Comparison of item characteristic analysis models of reading literacy test with polytomous Item Response Theory

Firyal Nabila Harsana, Universitas Negeri Yogyakarta, IndonesiaFollow
Heri Retnawati, Universitas Negeri Yogyakarta, IndonesiaFollow
Septinda Rima Dewanti, Islamic Queensland University of Technology, AustraliaFollow
Rogers Andrew Lumenyela, Institute of Rural Development Planning, United Republic of TanzaniaFollow
Maulana Fatahillah Adzima, Maulana Fatahillah Adzima, University of California Berkeley, United StatesFollow
Atut Reni Septiana, University of Manchester, United KingdomFollow

Keywords

GPCM;Item Response Theory;reading literacy test;polytomous

Document Type

Article

Abstract

This study aims to compare the analysis model of the characteristics of reading literacy items with the polytomous item response theory, which uses the Graded Response Model (GRM), Partial Credit Model (PCM), Generalized Partial Credit Model (GPCM), and Nominal Reasons Model (NRM). This research is quantitative research in nature, and secondary datawere used from about 1000 test takers’ responses to reading literacy items in the 2018 reading literacy study analyzed with the R program. This model comparison was carried out so that the analysis results obtained were more accurate in representing the level of reading literacy skills in Indonesia. The results show that the GPCM model is the fit model with an AIC value of 23753.89 and a BIC value of 24042.45, and the number of suitable testlets is 7 out of a total of 7 testlets. Based on the relationship between information function scores and SEM, reading literacy items provide higher information when participants’ abilities range between -2.3 and +2

Page Range

214-226

Issue

Volume

Digital Object Identifier (DOI)

10.21831/reid.v10i2.77852

Recommended Citation

Harsana, F. N., Retnawati, H., Dewanti, S. R., Lumenyela, R. A., Adzima, M. F., & Septiana, A. R. (2023). Comparison of item characteristic analysis models of reading literacy test with polytomous Item Response Theory. REID (Research and Evaluation in Education), 10(2). https://doi.org/10.21831/reid.v10i2.77852

References

Bahar, R., & Retnawati, H. (2022). Analisis karakteristik soal kemampuan koneksi matematika penskoran politomus. Jurnal Tarbiyah, 29(2), 195-211. http://dx.doi.org/10.30829/tar.v29i2.1650

Bichi, A. A., & Talib, R. (2018). Item response theory: An introduction to latent trait models to test and item development. International Journal of Evaluation and Research in Education (IJERE), 7(2), 142â151. http://doi.org/10.11591/ijere.v7i2.12900

Bock, R. D. (1972). Estimating item parameters and latent ability when responses are scored in two or more nominal categories. Psychometrika, 37, 29-51. https://doi.org/10.1007/BF02291411

Boliti, S. (2017). Peningkatan kemampuan membaca pemahaman siswa kelas IV SDN 1 Lumbi-Lumbia melalui metode latihan terbimbing. Jurnal Kreatif Tadulako, 2(2), 12-23.

Hambleton, R. K., Swaminathan, H., & Rogers, H. J. (1991). Fundamentals of item response theory. Sage Publications Inc.

Hambleton, R. K., & van der Linden, W. J. (1982). Advances in item response theory and applications: An introduction. Applied Psychological Measurement, 6(4), 373-378. https://doi.org/10.1177/014662168200600401

Hikamudin, E. (2017). Estimasi kemampuan siswa dalam ujian nasional menggunakan metode bayes. Jurnal Penelitian Kebijakan Pendidikan, 10(2), 1-14. https://doi.org/10.24832/jpkp.v10i2.171

Isgiyanto, A. (2013). Perbandingan penyekoran model rasch dan model partial credit pada matematika. Jurnal Kependidikan: Penelitian Inovasi Pembelajaran, 43(1), 9-18. https://journal.uny.ac.id/index.php/jk/article/view/1954

Krismanto, W., Halik, A., & Sayidiman, S. (2015). Meningkatkan kemampuan membaca pemahaman melalui metode survey, question, read, recite, review (SQ3R) pada siswa kelas IV SD Negeri 46 Parepare. Publikasi Pendidikan: Jurnal Pemikiran, Penelitian dan Pengabdian Masyarakat Bidang Pendidikan, 5(3). http://dx.doi.org/10.26858/publikan.v5i3.1616

Language Development and Fostering Agency. (2018). Laporan kajian bahan kebijakan teknis literasi nasional tahun 2018. Badan Pengembangan dan Pembinaan Bahasa Kementerian Pendidikan dan Kebudayaan.

Lee, G., Brennan, R. L., & Frisbie, D. A. (2000). Incorporating the testlet concept in test score analyses. Educational Measurement: Issues and Practice, 19(4), 9-15. http://dx.doi.org/10.1111/j.1745-3992.2000.tb00041.x

Manfaat, B., & Anasha, Z. Z. (2013). Analisis kemampuan berpikir kritis matematik siswa dengan menggunakan graded response models (grm). In Seminar Nasional Matematika dan Pendidikan Matematika under the theme âPenguatan Peran Matematika dan Pendidikan Matematika untuk Indonesia yang Lebih Baikâ (pp. 119-124).

Mariati, I. (2009). Analisis butir soal dengan teori tes klasik (classical test theory) dan teori respons butir (item response theory) (Studi kasus: Soal ujian olimpiade sains provinsi bidang informatika 2009). PYTHAGORAS Jurnal Pendidikan Matematika, 5(2), 1-13. https://doi.org/10.21831/pg.v5i2.536

Muraki, E. (1992). A generalized partial credit model: Application of an EM algorithm. Applied Psychology Measurement, 16, 159-176. https://doi.org/10.1177/014662169201600206

Noriasih, N. K. (2013). Pengaruh model pembelajaran reciprocal teaching terhadap pemahaman bacaan ditinjau dari konsep diri akademik siswa. Jurnal IKA, 11(2), 27-45. https://ejournal.undiksha.ac.id/index.php/IKA/article/view/1987

OECD. (2022). PISA 2022 results: Factsheets. OECD Publishing. https://www.oecd.org/en/publications/pisa-results-2022-volume-iii-factsheets_041a90f1-en/indonesia_a7090b49-en.html

Paek, I., & Cole, K. (2020). Using R for item response theory model applications. Routledge.

R Core Team. (2022). R: A language and environment for statistical computing. https://www.R-project.org/

Retnawati, H. (2014). Teori respons butir dan penerapannya (Untuk peneliti, praktisi, pengukuran, dan pengujian, mahasiswa pascasarjana). Parama Publishing.

Retnawati, H. (2016). Analisis kuantitatif instrumen penelitian. Parama Publishing.

Safari. (2000). Panduan analisis butir soal. http://www.dikmenum.go.id/

Safitri, A. (2020). Perbandingan estimasi kemampuan literasi matematika kelas VIII di Kota Sragen dengan berbagai model penskoran. Master Thesis, Universitas Negeri Yogyakarta, Yogyakarta.

Santoso, A., Pardede, T., Djidu, H., Apino, E., Rafi, I., Rosyada, M. N., & Abd Hamid, H. S. (2022). The effect of scoring correction and model fit on the estimation of ability parameter and person fit on polytomous item response theory. REID (Research and Evaluation in Education), 8(2), 140-151. https://doi.org/10.21831/reid.v8i2.54429

Sumarna, S. (2006). Analisis, validitas, reabilitas dan interpretasi hasil tes implementasi kurikulum 2004. PT. Remaja Rosdakarya Offset.

Sumaryanta. (2021). Teori tes klasik & teori respon butir: Konsep & contoh penerapannya. Confident.

Susongko, P. (2010). Perbandingan keefektifan bentuk tes uraian dan teslet dengan penerapan graded response model (GRM). Jurnal Penelitian dan Evaluasi Pendidikan, 14(2), 269-288. https://doi.org/10.21831/pep.v14i2.1082

Tahmidaten, L., & Krismanto, W. (2020). Permasalahan budaya membaca di Indonesia (studi pustaka tentang problematika & solusinya). Scholaria: Jurnal Pendidikan dan Kebudayaan, 10(1), 22-33. https://doi.org/10.24246/j.js.2020.v10.i1.p22-33

Thissen, D., & Wainer, H. (2001). Test scoring. Routledge. https://doi.org/10.4324/9781410604729

Ulpiyanti, U. (2019). Analisis tes kemampuan berpikir kritis matematis siswa dengan menggunakan generalized partial credeit model (GPCM): Penelitian deskriptif kuantitatif di SMP negeri 56 Bandung. Doctoral Dissertation, UIN Sunan Gunung Djati Bandung, Bandung.

Linden, W. J., & Hambleton, R. K. (1997). Handbook of modern item response theory. Springer-Verlag. https://doi.org/10.1007/978-1-4757-2691-6

Wang, Z. & Osterlind S. J. (2013). Classical test theory. In T. Teo (Eds.), Handbook of quantitative methods for educational research. SensePublishers. https://doi.org/10.1007/978-94-6209-404-8_2

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