Claim Missing Document
Check
Articles

Meta-Analysis: The Significance Of The Search, Solve, Create, And Share Model In Enhancing Students' Mathematical Problem-Solving Ability Erina Nurhalisha; Zaenuri Zaenuri; Kristina Wijayanti; Scolastika Mariani; Isnaini Rosyida
Mathline : Jurnal Matematika dan Pendidikan Matematika Vol. 10 No. 2 (2025): Mathline : Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/mathline.v10i2.927

Abstract

Mathematical problem-solving ability is an important ability that students must have to master mathematics learning and solve problems. The low mathematical problem-solving ability of students is often caused by the application of conventional learning models. One model that can improve students' mathematical problem-solving abilities is the Search, Solve, Create, and Share (SSCS) learning model. The Search, Solve, Create, and Share (SSCS) learning model emphasizes active student participation and problem-solving, significantly enhancing students' mathematical problem-solving abilities. This study was conducted to determine the effectiveness of the SSCS learning model in improving students' capacity for solving mathematical problems. The method employed was meta-analysis. The analysis of eight articles revealed a consistently high effect size across all of them.  In addition, the combined effect size of the eight articles was 1.199, which is included in the high category. Based on the results of the t-test, the values ​​of tcount = 30.14 > 1.648 = ttable, so H0 is rejected, indicating that students who engage with the SSCS learning model demonstrate a significantly higher average capability in solving mathematical problems than those who do not use it. Therefore, the SSCS learning paradigm presents a viable alternative for enhancing students' mathematical problem-solving skills.
Developing a Hypothetical Learning Trajectory for Eighth Graders’ Statistical Understanding through Techno-Ethno-Realistic Mathematics Education Farida Nursyahidah; Wardono Wardono; Scolastika Mariani; Kristina Wijayanti
Proceedings of International Conference on Science, Education, and Technology Vol. 12 (2026)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Statistics is an important aspect of mathematics that supports the development of students' cognitive abilities. However, understanding statistical concepts often becomes an obstacle for students. This article aims to develop and present a hypothetical learning trajectory on statistics using a techno-ethno-realistic mathematics education (TE-RME) approach. The research was conducted using a design research method that comprises three main stages: preliminary design, design experiments, and retrospective analysis. This research involved eighth-grade students at a junior high school in Semarang. The focus of this article is on the initial design stage, namely the development of a hypothetical learning trajectory that includes three main activities: (1) collecting, presenting, and interpreting data through culturally context-based video observation and spreadsheet, (2) determining the central tendency measures, and (3) determining the measure of data distribution. The series of activities in this learning trajectory is designed to help students build a deeper understanding of statistical concepts while fostering an appreciation of local culture and diversity in mathematical thinking. This hypothetical learning trajectory is designed to be implemented in experimental classes and research-based teaching using TE-RME to improve students' statistical understanding.