Proceeding International Conference on Mathematics and Learning Research

Integrating Robotics into Mathematics Education: Applications, Teaching Strategies, and Attitude Assessment in Primary School Students

Cesar Augusto Hernández Suárez — 2024-10-30

This study addresses the implementation of robotics applications in the teaching of mathematics and its impact on the attitudes of students and teachers in elementary schools in Cúcuta, Colombia. Through a mixed methodology combining quantitative and qualitative approaches, 120 teachers and 300 students participated. The quantitative results reveal that, after 12 weeks of using robotics applications, 75% of teachers considered robotics as an effective tool for teaching mathematics, compared to 40% prior to the intervention. Also, students experienced a significant improvement in their attitude towards mathematics, with a 50% to 20% reduction in insecurity about mathematical concepts and a 65% increase in motivation and enjoyment of learning. Qualitative analysis showed that robotics facilitates understanding of abstract concepts and fosters active and collaborative learning, although some teachers faced initial technical barriers. Despite these difficulties, teachers reported that robotics promotes key skills such as problem solving and teamwork, even in educational contexts with limited resources. Statistical analysis, based on t-tests and ANOVA, indicated that differences in perceptions and attitudes before and after implementation were statistically significant (p < 0.01), with no notable differences between school types. These results suggest that robotics is effective in a variety of educational contexts, regardless of school type. In conclusion, this research demonstrates that educational robotics can transform mathematics instruction, improving both academic outcomes and student motivation. The findings suggest that robotics should be integrated into the mathematics curriculum at the national level, accompanied by teacher training programs that address technical and pedagogical challenges. In addition, future studies are recommended to assess the long-term impact of robotics on students' academic and emotional performance, and how it can contribute to reducing educational gaps.

Analysis of the Use Intelligent Guess and Test Strategy in Solving Realistic HOTS Problems for Junior High School Students

Kadek Adi Wibawa — 2024-10-30

There are various strategies for solving realistic HOTS-type problems, one of which is the intelligent guess and test strategy. However, students have not yet fully understood the use of this strategy. Therefore, this study aims to analyze the use of the intelligent guess and test strategy in solving realistic HOTS-type problems. This research employs a qualitative approach with a case study type. The study was conducted at SMP Widiatmika in Badung Regency, Bali Province, involving 27 eighth-grade students. Data collection techniques included tests and documentation. Data analysis employed qualitative content analysis, thematic coding, constant comparative analysis, and narrative analysis. The results of this study indicate that 96.3% of students chose to solve problems using an arithmetic approach, while 3.7% used an algebraic approach. The study also revealed that students faced difficulties in solving realistic HOTS-type problems, particularly in understanding the problems and determining the methods to use. Furthermore, the study identified three patterns in the use of the intelligent guess and test strategy: incomplete, complete but indirect, and complete and direct. The incomplete pattern occurs when students determine a formula without a strong basis to arrive at the final answer to a problem. The second pattern, complete but indirect, begins after the student understands the problem and makes the most reasonable guess, followed by testing. The student then analyzes the test results and makes the next guess based on the initial guess. This process is carried out cyclically until the student finds the most accurate guess. The third pattern, complete and direct, occurs when the student makes a direct guess because they fully understand the problem and have considered various aspects of the issue. The student tests the first guess and obtains the expected result.

Praxeological Analysis of the Mathematics Textbook on the Topic of Translation

Talisadika Serrisanti Maifa — 2024-10-30

This study analyzes the sequence of tasks in the Mathematics textbook to identify learning obstacles associated with the concept of translation, with a specific focus on the definition of translation. This analysis employs the theory of praxeology, a key concept in the Anthropological Theory of Didactics (ATD). The findings highlight three potential didactical obstacles and one potential epistemological obstacle within the task sequence. Therefore, these findings should be considered by teachers to anticipate and minimize potential obstacles in teaching the concept of translation.

Systematic Literature Review: Students' Self-Regulated Learning at Different Levels of Education in Indonesia

Kunthy Ley Leana — 2024-10-30

Self-regulated learning (SRL) is an important skill for students. Students who have SRL can regulate and control themselves in the learning process, especially when dealing with school assignments. The purpose of this study was to review the literature on students' SRL at different levels of education in Indonesia. This study is qualitative and uses the systematic literature review method. The data collection technique used in this study was a literature study and documentation sourced from articles using the keywords "self-regulated learning", "mathematics", and "students". Articles were screened using Publish or Perish software with Google Scholar, Crossref, and Semantic Scholar databases. A total of 2993 works of literature were screened and analyzed using Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) so that 9 articles were obtained representing each level of education. The study results showed differences in students' SRL levels at each level of education. Elementary school students have relatively low SRL. High school students have SRL levels varying between moderate and low.

STEAM-H to Support Agribusiness Students' Work Skill

Ai Tusi Fatimah — 2024-10-30

The study focuses on the importance of work skills for students at Agribusiness Vocational High Schools in meeting the demands of 21st-century competencies. It explores how the STEAM-H (Science, Technology, Engineering, Agriculture, Mathematics, Health) approach can assist in developing these work skills. The research aims to assess students' grasp of the STEAM-H concept and to identify the work skills they acquire through learning that incorporates the STEAM-H approach. This investigation adopts a case study design involving 16 eleventh-grade students from the Agribusiness Vocational High School for Agricultural Product Processing in Ciamis Regency. Data was gathered through initial and final tests to gauge the students' understanding of STEAM-H, as well as through observations and interviews conducted while the students were engaged in a project on chicken wonton processing to evaluate their work skills. The results indicated a significant improvement in students' comprehension of the STEAMH concept after participating in the learning process. This increased understanding corresponded with the students' work skills, as evidenced by their successful completion of the chicken wonton processing project. The study concludes that the STEAM-H approach holds substantial potential for enhancing students' understanding of mathematics, food security, science, health, and technology concepts relevant to the agribusiness sector while also fostering the development of essential work skills required in the workplace. Wonton production requires a strong interdisciplinary approach. Mathematics, especially computational thinking skills, are crucial in designing an efficient and effective production process. The implication of this study underscores the importance of integrating the STEAM-H approach into the curriculum of Agribusiness Vocational High Schools, thereby preparing students to become competent graduates equipped to confront challenges in the era of Industry 4.0.

Forecasting Import-Export Volume and Value using Support Vector Machines and Random Forests

Hamda Yauma Istiqlala — 2024-10-30

National trade plays a crucial role in a country's economy by meeting the demand for goods and services. Imports and exports are vital components that significantly influence economic growth. This study aims to forecast and analyse the volume and value of imports and exports in the coming years, thereby helping the country to prepare for and enhance its competitiveness on the international stage. To achieve this, the study employs Support Vector Machine (SVM) and Random Forest methods, which have gained popularity for their high efficiency in handling classification and regression problems. These methods are particularly effective in producing accurate forecasts, especially when dealing with seasonal variations in data. The research also explores the potential of combining these methods for even more robust predictions. Additionally, the study considers external factors, such as global market trends and policy changes, which can influence trade dynamics. The findings of this research demonstrate the ability to predict future import and export volumes and values accurately. By comparing the error values in the form of Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE) from the model, it is proven that the SVM model is highly effective for export-import forecasting. Lower error values indicate higher prediction accuracy, highlighting the model's reliability in capturing complex trade dynamics. The insights from this study can be instrumental for policymakers and businesses in strategising for future trade activities, allowing them to make informed decisions that align with anticipated market shifts.

Front Matter

Rini Setyaningsih — 2024-10-30

Assalamu'alaikum Warahmatullahi Wabarakatuh

Alhamdulillah, we give thanks to Allah SWT for His grace, blessings, and guidance, enabling us to successfully organize the 2024 International Conference on Mathematics and Learning Research (ICOMER), hosted by the Mathematics Education Department of Universitas Muhammadiyah Surakarta, Indonesia.

The theme for this year is "Fostering Mathematical Thinking for Sustainable Development Goals: Empowering Minds, Transforming Futures." The conference aims to provide a dynamic platform for researchers, educators, and practitioners in the field of mathematics and mathematics education to exchange ideas, share their latest research, and explore innovative approaches to teaching and learning. Through this theme, we emphasize the vital role of mathematical thinking in addressing global issues and contributing to the Sustainable Development Goals (SDGs), aligning our efforts with the global vision for a sustainable and equitable future.

The ICOMER 2024 proceedings include a diverse range of papers presented at the conference, showcasing theoretical studies, empirical research, and practical applications in mathematics education. The collection reflects our commitment to enhancing mathematical literacy, problem-solving skills, and critical thinking to better equip learners for the challenges of the 21st century.

While we strive to ensure the quality of these proceedings, we recognize that there may still be areas for improvement. We warmly invite feedback, suggestions, and constructive criticism to help us enhance our future publications.

We hope this compilation serves as a valuable resource for readers, especially those committed to advancing the fields of mathematics and education. May it inspire further research, collaboration, and innovation, ultimately contributing to the transformative power of education.

Wassalamu'alaikum Warahmatullahi Wabarakatuh.