Mapping Epistemological Obstacles in Junior High School Students' Statistical Word-Problem Solving: A Systematic Literature Review - Aeryn Meiska Putri Bangun; Adi Ihsan Imami; Rina Marlina (Jurnal Didactical Mathematics, 2026)
Statistical word problems require students to integrate conceptual understanding, procedural competence, and computational skills to interpret and represent data meaningfully. However, the epistemological obstacles underlying students' difficulties in solving such problems remain fragmented across individual studies. This study aimed to synthesize empirical evidence on the epistemological obstacles experienced by junior high school students in statistical word-problem solving and to examine the relationships among conceptual, procedural, and operational obstacles. A Systematic Literature Review (SLR) was conducted following the PRISMA 2020 guidelines. Literature published between 2019 and 2026 was identified through Google Scholar, ERIC, and Garuda. After applying predefined eligibility criteria and quality assessment procedures, 24 empirical studies were included in the qualitative synthesis. Data were analyzed using qualitative content analysis and thematic synthesis. The review identified three dominant categories of epistemological obstacles. Conceptual obstacles were the most prevalent, appearing in 20 studies, followed by procedural obstacles in 17 studies and operational obstacles in 14 studies. The synthesis further revealed that these obstacles formed a progressive and interconnected pattern. Incomplete conceptual understanding constrained students' procedural decision-making, while procedural deficiencies subsequently increased the likelihood of operational errors during statistical problem solving. These findings suggest that students' statistical learning difficulties should be understood as an integrated system of epistemological obstacles rather than isolated categories of error. The review proposes a progressive framework of epistemological obstacles and highlights the importance of strengthening conceptual understanding through contextualized learning, multiple representations, and formative assessment to support meaningful statistical reasoning.