Research Trend of Rasch Model in the Development of Scientific Literacy Assessment Through Bibliometrics

Fajriatul Mufarriha Sunni*, Irgy Redityo Dawana, Roudlotul Jannah, Titin Sunarti, Madlazim Madlazim, Wasis Wasis, Iqbal Ainur Rizki

Abstract


Scientific literacy is fundamental ability to facing the complexity of problem solving in this 21 st century era. The Rasch model is needed as a measurement model that can provide detailed information about the quality of the items used. Therefore, it is crucial for educators and researchers to understand trends in measurement and the development of science literacy instruments within the Rasch model. This study aims to provide an overview of research trends on the measurement and the development of scientific literacy instruments, especially in rasch model, through search for articles that have been published since 2002-2023. The data consisted of articles derived from scopus (n=182) and google scholar (n=960), which were then processed using microsoft excel and vosviewer to obtain bibliometric mapping visualization. This process involves the application of statistical methods to generate accurate mappings and focuses on international publications and national journals, utilizing scopus and google scholar databases to compare their results. The result showed that the research of rasch model in scientific literacy instruments development in recent years has increased and it has the potential to be researched in the future. The findings are expected to provide an overview for othe researchers regarding rasch model in scientific literacy instruments development including affiliation, subject area, document type, source type, language, countries, and mapping visualization of the network on rasch model research.


Keywords


Rasch model, scientific literacy, publish or perish, VOSviewer, bibliometrics

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Admoko, S., Mukhayyarotin, N. R. J., & Madlazim, E. H. (2021). Bibliometric Profile of Science Education Research on Argumentation and the Contribution of Indonesia. 209(Ijcse), 502–509. https://doi.org/10.2991/aer.k.211215.085

Afifa, M., Khoirunnisa, R., Pratiwi, S.M.V., & Meitaza, D. (2024). Utilizing Rasch model to Analyze a Gender Gap in Students’ Scientific Literacy on Energy. Jurnal Pendidikan Fisika Indonesia, 20(1):85–95. https://doi.org/10.15294/jpfi.v20i1.44472

Andrich, D. (1988). Rasch Models for Measurement. Sage.

Aryani, I., Pramudita, D. A., Sinangkling, N.N., Tama, I. D. A. (2023). Development of Android-Based Learning Media Applications to Determine Validity and Feasibility for Grade VII Middle School Students on Ecosystem Material. Jurnal IPA & Pembelajaran IPA, 7(1), 72–85. https://doi.org/10.24815/jipi.v7i1.28885

Avinç, E., & Doğan, F. (2024). Digital literacy scale: Validity and reliability study with the rasch model. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12662-7

Azizah, A. & Wahyuningsih, S. (2020). Penggunaan Model Rasch untuk Analisis Instrumen Tes Pada Mata Kuliah Matematika Aktuaria. Jupitek: Jurnal Pendidikan Matematika, 3(1):45–50. https://doi.org/10.30598/jupitekvol3iss1pp45-50

Babcock, B., & Hodge, K. J. (2020). Rasch Versus Classical Equating in the Context of Small Sample Sizes. Educational and Psychological Measurement, 80(3), 499–521. https://doi.org/10.1177/0013164419878483

Bautista-Puig, N., Aleixo, A. M., Leal, S., Azeiteiro, U., & Costas, R. (2021). Unveiling the Research Landscape of Sustainable Development Goals and Their Inclusion in Higher Education Institutions and Research Centers: Major Trends in 2000–2017. Frontiers in Sustainability, 2. https://doi.org/10.3389/frsus.2021.620743

Blanchin, M., Guilleux, A., Hardouin, J.-B., & Sébille, V. (2020). Comparison of structural equation modelling, item response theory and Rasch measurement theory-based methods for response shift detection at item level: A simulation study. Statistical Methods in Medical Research, 29(4), 1015–1029. https://doi.org/10.1177/0962280219884574

Boone, W. J., & Noltemeyer, A. (2017). Rasch analysis: A primer for school psychology researchers and practitioners. Cogent Education, 4(1), 1416898. https://doi.org/10.1103/PhysRevPhysEducRes.15.020111

Briggs, D. C. (2019). Interpreting and visualizing the unit of measurement in the Rasch Model. Measurement, 146, 961–971. https://doi.org/10.1016/j.measurement.2019.07.035

Chhapola, V., Tiwari, S., Deepthi, B., & Kanwal, S. K. (2018). Citation classics in pediatrics: a bibliometric analysis. World Journal of Pediatrics, 14(6), 607–614. https://doi.org/10.1007/s12519-018-0146-6

Chi, S., Wang, Z., & Liu, X. (2023). Assessment of Context-Based Chemistry Problem-Solving Skills: Test Design and Results from Ninth-Grade Students. Research in Science Education, 53(2), 295–318. https://doi.org/10.1007/s11165-022-10056-8

Darman, D. R., Suhandi, A., Kaniawati, I., Samsudin, A., & Wibowo, F. C. (2024). Development and Validation of Scientific Inquiry Literacy Instrument (SILI) Using Rasch Measurement Model. Education Sciences, 14(3), 322-328. https://doi.org/10.3390/educsci14030322

Dawana, I. R., Dwikoranto, Setiani, R., & Marsini. (2022). E-Book Learning Research in Physics Education During the Last Five Years: A Review and Bibliometric Study. Journal of Physics: Conference Series, 2392(1), 12016. https://doi.org/10.1088/1742-6596/2392/1/012016

de Oliveira, O. J., da Silva, F. F., Juliani, F., Barbosa, L. C. F. M., & Nunhes, T. V. (2019). Bibliometric method for mapping the state-of-the-art and identifying research gaps and trends in literature: An essential instrument to support the development of scientific projects. In Scientometrics recent advances. IntechOpen. https://doi.org/10.5772/intechopen.85856

Desiriah, E., & Setyarsih, W. (2021). Tinjauan Literatur Pengembangan Instrumen Penilaian Kemampuan Berpikir Tingkat Tinggi (Hots) Fisika Di SMA. ORBITA: Jurnal Kajian, Inovasi Dan Aplikasi Pendidikan Fisika, 7(1), 79. https://doi.org/10.31764/orbita.v7i1.4436

Ding, C. (2022). Examining the context of better science literacy outcomes among U . S . schools using visual analytics : A machine learning approach. International Journal of Educational Research Open, 3(April), 100191. https://doi.org/10.1016/j.ijedro.2022.100191

Erfan, M., Maulyda, M. A., Ermiana, I., Hidayati, V. R., & Widodo, A. (2020). Validity and reliability of cognitive tests study and development of elementary curriculum using Rasch model. Psychology, Evaluation, and Technology in Educational Research, 3(1), 26–33. https://doi.org/10.33292/petier.v3i1.51

Guttersrud, O., & Petterson, K. S. (2015). Young adolescents’ engagement in dietary behaviour - The impact of gender, socio-economic status, self-efficacy and scientific literacy. Methodological aspects of constructing measures in nutrition literacy research using the Rasch model. Public Health Nutrition, 18(14), 2565–2574. https://doi.org/10.1017/S1368980014003152

Hidaayatullaah, H. N., Suprapto, N., Hariyono, E., Prahani, B. K., & Wulandari, D. (2021). Research trends on ethnoscience based learning through bibliometric analysis: Contributed to physics learning. Journal of Physics: Conference Series, 2110(1), 12026. https://doi.org/10.1088/1742-6596/2110/1/012026

Hizqiyah, I. Y. N., Widodo, A., Sriyati, S., & Ahmad, A. (2023). Development of a Digital Problem Solving Skills Test Instrument: Model Rasch Analysis. Jurnal Penelitian Pendidikan IPA, 9(4), 1658–1663. https://doi.org/10.29303/jppipa.v9i4.2671

Irwan, A. P. (2020). Analisis Kemampuan Literasi Sains Pesrta Didik Ditinjau Dari Kemampuan Menyelesaikan Soal Fisika Di SMAN 2 Bulukumba. Jurnal Sains Dan Pendidikan Fisika, 15(3), 17–24. https://doi.org/10.35580/jspf.v15i3.13494

Karakose, T., Tülübaş, T., & Papadakis, S. (2022). Revealing the Intellectual Structure and Evolution of Digital Addiction Research: An Integrated Bibliometric and Science Mapping Approach. International Journal of Environmental Research and Public Health, 19(22), 14883. https://doi.org/10.3390/ijerph192214883

Kazemi, S., Ashraf, H., Motallebzadeh, K., & Zeraatpishe, M. (2020). Development and validation of a null curriculum questionnaire focusing on 21st century skills using the Rasch model. Cogent Education, 7(1), 1736849. https://doi.org/10.1080/2331186X.2020.1736849

Khalaf, M. A., & Omara, E. M. N. (2022). Rasch analysis and differential item functioning of English language anxiety scale (ELAS) across sex in Egyptian context. BMC Psychology, 10(1), 242-246. https://doi.org/10.1186/s40359-022-00955-w

Lestari, A., & Samsudin, A. (2020). Using Rasch Model Analysis to Analyze Students’ Scientific Literacy on Heat and Temperature. Proceedings of the Proceedings of the 7th Mathematics, Science, and Computer Science Education International Seminar, MSCEIS 2019, 12 October 2019, Bandung, West Java, Indonesia. https://doi.org/10.4108/eai.12-10-2019.2296483

Lia, R. M., Rusilowati, A., & Isnaeni, W. (2020). NGSS-oriented chemistry test instruments: Validity and reliability analysis with the Rasch model. REiD (Research and Evaluation in Education), 6(1), 41–50. http://dx.doi.org/10.21831/reid.v6i1.30112

Marfu’i, L. N. R., Ilfiandra, & Nurhudaya. (2019). The analysis of critical thinking skills test in social-problems for physics education students with Rasch Model. Journal of Physics: Conference Series, 1280(5), 052012. https://doi.org/10.1088/1742-6596/1280/5/052012

Martha, A. S. D., Junus, K., Santoso, H. B., & Suhartanto, H. (2021). Assessing Undergraduate Students’ e-Learning Competencies: A Case Study of Higher Education Context in Indonesia. Education Sciences, 11(4), 189-207. https://doi.org/10.3390/educsci11040189

Maryati, M., Prasetyo, Z. K., Wilujeng, I., & Sumintono, B. (2019). Measuring Teachers’ Pedagogical Content Knowledge Using Many-Facet Rasch Model. Jurnal Cakrawala Pendidikan, 38(3), 452–464. https://doi.org/10.21831/cp.v38i3.26598

Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: a comparative analysis. Scientometrics, 106, 213–228 (2016). https://doi.org/10.1007/s11192-015-1765-5

Mubarokah, N., Permanasari, A., & Eliyawati, E. (2021). A case study of scientific literacy in natural science subject using rasch analysis model (RAM). Journal of Physics: Conference Series, 1806(1), 012144. https://doi.org/10.1088/1742-6596/1806/1/012144

Nur, L., Yulianto, A., Suryana, D., Malik, A. A., Al Ardha, M. A., & Hong, F. (2022). An Analysis of the Distribution Map of Physical Education Learning Motivation through Rasch Modeling in Elementary School. International Journal of Instruction, 15(2), 815–830. https://doi.org/10.29333/iji.2022.15244a

OECD. (2019). PISA 2018 Science Framework, in PISA 2018 Assesment and Analytical Framework. In OECD Publishing. https://doi.org/10.1787/b25efab8-en

Pizzi, S., Caputo, A., Corvino, A., & Venturelli, A. (2020). Management research and the UN sustainable development goals (SDGs): A bibliometric investigation and systematic review. Journal of Cleaner Production, 276, 124033. https://doi.org/10.1016/j.jclepro.2020.124033

Planinic, M., Boone, W. J., Susac, A., & Ivanjek, L. (2019). Rasch analysis in physics education research: Why measurement matters. Physical Review Physics Education Research, 15(2), 20111. https://doi.org/10.1103/PhysRevPhysEducRes.15.020111

Prahani, B. K., Dawana, I. R., Jatmiko, B., & Amelia, T. (2023). Research Trend of Big Data in Education During the Last 10 Years. International Journal of Emerging Technologies in Learning, 18(10, pp. 39-64. https://doi.org/10.3991/ijet.v18i10.38453

Purnami, W., Fauzi, A., & Naingalis, M. L. P. (2023, June). Computational thinking skills identification among students of physics education department using Rasch model analysis. In AIP Conference Proceedings (Vol. 2751, No. 1). AIP Publishing. https://doi.org/10.1063/5.0143158

Rahayu, W., Putra, M. D. K., Iriyadi, D., Rahmawati, Y., & Koul, R. B. (2020). A Rasch and factor analysis of an Indonesian version of the Student Perception of Opportunity Competence Development (SPOCD) questionnaire. Cogent Education, 7(1), 1721633. https://doi.org/10.1080/2331186X.2020.1721633

Ratnaningsih, I. Z., Prihatsanti, U., Prasetyo, A. R., & Sumintono, B. (2024). Validation of the Indonesian version of the psychological capital questionnaire (PCQ) in higher education: a Rasch analysis. Journal of Applied Research in Higher Education, 16(5), 480-496. https://doi.org/10.1108/JARHE-10-2023-0480

Romine, W. L., Sadler, T. D., & Kinslow, A. T. (2017). Assessment of scientific literacy: Development and validation of the Quantitative Assessment of Socio‐Scientific Reasoning (QuASSR). Journal of Research in Science Teaching, 54(2), 274–295. https://doi.org/10.1002/tea.21368

Rosana, D., Widodo, E., Setianingsih, W., & Setyawarno, D. (2020). Developing assessment instruments of PISA model to measure students’ problem-solving skills and scientific literacy in junior high schools. Jurnal Pendidikan Sains Indonesia (Indonesian Journal of Science Education), 8(2), 292–305. https://doi.org/ 10.24815/jpsi.v8i2.17468

Rusilowati, A., Kurniawati, L., & Nugroho, S. E. (2016). Developing an Instrument of Scientific Literacy Asessment on the Cycle Theme. International Journal of Enviromnental & Science Education, 11(12), 5718–5727. https://doi.org/10.21831/reid.v6i1.30112

Saidi, S. S., & Siew, N. M. (2019). Reliability and Validity Analysis of Statistical Reasoning Test Survey Instrument Using the Rasch Measurement Model. International Electronic Journal of Mathematics Education, 14(3), 535–546. https://doi.org/10.29333/iejme/5755

Sakdiah, H., & Syahrani, S. (2022). Pengembangan Standar Isi Dan Standar Proses Dalam Pendidikan Guna Meningkatkan Mutu Pembelajaran Di Sekolah. Cross-Border, 5(1), 622–632. https://doi.org/jebma.v4n2.3829

Sunni, F. M., & Sunarti, T. (2023). Profil Kompetensi Literasi Sains Siswa SMA Konteks Fenomena Bencana Banjir Kabupaten Lamongan. 12(3), 11–17.

Susongko, P., Arfiani, Y., & Kusuma, M. (2021). Determination of Gender Differential Item Functioning in Tegal Students’ Scientific Literacy Skills with Integrated Science (SLiSIS) Test Using Rasch Model. Jurnal Pendidikan IPA Indonesia, 10(2), 270–281. https://doi.org/10.15294/jpii.v10i2.26775

Susongko, P., Kusuma, M., & Arfiani, Y. (2022). 3-dimensional scientific literacy assessment framework for senior high school science program students. The 3rd International Conference on Science Education (ICoSEd 2021), 020006(December), 1–7. https://doi.org/10.1063/5.0113936

Susongko, P., Kusuma, M., Arfiani, Y., Samsudin, A., & Aminudin, A. (2020). Revising of the Integrating Scientific Literacy Skills Scale (ISLS) with Rasch Model Analysis. Journal for the Education of Gifted Young Scientists, 8(4), 1583–1602. http://dx.doi.org/10.17478/jegys.781583

Susongko, P., Widiatmo, H., Kusuma, M., & Afiani, Y. (2019). Development of integrated science-based science literacy skills instruments using the Rasch model. Unnes Science Education Journal, 8(3): 277-292. https://doi.org/10.15294/usej.v8i3.31262

Tarigan, E. F., Nilmarito, S., Islamiyah, K., Darmana, A., & Suyanti, R. D. (2022). Analisis Instrumen Tes Menggunakan Rasch Model dan Software SPSS 22.0. Jurnal Inovasi Pendidikan Kimia, 16(2), 92–96. https://doi.org/10.15294/jipk.v16i2.30530

Tesio, L., Caronni, A., Simone, A., Kumbhare, D., & Scarano, S. (2024). Interpreting results from Rasch analysis 2. Advanced model applications and the data-model fit assessment. Disability and Rehabilitation, 46(3), 604–617. https://doi.org/10.1080/09638288.2023.2169772

Van der Lans, R. M., Van de Grift, W. J. C. M., & van Veen, K. (2018). Developing An Instrument For Teacher Feedback: Using the Rasch Model to Explore Teachers’ Development of Effective Teaching Strategies and Behaviors. The Journal of Experimental Education, 86(2), 247–264. https://doi.org/10.1080/00220973.2016.1268086

Van Zile-Tamsen, C. (2017). Using Rasch analysis to inform rating scale development. Research in Higher Education, 58(8), 922–933. https://doi.org/10.1007/s11162-017-9448-0

Woudstra, A. J., Meppelink, C. S., Pander Maat, H., Oosterhaven, J., Fransen, M. P., & Dima, A. L. (2019). Validation of the short assessment of health literacy (SAHL-D) and short-form development: Rasch analysis. BMC Medical Research Methodology, 19(1), 122. https://doi.org/10.1186/s12874-019-0762-4

Yirci, R., Karakose, T., Kocabas, I., Tülübaş, T., & Papadakis, S. (2023). A Bibliometric Review of the Knowledge Base on Mentoring for the Professional Development of School Administrators. Sustainability, 15(4), 3027. https://doi.org/10.3390/su15043027




DOI: https://doi.org/10.24815/jipi.v8i4.42307

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