Rasch model item response theory (IRT) to analyze the quality of mathematics final semester exam test on system of linear equations in two variables (SLETV)

Adilla Desy Rizbudiani, Amat Jaedun, Abdul Rahim, Arief Nurrahman

Abstract


A high-quality test has a balanced level of difficulty and can be completed by the respondent with their level of abilities. This study analyzed the test instrument used to measure students' mathematics abilities in the semester final exam on System of Linear Equations in Two-Variables. The purposive sampling technique was applied to select the respondent students (N=195). The test items were twenty multiple-choice questions. The researchers performed the data analysis using Rasch model Item Response Theory (IRT) approach with the QUEST program. The analysis revealed that the twenty items’ validity matched the Rasch model with a range of INFIT MNSQ values between 0.89 – 1.17. Items on the final semester exam can be used based on the estimated OUTFIT t-value less than equal to 2.00. The OUTFIT t analysis obtained nineteen qualified items and one unqualified item.

 


Keywords


System of Linear Equations in Two Variables; Item Response Theory; Rasch Model.

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References


Achir, Y. S., Usodo, B., & Retiawan, R. (2017). Analisis kemampuan komunikasi matematis siswa dalam pemecahan masalah matematika pada materi sistem persamaan linear dua variabel (spldv) ditinjau dari gaya kognitif. Paedagogia, 20(1), 78. https://doi.org/10.20961/paedagogia.v20i1.16600

Agnesti, Y., & Amelia, R. (2020). Penerapan pendekatan kontekstual dalam menyelesaikan soal cerita pada materi perbandingan dan skala terhadap siswa SMP. Mosharafa : Jurnal Pendidikan Matematika, 9(2), 347–358. https://journal.institutpendidikan.ac.id/index.php/mosharafa/article/view/mv9n2_15

Al Ali, R. M. A., & Shehab, R. T. (2020). Psychometric properties of social perception of mathematics:‎‎ Rasch Model Analysis. International Education Studies, 13(12), 102. https://doi.org/10.5539/ies.v13n12p102

Alfarisa, F., & Purnama, D. N. (2019). Analisis butir soal ulangan akhir semester mata pelajaran ekonomi SMA menggunakan RASCH model. 11(2).

Ardiyanti, D. (2016). Aplikasi model rasch pada pengembangan skala efikasi diri dalam pengambilan keputusan karir siswa [application of the rasch model on the development of self-efficiency scale in student career decision making]. Jurnal Psikologi, 43(3), 248–263.

Asih, N., & Ramadhani, S. (2019). Peningkatan kemampuan pemecahan masalah matematis dan kemandirian belajar siswa menggunakan model pembelajaran means end analysis. Jurnal Pendidikan Matematika, 8(September), 12.

Asriadi, M., & Hadi, S. (2021). Implementation of item response theory at final exam test in physics learning: Rasch model study. Proceedings of the 6th International Seminar on Science Education (ISSE 2020), 541(Isse 2020), 336–342. https://doi.org/10.2991/assehr.k.210326.048

Ayub, M. R. S. S. N., Istiyono, E., Munadi, S., Permadi, C., Pattiserlihun, A., & Sudjito, D. N. (2020). Analisa penilaian soal fisika menggunakan model rasch dengan program r. jurnal sains dan edukasi sains, 3(2), 46–52. https://doi.org/10.24246/juses.v3i2p46-52

Azizah, & 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

Bashooir, K., & Supahar. (2018). Validitas dan reliabilitas instrumen asesmen kinerja literasi sains pelajaran fisika berbasis STEM. Jurnal Penelitian Dan Evaluasi Pendidikan, 22(2), 168–181. https://doi.org/10.21831/pep.v22i2.20270

Bey, A., & Asriani. (2013). Penerapan pembelajaran problem solving untuk meningkatkan aktivitas dan hasil belajar matematika pada materi SPLDV. Jurnal Pendidikan Matematika, 4(2), 224–239. https://doi.org/10.36709/jpm.v4i2.2035

Bozdağ, H. C., & Türkoğuz, S. (2021). A rasch model analysis of primary school students’ conceptual understanding levels of the concept of light. IOJPE: International Online Journal of Primary Education, 10(1), 160–179.

Chan, S. W., Looi, C. K., & Sumintono, B. (2021). Assessing computational thinking abilities among Singapore secondary students: A rasch model measurement analysis. Journal of Computers in Education, 8(2), 213–236. https://doi.org/10.1007/s40692-020-00177-2

Che Lah, N. H., Tasir, Z., & Jumaat, N. F. (2021). Applying alternative method to evaluate online problem-solving skill inventory (OPSI) using Rasch model analysis. Educational Studies, 00(00), 1–23. https://doi.org/10.1080/03055698.2021.1874310

Cotet, G. B., Carutasu, N. L., & Chiscop, F. (2020). Industry 4.0 diagnosis from an imillennial educational perspective. Education Science, 10.

Hambleton, R. K., Swaminathan, H., & Rogers, D. J. (1991). Fundamentals of item response theory library of congress cataloging-in-publication data.

Himelfarb, I. (2019). A primer on standardized testing: History, measurement, classical test theory, item response theory, and equating. Journal of Chiropractic Education, 33(2), 151–163. https://doi.org/10.7899/JCE-18-22

Isnani, I., Utami, W. B., Susongko, P., & Lestiani, H. T. (2019). Estimation of college students’ ability on real analysis course using Rasch model. Research and Evaluation in Education, 5(2), 95–102. https://doi.org/10.21831/reid.v5i2.20924

Johari, A. B., Wahat, N. W. A., & Zaremohzzabieh, Z. (2021). Innovative work behavior among teachers in Malaysia: The effects of teamwork, principal support, and humor. Asian Journal of University Education, 17(2), 72–84. https://doi.org/10.24191/AJUE.V17I2.13387

Mardapi, D. (2012). Pengukuran, penilaian & evaluasi pendidikan. Nuha Medika.

Murtiyasa, B., & Al Karomah, I. I. (2020). The impact of learning strategy of problem solving and discovery towards learning outcomes reviewed from students learning motivation. Universal Journal of Educational Research, 8(9), 4105–4112. https://doi.org/10.13189/ujer.2020.080936

Nasution, D. P., & Ahmad, M. (2018). Penerapan pembelajaran matematika realistik untuk meningkatkan kemampuan komunikasi matematis siswa. Mosharafa: Jurnal Pendidikan Matematika, 7(3), 389–400. https://doi.org/10.31980/mosharafa.v7i3.133

Nielsen, T., Martínez-García, I., & Alastor, E. (2021). Critical thinking of psychology students: A within- and cross-cultural study using rasch models. Scandinavian Journal of Psychology, 62(3), 426–435. https://doi.org/10.1111/sjop.12714

Noortsani, I. (2019). Meningkatkan kualitas proses pembelajaran melalui penerapan model pembelajaran. Simpul Juara, 1(1).

Palimbong, J., Mujasan, & Allo, A. Y. T. (2018). Item analysis using rasch model in semester final exam evaluation study subject in physics class X TKJ SMK negeri 2 Manokwari. Kasuari: Physics Education Journal, 1(1), 48–51. i.yusuf@unipa.ac.id

Panyahuti, Krismadinata, Jalinus, N., Rahmat, R., & Ambiyar, A. (2020). Analisis pemetaan kemampuan numerik siswa smk model teori respon butir. INVOTEK: Jurnal Inovasi Vokasional Dan Teknologi, 20(3), 11–22. https://doi.org/10.24036/invotek.v20i3.640

Pratama, D. (2020). Analisis kualitas tes buatan guru melalui pendekatan item response theory (IRT) model rasch. Tarbawy : Jurnal Pendidikan Islam, 7(1), 61–70. https://doi.org/10.32923/tarbawy.v7i1.1187

Primi, C., Morsanyi, K., Chiesi, F., Donati, M. A., & Hamilton, J. (2016). The development and testing of a new version of the cognitive reflection test applying item response theory (IRT). Journal of Behavioral Decision Making, 29(5), 453–469. https://doi.org/10.1002/bdm.1883

Purnamasari, U. D., & Kartowagiran, B. (2019). Application rasch model using R program in analyze the characteristics of chemical items. Jurnal Inovasi Pendidikan IPA, 5(2), 147–157. https://doi.org/10.21831/jipi.v5i2.24235

Purwandari, A. S., Astuti, M. D., & Yuliani, A. (2018). Evaluasi kemampuan komunikasi matematis siswa smp pada materi sistem persamaan linear dua variabel. IndoMath: Indonesia Mathematics Education, 1(1), 55. https://doi.org/10.30738/indomath.v1i1.2219

Rachmawati, Y. I., Sugandi, E., & Prayitno, L. L. (2019). Senior high school student’s ability in posing system of linear equations in two variables problems. JRAMathEdu (Journal of Research and Advances in Mathematics Education), 4(1), 57–65. https://doi.org/10.23917/jramathedu.v4i1.6954

Rahayu, W., Putra, M. D. K., Rahmawati, Y., Hayat, B., & Koul, R. B. (2021). Validating an indonesian version of the what is happening in this class? (WIHIC) questionnaire using a multidimensional rasch model. International Journal of Instruction, 14(2), 919–934. https://doi.org/10.29333/iji.2021.14252a

Ramdani, R., Hanurawan, F., Ramli, M., Lasan, B. B., & Afdal, A. (2020). Development and validation of Indonesian academic resilience scale using rasch models. International Journal of Instruction, 14(1), 105–120. https://doi.org/10.29333/IJI.2021.1417A

Rojas-kramer, C. A., Moreno-García, E., & Venegas-Martínez, F. (2020). Anxiety Determinants towards mathematics in mexican high school students. European Journal of Contemporary Education, 9(4), 866–877. https://doi.org/10.13187/ejced.2020.4.866

Sainuddin, S. (2018). Analisis karakteristik butir tes matematika berdasarkan teori modern (teori respon butir). Jurnal Penelitian Matematika Dan Pendidikan Matematika, 1(1), 1–12.

Schunk, D. H., & DiBenedetto, M. K. (2020). Motivation and social cognitive theory. Contemporary Educational Psychology, 60, 101832. https://doi.org/10.1016/j.cedpsych.2019.101832

Scoulas, J. M., Aksu Dunya, B., & De Groote, S. L. (2021). Validating students’ library experience survey using rasch model. Library and Information Science Research, 43(1), 101071. https://doi.org/10.1016/j.lisr.2021.101071

Slavinec, M., Aberšek, B., Gačević, D., & Flogie, A. (2019). Monddisciplinarity in science versus transdiciplinarity in STEM education. Journal of Baltic Science, 18(3), 435–449.

Stewart, J., Zabriskie, C., Devore, S., & Stewart, G. (2018). Multidimensional item response theory and the force concept inventory. Physical Review Physics Education Research, 14(1), 10137. https://doi.org/10.1103/PhysRevPhysEducRes.14.010137

Sumintono, B., & Widhiarso, W. (2015). Aplikasi pemodelan rasch pada assessment pendidikan. trim komunikata.

Suryani, M., Jufri, L. H., & Putri, T. A. (2020). Analisis kemampuan pemecahan masalah siswa berdasarkan kemampuan awal. Musharafa: Jurnal Pendidikan Matematika, 9(1), 119–130. https://journal.institutpendidikan.ac.id/index.php/mosharafa/article/view/mv9n1_11, diakses Rabu ‎2 Juni ‎2021

Susdelina, Perdana, S. A., & Febrian. (2018). Analisis kualitas instrumen pengukuran pemahaman konsep persamaan kuadrat melalui teori tes klasik dan rasch model. Jurnal Kiprah, 6(1), 41–48. https://doi.org/10.31629/kiprah.v6i1.574

Syafitri, Q., Mujib, Anwar, C., Netriwati, & Wawan. (2018). The mathematics learning media uses geogebra on the basic material of linear equations. Al Jabar: Jurnal Pendidikan Matematika, I, 9–18.

Tseng, M. C., & Wang, W. C. (2021). The q-matrix anchored mixture rasch model. Frontiers in Psychology, 12(March), 1–9. https://doi.org/10.3389/fpsyg.2021.564976

Yulistianti, H. D., & Megawati, E. (2019). Analisis instrumen tes higher order thinking. Jurnal Pendidikan Matematika, 13(1), 41–54.

Yusuf, A., & Fitriani, N. (2020). Analisis kesalahan siswa smp dalam menyelesaikan soal persamaan linear dua variabel di SMPN 1 Campaka mulya-cianjur. Jurnal Pembelajaran Matematika Inovatif, 3(1), 59–68. https://doi.org/10.22460/jpmi.v3i1.p59-68

Zulkifli, F., Abidin, R. Z., Razi, N. F. M., Mohammad, N. H., Ahmad, R., & Azmi, A. Z. (2018). Evaluating quality and reliability of final exam questions for probability and statistics course using rasch model. International Journal of Engineering and Technology(UAE), 7(4), 32–36. https://doi.org/10.14419/ijet.v7i4.33.23479




DOI: http://dx.doi.org/10.24042/ajpm.v12i2.9939

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