Assessing Data Literacy Competencies in Mathematics Among Junior High School Students in Yogyakarta City
Abstract
This research aims to assess students' data literacy skills, focusing on their ability to translate data from one format to another, comprehend data-related problems, analyze strategies for data-driven problem-solving, predict outcomes based on data, draw conclusions, and construct arguments grounded in data. The study employs a survey methodology with both quantitative and qualitative approaches. A total of 362 students from various educational levels in Yogyakarta's state junior high schools were surveyed and selected through stratified and proportionate random sampling techniques. Data were collected using a test instrument comprising six questions designed to measure different aspects of data literacy, alongside interview results. The students' data literacy was categorized into high, medium, and low levels. The findings indicate that a significant majority (95%) of students exhibited low data literacy, particularly struggling with drawing conclusions and constructing arguments based on data. Students with high data literacy skills successfully met all the indicators. Those with medium-level skills performed well on most indicators but faced difficulties in choosing strategies for data problem-solving and drawing conclusions, often due to insufficient time for deeper reflection. Conversely, students with low data literacy struggled to meet any of the indicators effectively.
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Batur, A., & Baki, A. (2022). Examination of the relationship between statistical literacy levels and statistical literacy self-efficacy of high school students. Egitim ve Bilim, 47(209), 171–205. https://doi.org/10.15390/EB.2022.9970
Blake, B & Pope, T. (2008) Developmental Psychology: Incorporating Piaget’s and Vygotsky’s Theories in Classrooms, Journal of Cross-Disciplinary Perspectives in Education, 1(1), 59-67.
BUMN. (2019). Industri 4.0: Asuransi Harus Siap Bertransformasi. Jakarta: PT Reasuransi Indonesia Utama.
D’Ignazio, C., & Bhargava, R. (2015). Approaches to Building Big Data Literacy. Bloomberg Data for Good Exchange Conference.
D’Ignazio, C., & Bhargava, R. (2016). DataBasic: Design Principles, Tools and Activities for Data Literacy Learners. The Journal of Community Informatics, 12(3), 83–107. https://doi.org/10.15353/joci.v12i3.3280
Fitri, I., Setyaningrum, W., & Pulungan, D. A. (2023). Fenomena Literasi Statistik Pada Pembelajaran Matematika Siswa Sma Di Lhokseumawe Aceh. AKSIOMA: Jurnal Program Studi Pendidikan Matematika, 12(2), 1927. https://doi.org/10.24127/ajpm.v12i2.7000
GLN. (2017). Materi Pendukung Literasi Digital. In Kementerian Pendidikan dan Kebudayaan. Jakarta. Retrieved from http://gln.kemdikbud.go.id/glnsite/wp-content/uploads/2017/10/literasi-DIGITAL.pdf
Gunawan, G., Asriani, N. W., Kumala, F. Z., Akhsani, L., & Rohmawati, S. (2022). Karakteristik Kemampuan Literasi Statistika Siswa Dalam Menyelesaikan Masalah Model Pisa. AKSIOMA: Jurnal Program Studi Pendidikan Matematika, 11(3), 2282. https://doi.org/10.24127/ajpm.v11i3.5443
Hafiyusholeh, M. (2015). Literasi Statistik dan Urgensinya Bagi Siswa. Wahana, 64(1), 1–8. Retrieved from https://jurnal.unipasby.ac.id/index.php/whn/article/view/531/390
Herzog, D. (2015). Data Literacy. Retrieved November 25, 2023, from SAGE Publications website: https://books.google.co.id/books?hl=id&lr=&id=rDFyBgAAQBAJ&oi=fnd&pg=PP1&ots=nFF1xO_uGi&sig=W5VBpfuT2_bbSOx_8t4jKadFw7o&redir_esc=y#v=onepage&q&f=false
Kartika, E., Ariswan, Suban, M. E., & Arafah, Z. U. (2021). Students’ Data Literacy Ability in Physics Using the Physics E-Module Integrated with the Values of Pancasila During the Covid-19. Proceedings of the 6th International Seminar on Science Education (ISSE 2020), 541(Isse 2020), 329–335. https://doi.org/10.2991/assehr.k.210326.047
Kemenkes. (2022). UPDATE 30 Januari: Kasus Covid-19 di Indonesia Bertambah 12.422 Artikel ini telah tayang di Kompas.com dengan judul “UPDATE 30 Januari: Kasus Covid-19 di Indonesia Bertambah 12.422”, Klik untuk baca: https://nasional.kompas.com/read/2022/01/30/18153891/up. Retrieved from Kompas website: https://nasional.kompas.com/read/2022/01/30/18153891/update-30-januari-kasus-covid-19-di-indonesia-bertambah-12422
Khan, K., & Mason, J. (2021). The M in STEM and Issues of Data Literacy. 29th International Conference on Computers in Education Conference, ICCE 2021 - Proceedings, 1, 632–637.
Khuan, L., & Krauss, S. E. (2015). of Clients ’ Experiences in Healthcare Research ? International Journal of Public Health and Clinical Sciences, 2(4), 1–6.
Kireina, N. F. (2017). Mesin parkir elektronik sebagai wujud dari smart city di kota bandung. Jurnal Ilmu Sosial Dan Ilmu Politik, 7(2), 63–80.
Larasati, P. E., Supahar, & Yunanta, D. R. A. (2020). Validity and reliability estimation of assessment ability instrument for data literacy on high school physics material. Journal of Physics: Conference Series, 1440(1). https://doi.org/10.1088/1742-6596/1440/1/012020
Moralez, L. G, Hsu, Y. C., Poole, J., Rae. B., & Rutherford. I. (2014).A World that Counts Mobilishing the Data Revolution for Sustainable Development. Admir Jahi.
OECD. (2018). Pisa 2021 Mathematics Framework (Draft). In Angewandte Chemie International Edition, 6(11), 951–952. OECD Publisher. Retrieved from http://www.oecd.org/pisa/pisaproducts/pisa-2021-mathematics-framework-draft.pdf
Permendikbudristek. (2022). Peraturan Menteri Pendidikan, Kebudayaan, Riset, dan Teknologi Rebuplik Indonesia Nomor 5 tentang Standar Kompetensi Lulusan pada Pendidikan Anak Usia Dini, Jenjang Pendidikan dasar, dan Jenjang Pendidikan Menengah.
PSKPKemendikbudristek. (2020). Penerimaan Peserta Didik Berdasarkan Zonasi Pendidikan. Jakarta: Pusat Penelitian Kebijakan, Badan Penelitian dan Pengembangan dan Perbukuan, Kementerian Pendidikan dan Kebudayaan.
Reeves, T. D., & Chiang, J. L. (2019). Effects of an asynchronous online data literacy intervention on pre-service and in-service educators’ beliefs, self-efficacy, and practices. Computers and Education, 136, 13–33. https://doi.org/10.1016/j.compedu.2019.03.004
Samosir, P., Rajagukguk, W., & Ratnawati. (2022). Dasar-Dasar Statistika Inferensi Dalam Penelitian.Schield, M. (2011). Statistical literacy: A new mission for data producers. Statistical Journal of the IAOS, 27(3–4), 173–183. https://doi.org/10.3233/SJI-2011-0732
Septiani, & Gunawan, D. (2017). Metode Horisontal Untuk Pembelajaran Berhitung Pembagian Pada Siswa Tunarungu. JASSI_anakku, 18(1976), 57–62. Retrieved from http://uir.ac.id/?p=2499].
DOI: https://doi.org/10.35445/alishlah.v16i3.5072
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