Erna Puji Astutik, Silviana Maya Purwasih, Restu Ria Wantika, Erlin Ladyawati

Analisis Kemampuan Berpikir Reflektif Mahasiswa Calon Guru dalam Menyelesaikan Masalah Statistika Matematika dengan Bantuan ChatGPT

Introduction

Analisis kemampuan berpikir reflektif mahasiswa calon guru dalam menyelesaikan masalah statistika matematika dengan bantuan chatgpt. Analisis kemampuan berpikir reflektif mahasiswa calon guru dalam menyelesaikan masalah statistika matematika dengan ChatGPT. Temukan variasi tingkat refleksi dan implikasi pedagogis pemanfaatan AI.

Abstract

Kemampuan berpikir reflektif merupakan salah satu keterampilan berpikir tingkat tinggi yang penting dimiliki oleh mahasiswa calon guru matematika. Kemampuan ini berperan dalam membantu mahasiswa memahami konsep secara mendalam, mengevaluasi proses penyelesaian masalah, serta merekonstruksi solusi secara bermakna. Perkembangan teknologi kecerdasan buatan, khususnya ChatGPT, membuka peluang baru sebagai media bantu yang dapat mendukung proses refleksi mahasiswa dalam pembelajaran matematika. Penelitian ini bertujuan untuk menganalisis kemampuan berpikir reflektif mahasiswa calon guru dalam menyelesaikan masalah Statistika Matematika dengan bantuan ChatGPT. Penelitian ini menggunakan pendekatan kualitatif deskriptif dengan subjek enam mahasiswa Program Studi Pendidikan Matematika. Teknik pengumpulan data meliputi tes, presentasi, wawancara, dan transkrip interaksi mahasiswa dengan ChatGPT. Analisis data dilakukan berdasarkan lima indikator kemampuan berpikir reflektif, yaitu understanding, analysis, evaluation, self-awareness, dan reconstruction. Hasil penelitian menunjukkan adanya variasi tingkat kemampuan berpikir reflektif mahasiswa, mulai dari sangat tinggi hingga sangat rendah. Mahasiswa dengan kemampuan reflektif tinggi mampu memanfaatkan ChatGPT secara dialogis dan kritis sebagai cognitive dan metacognitive partner, sedangkan mahasiswa dengan kemampuan reflektif rendah cenderung menggunakan ChatGPT sebagai alat pencari jawaban cepat. Temuan ini menunjukkan bahwa pemanfaatan ChatGPT tidak secara otomatis meningkatkan kemampuan berpikir reflektif, melainkan sangat dipengaruhi oleh kualitas interaksi dan kesadaran reflektif mahasiswa. Oleh karena itu, integrasi ChatGPT dalam pembelajaran statistika matematika perlu disertai dengan scaffolding pedagogis yang menekankan refleksi dan evaluasi konseptual.

Review

This paper presents a timely and relevant investigation into the reflective thinking abilities of pre-service mathematics teachers when solving mathematical statistics problems with the assistance of ChatGPT. The study addresses a critical gap by exploring how a crucial higher-order thinking skill, reflective thinking, interacts with emerging AI technologies in an educational context. By focusing on pre-service teachers, the research contributes significantly to teacher education literature, highlighting the importance of deep conceptual understanding and problem-solving evaluation, especially in the context of integrating new technological tools. The overall aim to analyze this complex interplay is well-articulated and holds substantial implications for future pedagogical practices. Methodologically, the study employs a qualitative descriptive approach, utilizing a small yet focused sample of six pre-service mathematics education students. Data collection methods are comprehensive, including tests, presentations, interviews, and detailed transcripts of student interactions with ChatGPT, allowing for a rich exploration of reflective processes. The analysis, guided by five established indicators of reflective thinking—understanding, analysis, evaluation, self-awareness, and reconstruction—provides a robust framework for assessing student capabilities. The findings reveal a significant variation in students' reflective thinking levels, ranging from very high to very low. Crucially, the research demonstrates that students with higher reflective abilities leveraged ChatGPT as a critical and dialogical partner, engaging in cognitive and metacognitive processes, while those with lower reflective abilities tended to use it merely as a quick answer-seeking tool. The most profound insight from this research is the finding that ChatGPT does not inherently enhance reflective thinking; rather, its effectiveness is highly dependent on the quality of student interaction and their existing reflective awareness. This conclusion offers a vital caveat to the enthusiastic adoption of AI in education, emphasizing the continued importance of pedagogical design. The study strongly advocates for integrating ChatGPT with deliberate pedagogical scaffolding that explicitly promotes reflection and conceptual evaluation. While the small sample size might limit the generalizability of the findings, it is appropriate for the in-depth qualitative nature of the investigation. This paper provides valuable guidance for educators and curriculum developers on how to responsibly and effectively integrate AI tools to foster, rather than circumvent, the development of essential higher-order thinking skills in future educators.

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