COGNITIVE TEST INSTRUMENT TO MEASURE THE CHEMICAL LITERACY SKILLS OF HIGH SCHOOL STUDENTS REGARDING SALT HYDROLYSIS
DOI:
https://doi.org/10.32699/cy76j121Keywords:
Chemical literacy, Cognitive test, Rasch, WinstepAbstract
Scientific literacy ability has also become a focus of attention in international assessments, namely through the Programme for International Student Assessment. Indonesia ranked 68th out of 81 participating countries with a science literacy score of 383. This low achievement indicates that the scientific literacy ability of students in Indonesia still requires serious attention. Scientific literacy has several branches, one of which is chemical literacy. Difficulty in understanding chemical concepts can affect chemical literacy ability, as chemical literacy is a student's ability to understand and apply basic chemical concepts accurately and effectively in everyday life. The purpose of this study is to develop a chemical literacy test instrument using the Rasch model. The objective of this study was to develop a chemistry literacy test instrument using the Rasch model. This research is a research and development (R&D) study employing the Rasch model. The test instrument was examined for validity, reliability, difficulty level, and discrimination index. The subjects of this study were 120 high school students. The research instrument used was a set of test items that had been developed. Based on the results of the analysis, the Rasch model can be applied to the developed chemistry literacy test instrument on the topic of salt hydrolysis. The field test results for the developed instrument indicate that it is valid and can be used to measure students' chemistry literacy ability. The validity of the instrument was assessed through empirical validity analysis, with Outfit MNSQ values ranging from 0.81 to 1.20, Outfit ZSTD values ranging from -1.43 to 1.34, and point measure correlation values ranging from 0.60 to 0.72. Reliability was assessed based on a person reliability of 0.78 and an item reliability of 0.99.
References
Anderson, L. W., & Krathwohl, D. R. (2020). Blooms Taxonomy Revised - Understanding the New Version of Bloom’s Taxonomy. Understanding the New Version of Bloom’s Taxonomy, 1(1), 1–8.
Arikunto, S. (2018). Dasar-dasar evaluasi pendidikan. Rineka Cipta.
Atik A , Marieke M, M. G. S. (2023). Uncovering important 21st-century skills for sustainable career development of social sciences graduates: A systematic review. Educational Research Review, 39(August 2022). https://doi.org/10.1016/j.edurev.2023.100528
Bond, T. G., & Fox, C. M. (2015). Applying the Rasch Model. In Applying the Rasch Model. Routledge/Taylor & Francis Group. https://doi.org/10.4324/9781410614575
Boone, W. J., Staver, J. R., & Yale, M. S. (2014). Rasch analysis in the human science. Journal of Research Design and Statistics in Linguitstics and Comunication Science, 5(2), 208–211.
Burhanuddin B, Junaidi, E., & Al Idrus, S. W. (2023). Analisis Tingkat Lierasi Kimia Siswa Kelas XI di SMAN 1 Mataram. Chemistry Education Practice, 6(2)(ISSN 2654-8119 (print), ISSN 2656-3940 (online)), 240–247. https://doi.org/10.29303/cep.v6i2.5522
Dori, Y. J., & Sasson, I. (2008). Chemical understanding and graphing skills in an honors case-based computerized chemistry laboratory environment: The value of bidirectional visual and textual representations. Journal of Research in Science Teaching, 45(2), 219–250. https://doi.org/10.1002/tea.20197
Eliza, W., & Yusmaita, E. (2021). Pengembangan Butir Soal Literasi Kimia pada Materi Sistem Koloid Kelas XI IPA SMA / MA Keywords : Chemical literacy instrument , Colloid system , MER , Rasch model. JEP (Jurnal Eksakta Pendidikan), 5(2), 197–204.
Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of Convenience Sampling and Purposive Sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11
Hasan E N. (2024). Pesantren dalam Memecahkan Masalah Kesehatan Tubuh : Studi Kasus di Pondok Pesantren Mamba’us Sholihin 8. 2(1).
Hasanah, H., & Aini, F. Q. (2025). Pengembangan Instrumen Tes Keterampilan Proses Sains pada Topik Kesetimbangan Kimia: Analisis dengan Model Rasch. JagoMIPA: Jurnal Pendidikan Matematika Dan IPA, 5(1), 68–82. https://doi.org/10.53299/jagomipa.v5i1.1043
Hope, D., Kluth, D., Homer, M., Dewar, A., Jaap, A., & Cameron, H. (2025). Exploring the use of Rasch modelling in “common content” items for multi-site and multi-year assessment. Advances in Health Sciences Education, 30, 427–438.
Hossan, D., Dato’ Mansor, Z., & Jaharuddin, N. S. (2023). Research Population and Sampling in Quantitative Study. International Journal of Business and Technopreneurship (IJBT), 13(3), 209–222. https://doi.org/10.58915/ijbt.v13i3.263
Jamaludin, J., Lay, Y. F., Khoo, C. H., & Leong, A. S. Y. (2021). Examining the Stem-Science Achievement Test (Ssat) Using Rasch Dichotomous Measurement Model. Jurnal Pendidikan IPA Indonesia, 10(4), 571–584. https://doi.org/10.15294/jpii.v10i4.29405
Jayanti, S. D., & Sutrisno, H. (2025). Improving Chemical Literacy Ability and Self Efficacy through Context Based Approach with Prediction-Observation-Explanation Strategy. Jurnal Penelitian Pendidikan IPA, 11(9), 573–582. https://doi.org/10.29303/jppipa.v11i9.11427
Kemendikdasmen. (2025). Hasil Tes Kemampuan Akademik.
Lasahinda, A., Pulukadang, R., & Kumesan, S. (2025). Analisis Butir Soal Matematika Pada Penilaian Akhir Semester Ganjil Menggunakan Model Rasch Berbantuan Software Winstep. Jurnal Pemikiran Dan Penelitian Pendidikan Matematika (JP3M), 8(2), 191–217. https://journal.rekarta.co.id/index.php/jp3m/article/view/765
Lawshe, C. H. (1975). a Quantitative Approach To Content Validity. Personnel Psychology, 28(4), 563–575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x
Lestari, K. E., & Yudhanegara, M. R. (2017). Analisis Kemampuan Representasi Matematis Mahasiswa pada Mata Kuliah Geometri Transformasi Berdasarkan Latar Belakang Pendidikan Menengah. Jurnal Matematika Integratif, 13(1), 28–33. https://doi.org/10.24198/jmi.v13.n1.11410.28-33
Liu, X. (2020). Using and Developing Measurement Instruments in Science Education: A Rasch Modeling Approach. In Coresource 4. https://doi.org/10.1002/sce.20477
Messick, S. (1995). Validity of psychological assessment: Validation of inferences from persons’ responses and performances as scientific inquiry into score meaning. American Psychologist, 50(9), 741–749.
OECD. (2023). PISA 2022 Assessment and Analytical Framework. In OECD Publishing.
Purniasari, L., Masykuri, M., & Ariani, S. R. D. (2021). Analisis Butir Soal Ujian Sekolah Mata Pelajaran Kimia Menggunakan Model Iteman dan Rasch. Jurnal Pendidikan Kimia, 10(2), 205–214.
Rahmayanti, N. P. (2024). Spss Training Validity Tests and Reliability Tests for Primary Data. BAKTI BANUA : Jurnal Pengabdian Kepada Masyarakat, 5(2), 21–26.
Rizki, M., & Yusmaita, E. (2021). Pengembangan Butir Soal Literasi Kimia pada Materi Ikatan Kimia Menggunakan Model Rasch. Edukimia, 3(2), 121–134. https://doi.org/10.24036/ekj.v3.i2.a282
Saputri H A, Zulhijrah, Larasati N Ji, S. (2023). Analisis Instrumen Assesmen : Validitas, Relibitas, Tingkat Kesukara dan Daya Beda Butir Soal. Didaktik : Jurnal Ilmiah PGSD FKIP Universitas Mandiri, 9(5), 2986–2995.
Sartika, A. Y. M., & Yusmaita, E. (2020). Pengembangan Asesmen Literasi Kimia pada Materi Hukum-Hukum Dasar Kimia dan Stoikiometri Kelas X SMA/MA. Edukimia, 2(3), 128–133. https://doi.org/10.24036/ekj.v2.i3.a187
Setiyawan, R. A., & Wijayanti, P. S. (2020). Analisis Kualitas Instrumen Untuk Mengukur Kemampuan Pemecahan Masalah Siswa Selama Pembelajaran Daring Di Masa Pandemi. Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika Dan Statistika, 1(2), 130–139. https://doi.org/10.46306/lb.v1i2.26
Sholeha, D. F., Kusasi, M., & Bakti, I. (2023). Pengembangan Instrumen Soal Higher-Order Thinking Skills (HOTS) Berbasis Google Form untuk Mengukur Hasil Belajar Peserta Didik pada Materi HID GARAM Development of Higher-Order Thinking Skills (HOTS) Questions Based on Google Form to Measure Stude. Journal of Chemistry And Education), 7(1), 32–48. http://jtam.ulm.ac.id/index.php/jcae
Shwartz, Y., Ben-Zvi, R., & Hofstein, A. (2006). The use of scientific literacy taxonomy for assessing the development of chemical literacy among high-school students. Chemistry Education Research and Practice, 7(4), 203–225. https://doi.org/10.1039/B6RP90011A
Sumintono, B., & Widhiarso, W. (2015). Aplikasi pemodelan Rasch pada assessment pendidikan (Bambang Sumintono & Wahyu Widhiarso, Ed.; 1st ed.). September 2015.
Surya, C. and. (2024). Content validity analysis of literacy assessment instruments. 40(1), 81–91. https://doi.org/10.21831/cp.v40i1.33474
Tesio, L., Caronni, A., Kumbhare, D., & Scarano, S. (2024). Interpreting results from Rasch analysis 1. The “most likely” measures coming from the model. Disability and Rehabilitation, 46(3), 591–603. https://doi.org/10.1080/09638288.2023.2169771
Wrigley, W., Van Der Vleuten, C. P., Freeman, A., & Muijtjens, A. (2012). A systemic framework for the progress test: Strengths, constraints and issues: AMEE Guide No. 71. Medical Teacher, 34(9), 683–697. https://doi.org/10.3109/0142159X.2012.704437
Zayrin A. A., Nupus, H., Maizia, K. K., Marsela, S., Hidayatullah, R., & H. (2025). Analisis Instrumen Penelitian Pendidikan (Uji Validitas Dan Relibilitas Instrumen Penelitian). Jurnal QOSIM Jurnal Pendidikan Sosial & Humaniora, 3(2), 780–789. https://doi.org/10.61104/jq.v3i2.1070
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