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All Journal SIGMA: Jurnal Pendidikan Matematika Jumper : Journal of Educational Multidisciplinary Research
Fitriani Fitriani
Universitas Islam Ahmad Dahlan
Computer Science & IT Education Environmental Science Library & Information Science Mathematics Other

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ANALISIS PENGARUH ARUS GLOBALISASI TERHADAP PERUBAHAN NILAI SOSIAL SISWA DALAM PEMBELAJARAN MATEMATIKA DI SEKOLAH DASAR Nurjannah Nurjannah; Anggy Heriyanti; Irmayanti Irmayanti; Fitriani Fitriani; Husnul Khatimah
SIGMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 17 No. 2: Desember 2025
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/9ywn7k97

Abstract

Penelitian ini bertujuan untuk menggambarkan arus globalisasi dan nilai sosial siswa, mengkaji hubungan linear keduanya, serta menganalisis pengaruh arus globalisasi terhadap nilai sosial dalam pembelajaran matematika di SD 286 Pasaka. Sampel penelitian sebanyak 48 siswa kelas IV sampai VI diambil dengan teknik total sampling. Data dikumpulkan menggunakan angket dan dianalisis secara deskriptif serta regresi linier sederhana. Hasil menunjukkan bahwa arus globalisasi yang dialami siswa berada pada kategori sedang, sementara nilai sosial siswa dalam pembelajaran matematika tergolong tinggi. Hubungan antara arus globalisasi dan nilai sosial bersifat linear dengan nilai signifikansi 0,973 (p > 0,05). Selain itu, arus globalisasi berpengaruh positif dan signifikan terhadap nilai sosial siswa dengan koefisien regresi sebesar 0,277 dan nilai signifikansi 0,013 (p < 0,05), yang menjelaskan 14% variasi nilai sosial siswa. Temuan ini menegaskan bahwa globalisasi dapat memengaruhi nilai sosial siswa secara positif apabila diarahkan melalui pembelajaran berbasis nilai dan peran aktif guru. Penelitian ini memberikan implikasi penting bagi pengembangan strategi pembelajaran matematika yang mengintegrasikan aspek kognitif dan nilai karakter dalam menghadapi tantangan globalisasi.
Analisis Proses Berpikir Tingkat Tinggi Berbasis STEM Terintegrasi Artificial Intelligence pada Mata Kuliah Statistik Dasar Fitriani Fitriani; Andi Heriani; Nurjannah Nurjannah; Anggy Heriyanti; Wafiq Azizah
Jumper: Journal of Educational Multidisciplinary Research Vol 5 No 2 (2026): Jumper: Journal of Educational Multidisciplinary Research
Publisher : LSM Catimore dan Sahabat Jl. Paya Ilang/Pertamina Desa Lemah Burbana, Takengon, Aceh Tengah 24552

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56921/jumper.v5i2.462

Abstract

This study aims to analyze students' Higher-Order Thinking Skills (HOTS) within the context of an AI-integrated, STEM-based Basic Statistics course and to describe the role of AI in supporting the development of these skills. A qualitative, descriptive research approach was employed. The subjects consisted of three students from the Mathematics Education program enrolled in the Basic Statistics course, selected purposively based on high, medium, and low ability levels. Data were collected through observation, in-depth interviews, documentation, and HOTS-based assignment sheets. Data analysis followed the Miles and Huberman model—comprising data reduction, data display, and conclusion drawing—while data validity was verified through source and method triangulation. The results indicate that high-ability students were capable of critically analyzing, evaluating, and reflecting on statistical problem-solving processes and effectively utilizing AI as a learning aid. Medium-ability students demonstrated an understanding of concepts and the ability to use technology, though their evaluative and creative skills remained limited. Meanwhile, low-ability students tended to rely on procedural approaches, example solutions, and instant answers, showing suboptimal performance in contextual analysis and reflection. AI played a role in facilitating conceptual understanding, data analysis, answer evaluation, and the development of critical thinking and problem-solving skills; however, its use required a critical mindset to avoid dependency. This study provides empirical insights into the characteristics of students' HOTS in an AI-integrated, STEM-based Basic Statistics course, offering a reference for developing instructional strategies aimed at enhancing higher-order thinking skills in higher education.
Co-Authors Andi Heriani Anggy Heriyanti Husnul Khatimah Irmayanti Irmayanti Nurjannah Nurjannah Wafiq Azizah