experimental studies to establish causal evidence.  
Co-Authors Fahri Zulkarnain Pardamean Pane Heni Pujiastuti Yuyu Yuhana