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Uncovering metacognitive awareness and meaningful learning of prospective mathematics teachers after learning absolute value inequalities Wayan Rumite; Halil Arianto; Syamsinar Syamsinar
JRAMathEdu (Journal of Research and Advances in Mathematics Education) Volume 11, Issue 1, January 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jramathedu.v11i1.13391

Abstract

Learners who lack adequate metacognitive awareness and meaningful have the potential to work mechanically. The aims of this study is to uncover the characteristics and description of metacognitive awareness and meaningful of prospective mathematics teachers after learning absolute value inequalities and the involvement of intuitive and analytical thinking. This study uses a qualitative approach with an exploratory type. A total of 5 prospective mathematics teachers who were taking differential calculus courses were selected as subjects from 87 candidate subjects from two different universities in Indonesia. Data collection was carried out by administering tests and conducting semi-structured interviews. Data analysis in this study went through three stages, namely data reduction, data presentation, and drawing conclusions. The results of data analysis show that: 1) unaware and not meaningful, 2) aware but not meaningful, 3) unaware but meaningful, 4) aware and meaningful. In addition, a pattern of intuitive and analytical thinking was also found, whereby prospective mathematics teachers who were not conscious activated analytical thinking, while those who were conscious activated intuitive thinking.  These findings imply the importance of emphasizing mindful and meaningful during the learning process so that students can understand concepts holistically and deeply, enabling them to solve problems accurately.
Pengaruh pembelajaran matematika berbantuan generative artificial intelligence terhadap kemampuan pemecahan masalah matematis mahasiswa Fajar Arwadi; Muhammad Syarifuddin Rahman; Wayan Rumite
Cakrawala Vol 5, No 1 (2026): Juni
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/cakrawala.v5i1.4064

Abstract

Pemecahan masalah matematis merupakan kompetensi penting bagi mahasiswa calon pendidik, terutama ketika mereka memasuki matematika tingkat lanjut dan belajar mandiri di luar kelas. Penelitian ini mengkaji pengaruh Generative Artificial Intelligence (GenAI) terhadap kemampuan pemecahan masalah matematis serta menjelaskan perannya sebagai Machine Presence dalam kerangka Community of Inquiry (CoI). Penelitian menggunakan mixed methods dengan desain sekuensial eksplanatori. Fase kuantitatif berupa kuasi-eksperimen melibatkan 69 mahasiswa S1 Pendidikan Matematika Universitas Negeri Makassar pada kelas eksperimen dan kontrol. Analisis ANCOVA menunjukkan bahwa intervensi GenAI berpengaruh positif terhadap kemampuan pemecahan masalah matematis. Fase kualitatif melalui kuesioner CoI termodifikasi dan wawancara memperlihatkan bahwa Machine Presence bekerja sebagai tutor Socratic yang menyediakan scaffolding heuristik, membantu mahasiswa memeriksa inkonsistensi logis tanpa memberi jawaban komputasional instan, serta tetap menjaga otoritas Teaching Presence dosen. Temuan ini menegaskan bahwa GenAI, dengan batasan instruksional yang tepat, dapat menjadi mitra kognitif bagi mahasiswa perguruan tinggi dalam pembelajaran matematika lanjut yang menantang secara terarah.
Mathematical Representations in Determining the Area of a Triangle: Visual Representation as a Cognitive Guide Wayan Rumite; Lathifaturrahmah Lathifaturrahmah; Intan Buhati Asfyra
Indiktika : Jurnal Inovasi Pendidikan Matematika Vol. 8 No. 2 (2026): Indiktika : Jurnal Inovasi Pendidikan Matematika
Publisher : FKIP Universitas PGRI Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31851/indiktika.v8i2.21661

Abstract

Mathematical representation is a critical competency that prospective mathematics teachers must possess in order to understand concepts and solve problems effectively. However, previous studies still leave conceptual gaps in explaining how prospective mathematics teachers construct and coordinate representations as cognitive guidance mechanisms, particularly when calculating the area of a triangle. This study aims to uncover the involvement of visual representations and cognitive guidance during the process of solving problems involving the area of a triangle. This study employs an exploratory qualitative approach. Data were collected through problem-solving tests and semi-structured interviews with five subjects selected from 93 prospective participants. The data were analyzed based on the use of visual representations, the concept of coordinate transformation, plotting accuracy, and indications of cognitive guidance. The results revealed four characteristics of representation use: (1) no visual representation, incorrect coordinate transformation, failure to plot coordinate points, and no cognitive guidance; (2) visual representation, incorrect coordinate transformation, incorrect plotting of coordinate points, and cognitive guidance; (3) does not involve visual representations, correct coordinate transformations, does not plot coordinate points, and is not cognitively guided; and (4) involves visual representations, correct coordinate transformations, plots coordinate points accurately, and is cognitively guided. Visual representations help understand geometric structures and spatial relationships, while symbolic representations formalize computational procedures.