An Indicator-Based Analysis of Students’ Numeracy in Statistics: A Qualitative Descriptive Study - Prameslani, Adelia Septina; Silvia, Ike; Wahyuni, Reni; Saputri, Dwika (International Journal of Applied Learning and Research in Algebra, 2026)
Purpose – This study analyzes Grade VIII junior high school students’ numeracy ability in statistics based on numeracy indicators. Numeracy is essential for everyday life because it enables individuals to understand, use, and evaluate quantitative information in real-world contexts, including making decisions from data. Methodology – Using a phenomenological approach with a qualitative descriptive design, this study involved 35 Grade VIII students. Data were collected through a numeracy test consisting of numerical description tasks aligned with three indicators: (1) using numbers and basic mathematical symbols, (2) analyzing data in visual form (tables/graphs), and (3) interpreting analytical results as a basis for decision-making. Students’ responses were analyzed descriptively by indicator to determine achievement and identify recurring difficulties. Findings – Performance was highest on using numbers and basic mathematical symbols (82.5%), followed by analyzing visually presented data (61.79%). The lowest achievement was found in interpreting results for decision-making (21.07%). These results suggest that while many students can apply basic numerical procedures and read visual data, they struggle to connect statistical results to justified decisions. Instruction should therefore emphasize interpretation and decision-making through authentic, context-based data tasks. Novelty – This study offers an indicator-based profile of statistical numeracy using numerical description tasks within a phenomenological, qualitative-descriptive framework, revealing decision-making as the weakest indicator. Significance – The findings inform teachers, curriculum developers, and assessment designers in developing learning and assessment strategies that strengthen students’ statistical interpretation and data-driven decision-making skills.