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All Journal JRAMathEdu (Journal of Research and Advances in Mathematics Education) Jurnal Pendidikan Matematika Universitas Lampung
Satria Bayu Herlambang
Universitas Jambi
Education Mathematics

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Portrait of Junior High School Students' Statistical Literacy through PISA on Uncertainty and Data Content Satria Bayu Herlambang; Duano Sapta Nusantara; Feri Tiona Pasaribu
Jurnal Pendidikan Matematika Universitas Lampung Vol. 13 No. 4 (2025): Jurnal Pendidikan Matematika Universitas Lampung
Publisher : Faculty of Teacher Training and Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/mtk/v13i4.pp217-228

Abstract

Statistical literacy is a critical 21st-century competency, as students increasingly encounter data-driven information in their everyday lives. However, international assessments such as PISA consistently show that Indonesian students struggle to interpret and reason with data. This study aims to investigate junior high school (JHS) students’ statistical literacy in solving PISA-based problems related to uncertainty and data, while also linking the results to Sustainable Development Goal (SDG) 4: Quality Education. A descriptive qualitative approach was employed involving 40 ninth-grade students from JHS Negeri 6 Kota Jambi, selected through purposive sampling to represent high, medium, and low academic ability groups. Data were collected through a validated PISA 2012 item focusing on uncertainty and data, along with semi-structured interviews designed to explore students’ statistical-literacy strategies. Data analysis followed an interactive model consisting of data reduction, data display, and conclusion drawing, guided by Schield’s (2011) statistical-literacy indicators. The findings indicate that only 17.5% of students demonstrated a high level of statistical literacy, while most were categorized as medium (37.5%) or low (45%). Further analysis revealed persistent difficulties in identifying trends, calculating averages, and drawing valid conclusions. These findings underscore the need for contextual, PISA-based learning tasks that foster statistical reasoning and strengthen students’ fundamental literacy skills as a foundation for achieving quality education.
Developing PISA-like task using climate change contexts to enhance students’ statistical literacy Duano Sapta Nusantara; Satria Bayu Herlambang; Feri Tiona Pasaribu; Kgaladi Maphutha
JRAMathEdu (Journal of Research and Advances in Mathematics Education) Volume 11, Issue 2, April 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jramathedu.v11i2.15181

Abstract

This study developed PISA-like tasks in the Uncertainty and Data domain using climate change contexts and examined their potential to elicit junior high school students' statistical literacy. The study employed a design research methodology of the development studies type, in which Tessmer's formative evaluation model was applied specifically to the formative evaluation stage, encompassing self-evaluation, expert review, one-to-one, small group, and field test, alongside a preliminary phase and an assessment phase. A total of 49 Grade IX students from a state junior high school in Jambi, Indonesia, participated across the evaluation stages: three in one-to-one, nine in small group, and 37 in the field test. Twenty-two climate change–related tasks were developed. However, this article specifically focuses on one scenario concerning “Jakarta is Singking” due to climate change impacts. Data were collected through expert validation, student practicality questionnaires, written task responses, and interviews, and were analyzed qualitatively and descriptively. The developed tasks were valid in terms of content, construct, and language, and practical based on students' practicality scores. The assessment phase revealed a positive potential effect: Problem Understanding reached 76.06%, Data Processing 69.26%, and Data Interpretation 68.69%, all in the moderate category, with interpretation being the least developed due to students' limited prior exposure to context-rich tasks. The climate change context supported engagement with trends, variability, and uncertainty. These findings suggest that future studies should integrate climate-based PISA-like tasks within structured instructional phases to support the written expression of students' statistical reasoning, which in this study emerged more clearly through interviews than written responses.
Co-Authors Duano Sapta Nusantara Feri Tiona Pasaribu Kgaladi Maphutha