I The Impact of Computational Thinking Skills on Mathematics Learning – Systematic Literature Review

The Impact of Computational Thinking Skills on Mathematics Learning – Systematic Literature Review

A SYSTEMATIC LITERATURE REVIEW OF THE PROBLEM-BASED LEARNING ON STUDENTS’ MATHEMATICAL COMMUNICATION SKILLS IN PRIMARY AND SECONDARY EDUCATION

Mathematical communication skills are among the most important skills in mathematics education, helping students convey ideas, explain their thought processes, and represent concepts mathematically. The development of these skills remains a focus of various studies in mathematics education. The purpose of this study is to systematically analyze research trends regarding the application of the PBL model to students’ mathematical communication skills. This study employed a Systematic Literature Review (SLR) method with a qualitative descriptive approach and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The literature search was conducted via the Google Scholar database using the Publish or Perish version 8 application to identify publications from 2022 to 2026. From an initial search yielding 600 articles, 16 articles that met the inclusion and exclusion criteria were selected for analysis. The data were analyzed descriptively through a process of extraction, categorization, and synthesis based on educational level, instructional content, research methods, and research findings. The results indicate that the majority of studies on the application of the PBL model to mathematical communication skills were conducted at the junior high school level, accounting for 56% of the total. Regarding research methods, quantitative methods were the most prevalent, particularly quasi-experimental designs, which accounted for 62%. The variety of instructional materials used was also quite diverse. Overall, the research findings indicate that the implementation of the PBL model effectively improves students’ mathematical communication skills. Additionally, several studies also show that the use of instructional media in PBL can enhance student engagement and support the process of mathematical communication in the classroom. Thus, the PBL model can be considered one of the relevant instructional models to help develop students’ mathematical communication skills.

IMPLEMENTATION AND RESEARCH TRENDS OF PROBLEM-BASED LEARNING IN MATHEMATICS EDUCATION AT SCHOOL: A SYSTEMATIC LITERATURE REVIEW

Problem-Based Learning (PBL) is widely used in mathematics education to encourage active student participation and the development of higher-order thinking skills. Therefore, this study aims to examine the implementation and research trends of Problem-Based Learning (PBL) in school mathematics learning through a Systematic Literature Review (SLR). The review followed the PRISMA framework and searched articles in the Scopus database published during 2020-2025. From 200 identified records, eight articles met the inclusion criteria and were included in the final analysis. The findings reveal that PBL is generally implemented through problem orientation, group organization, investigation, presentation, and reflection or evaluation, although variations exist in learning context and instructional integration. In addition, PBL research is still dominated by senior high school contexts, quasi-experimental methods, and higher-order cognitive outcomes, particularly problem-solving and critical thinking skills. These findings indicate that while PBL has been implemented consistently in mathematics education, opportunities remain for broader research across educational levels, learning outcomes, and instructional integrations. Keywords: Mathematics Education, PRISMA, Problem-Based Learning, Systematic Literature Review

Review Journal of Higher-Order Thinking and Metacognition

ANALYSIS OF THE RELATIONSHIP BETWEEN HIGHER ORDER THINKING SKILLS AND SCIENTIFIC REASONING SKILLS IN CHEMISTRY LEARNING

Higher Order Thinking Skills (HOTS) and Scientific Reasoning Skills (SRS) play a significant role in helping students develop a comprehensive understanding of chemistry concepts. However, studies examining the relationship between HOTS and SRS remain limited. Such studies are essential for providing a theoretical foundation for the development of chemistry instruction in schools. Therefore, this study aims to analyze the relationship between HOTS and SRS in chemistry learning. This study employed a narrative literature review approach, with HOTS and SRS as the focus of the review. Relevant literature was identified through the Google Scholar database, covering publications from 2020 to 2026, using the keywords "higher order thinking skills" OR "scientific reasoning skills" AND "chemistry learning." A total of 27 relevant articles were selected for analysis. The data were analyzed by synthesizing and presenting the findings of previous studies in a narrative and descriptive manner. The review revealed that scientific reasoning skills constitute an essential component of HOTS that students need to develop a meaningful and comprehensive understanding of chemistry concepts. Furthermore, the dimensions of scientific reasoning contribute to the development of students' HOTS, thereby supporting the acquisition of essential twenty-first-century skills.

Analysis of Mathematical Computational Thinking Skills in Statistics Courses in Relation to High School Students' Learning Interest

Purpose: Computational thinking is increasingly recognized as a critical competency in mathematics education, particularly for enabling students to formulate, analyze, and solve complex problems. However, students’ engagement in computational thinking may vary according to their level of learning interest. Methodology: This qualitative case study examined students’ mathematical computational thinking in statistics across different levels of learning interest. Participants were 31 eleventh-grade students at a senior high school in East Jakarta, Indonesia. Based on a learning-interest questionnaire, students were classified into high, moderate, and low interest groups, from which three representative students were purposively selected for in-depth analysis. Data were collected through a mathematical computational thinking test and semi-structured interviews and analyzed thematically using four indicators: decomposition, pattern recognition, abstraction, and algorithmic thinking. Findings: The findings demonstrated differentiated computational thinking profiles across the three levels of learning interest. The highly interested student demonstrated all four indicators and applied systematic, coherent, and logically structured problem-solving strategies. The moderately interested student exhibited adequate conceptual understanding but experienced difficulties in articulating complete and logically organized solution procedures. The student with low learning interest encountered difficulties across all four indicators, particularly in identifying relevant information, recognizing patterns, abstracting essential concepts, and constructing logical solution procedures. Significance: Within the context of this study, learning interest was associated with variations in students’ mathematical computational thinking in statistics. These findings highlight the importance of instructional approaches that concurrently foster learning interest and strengthen students’ computational thinking capabilities in mathematical problem solving.