Kemampuan Literasi Matematis Siswa Ditinjau dari Jenis Pemahaman Skemp dalam Konteks Statistika - Ningsih, Hesti Rahayu; Suryanti; Pramesti, Cicik (Papanda, 2025)
Mathematical literacy is an essential competence in education, encompassing the ability to understand and apply mathematical concepts in everyday life. Within the topic of statistics, this literacy becomes particularly relevant, as it relates directly to data processing and interpretation. However, many students tend to memorize formulas mechanically without fully understanding their meaning and purpose. This study aims to examine students’ mathematical literacy skills in relation to Skemp’s theory of understanding, which distinguishes between instrumental and relational understanding. The research employed a qualitative case study approach, involving three eighth-grade students at SMPN 1 Sanankulon who represented high, medium, and low levels of ability. The research instruments consisted of a mathematical literacy test based on statistical contexts and interview guidelines designed to explore students’ reasoning processes. Data analysis referred to three indicators of mathematical literacy developed by PISA, namely formulating, employing, and interpreting. The findings revealed that students with relational understanding demonstrated higher levels of mathematical literacy compared to those with instrumental understanding. Relational learners were able to connect statistical concepts with real-life contexts, justify the procedures used, and interpret results meaningfully. In contrast, students with instrumental understanding often relied on rote memorization of formulas, leading to difficulties in adapting their knowledge to new or unfamiliar contexts. These results highlight the importance of promoting relational understanding as a foundation for enhancing mathematical literacy. The study suggests that instructional strategies should emphasize contextual problem-solving, conceptual connections, and reflective reasoning, particularly in statistics, to better equip students with the skills needed for data interpretation and informed decision-making in real-world situations