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All Journal Jumper : Journal of Educational Multidisciplinary Research Indonesian Mathematics Education Journal
Wafiq Azizah
Universitas Islam Ahmad Dahlan
Computer Science & IT Education Environmental Science Library & Information Science Mathematics

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Efektivitas Media Pembelajaran Ular Tangga Matematika Terhadap Minat Belajar Matematika Siswa Nurhalimah Nurhalimah; Wafiq Azizah; Herianto Herianto; Nurjannah Nurjannah
Indonesian Mathematics Education Journal Vol. 3 No. 1 (2026)
Publisher : UIN Kiai Ageng Muhammad Besari Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21154/imej.v3i1.72

Abstract

Penelitian ini bertujuan untuk menganalisis efektivitas media pembelajaran Ular Tangga terhadap minat belajar matematika siswa di UPT SMKN 1 Sinjai. Penelitian ini menggunakan metode kuantitatif dengan jenis pre-eksperimen dan desain One Group Pretest–Posttest. Sampel penelitian berjumlah 20 siswa kelas X AKL 1 yang dipilih secara purposive sampling. Instrumen penelitian berupa angket minat belajar dengan 24 pernyataan skala Likert yang mencakup empat indikator, yaitu perasaan terhadap matematika, minat kognitif, ketertarikan terhadap aktivitas pembelajaran, dan keterlibatan siswa. Data dianalisis menggunakan uji normalitas Shapiro–Wilk, uji homogenitas Levene, analisis deskriptif, dan uji paired sample t-test. Hasil penelitian menunjukkan bahwa data berdistribusi normal dan homogen. Rata-rata skor minat belajar meningkat dari 70,95 menjadi 85,15 dengan selisih 14,20 poin. Hasil uji paired sample t-test menunjukkan nilai p-value 0,000 (<0,05), sehingga terdapat pengaruh signifikan setelah penerapan media Ular Tangga. Temuan ini menunjukkan bahwa media pembelajaran Ular Tangga memiliki pengaruh signifikan terhadap minat belajar matematika siswa di UPT SMKN 1 Sinjai. Penelitian ini memberikan kontribusi berupa bukti empiris serta implikasi pentingnya penggunaan media pembelajaran yang kreatif dan interaktif.
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 Fitriani Fitriani Herianto Herianto Nurhalimah Nurhalimah Nurjannah Nurjannah