PENALARAN ANALOGI PESERTA DIDIK SMA DALAM MENYELESAIKAN MASALAH MATEMATIKA OPEN-ENDED DENGAN DUKUNGAN AI DITINJAU DARI KEMAMPUAN MATEMATIS
DOI:
https://doi.org/10.23969/jp.v11i03.61908Keywords:
Analogical Reasoning, Open-Ended Problem, Artificial Intellegence, Mathematical AbilityAbstract
Analogical reasoning is an essential skill in mathematics learning because it enables students to transfer knowledge from a source problem to a target problem with a similar underlying structure. With technological advancements, Artificial Intelligence (AI), such as ChatGPT, has emerged as a learning support tool in mathematics education. This study aimed to describe senior high school students’ analogical reasoning in solving open-ended mathematical problems with AI support based on their mathematical ability levels. This research employed a qualitative case study design. The participants were three senior high school students selected through purposive sampling, consisting of student with high mathematical ability, student with moderate mathematical ability, and student with low mathematical ability. The research instruments included a mathematical ability test, an analogical reasoning test in the form of open-ended problems on the topic of Systems of Linear Equations in Three Variables (SLETV), and a semi-structured interview guide. Data were analyzed using Ruppert’s stages of analogical reasoning: structuring, mapping, applying, and verifying. The findings revealed that students with high mathematical ability demonstrated structural analogical reasoning by completing all stages of analogical reasoning and focusing on the underlying mathematical structure shared by the source and target problems. Students with moderate mathematical ability exhibited partial analogical reasoning, completing all stages but relying primarily on similarities in solution procedures. Meanwhile, students with low mathematical ability demonstrated surface analogical reasoning, characterized by a focus on contextual and surface similarities between the problems. Overall, the quality of analogical reasoning improved as students’ mathematical ability increased. AI functioned as an interactive support tool that facilitated idea exploration, strategy development, and solution verification throughout the analogical reasoning process
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