Math elementary school exam analysis based on the Rasch model

Herwin Herwin, Department of Elementary School Education, Universitas Negeri Yogyakarta, Indonesia
Andi Tenriawaru, Sekolah Tinggi Keguruan dan Ilmu Pendidikan Yayasan Pendidikan Ujung Pandang, Indonesia
Abdoulaye Fane, University of Letters and Human Sciences of Bamako, Mali

Abstract


This study aims to analyze the quality of mathematics exam tests in elementary schools using the Rasch model. This research is a type of descriptive quantitative research. The subject of this study were all items of School Examination Mathematical Questions in SDN Region III of Donri Donri Subdistrict, Soppeng Regency. The Mathematics Problem is 40 items. Besides that, in this study, 125 answer sheets from the participants were collected from 125 participants. The technique of data collection is done through documentation. This data collection technique is used to get a set of questions, answers, and a list of names of examinees. The data obtained were analyzed using the Rasch Model. The results showed that based on the Rash Model of 40 items on the mathematics exam 33 items (82.5%) were in a good category, while the other seven items (17.5%) were in a bad category. Test results indicate that the test information value is 13.8 on the ability scale -1.5 with a measurement error of 0.26. 


Keywords


Math elementary school exam; rasch model

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References


Abdullah, H., Arsad, N., Hashim, F. H., Aziz, N. A., Amin, N., & Ali, S. H. (2012). Evaluation of students’ achievement in the final exam questions for microelectronic (KKKL3054) using the Rasch model. Procedia - Social and Behavioral Sciences, 60, 119–123. https://doi.org/10.1016/j.sbspro.2012.09.356

Ariffin, S. R., Omar, B., Isa, A., & Sharif, S. (2010). Validity and reliability Multiple Intelligent item using Rasch measurement model. In Procedia - Social and Behavioral Sciences (Vol. 9, pp. 729–733). https://doi.org/10.1016/j.sbspro.2010.12.225

Baker, F. B. (2001). The basics of item response theory. Clearinghouse on Assessment and Evaluation.

Baker, F. B., & Kim, S.-H. (2017). The basics of item response theory using R. Springer.

bin Abd. Razak, N., bin Khairani, A. Z., & Thien, L. M. (2012). Examining quality of mathemtics test items using Rasch model: Preminarily analysis. Procedia - Social and Behavioral Sciences, 69, 2205–2214. https://doi.org/10.1016/j.sbspro.2012.12.187

Bond, T. G., & Fox, C. M. (2001). Applying the Rasch model: Fundamental measurement in the human sciences. Psychology Press.

De Ayala, R. J. (2013). The theory and practice of item response theory. Guilford Publications.

Hambleton, R. K., & Swaminathan, H. (1985). Item response theory: Principles and applications. New York, N.Y.: Springer Science+Business Media. https://doi.org/10.1007/978-94-017-1988-9

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

Herwin, H. (2016). An application of the generalized logistic regression method in identifying DIF: Analysis of school examination in Soppeng. In International Conference on Educational Research and Evaluation (ICERE). Yogyakarta: Universitas Negeri Yogyakarta.

Herwin, H., & Heriyati, H. (2016). Identifikasi kecurangan peserta ujian melalui metode person fit. In Prosiding Seminar Nasional LPPM UNY: Meneguhkan Peran Penelitian dan Pengabdian kepada Masyarakat dalam Memuliakan Martabat Manusia (pp. 91–96). Yogyakarta: Universitas Negeri Yogyakarta.

Jacob, E. R., Duffield, C., & Jacob, A. M. (2019). Validation of data using RASCH analysis in a tool measuring changes in critical thinking in nursing students. Nurse Education Today, 76, 196–199. https://doi.org/10.1016/j.nedt.2019.02.012

Jennings, N. B., Slack, M. K., Mollon, L. E., & Warholak, T. L. (2016). Measurement characteristics of a concept classification exam using multiple case examples: A Rasch analysis. Currents in Pharmacy Teaching and Learning, 8(1), 31–38. https://doi.org/10.1016/j.cptl.2015.09.010

Linden, W. J. van der, & Hambleton, R. K. (1996). Handbook of modern item response theory. New York, N.Y.: Springer Science+Business Media. https://doi.org/10.1007/978-1-4757-2691-6 I.

Moghadamzadeh, A., Salehi, K., & Khodaie, E. (2011). A comparison the information functions of the item and test on one, two and three parametric model of the item response theory (IRT). Procedia - Social and Behavioral Sciences, 29, 1359–1367. https://doi.org/10.1016/j.sbspro.2011.11.374

Mohamed, A., Aziz, A., Zakaria, S., & Masodi, M. S. (2008). Appraisal of course learning outcomes using rasch measurement: a case study in information technology education. In Conference Proceeding 7th WSEAS International Conference on Artificial Intelligent, Knowledge Engineering and Databases (AIKED ‘08) (pp. 20–22).

Pathak, A., Patro, K., Pathak, M., & Valecha, M. (2013). Item response theory. International Journal of Computer Science and Mobile Computing, 2(11), 7–11.

Retnawati, H. (2014). Teori respons butir dan penerapannya: Untuk peneliti, praktisi pengukuran dan pengujian, mahasiswa pascasarjana. Yogyakarta: Nuha Medika.

Retnawati, H., Kartowagiran, B., Arlinwibowo, J., & Sulistyaningsih, E. (2017). Why are the mathematics national examination items difficult and what is teachers’ strategy to overcome it? International Journal of Instruction, 10(103), 257–276. https://doi.org/10.12973/iji.2017.10317a

Rizopoulos, D. (2006). ltm : An R package for latent variable modeling and item response theory analyses. Journal of Statistical Software, 17(5). https://doi.org/10.18637/jss.v017.i05

van der Linden, W. J., & Hambleton, R. K. (2013). Handbook of modern item response theory. Springer Science & Business Media.

Yang, S.-C., Tsou, M.-Y., Chen, E.-T., Chan, K.-H., & Chang, K.-Y. (2011). Statistical item analysis of the examination in anesthesiology for medical students using the Rasch model. Journal of the Chinese Medical Association, 74(3), 125–129. https://doi.org/10.1016/j.jcma.2011.01.027

Yasin, R. M., Yunus, F. A. N., Rus, R. C., Ahmad, A., & Rahim, M. B. (2015). Validity and reliability learning transfer item using Rasch measurement model. Procedia - Social and Behavioral Sciences, 204, 212–217. https://doi.org/10.1016/j.sbspro.2015.08.143

Zięba, A. (2014). The item information function in one and two-parameter logistic models – a comparison and use in the analysis of the results of school tests. Didactics of Mathematics, 10(10). https://doi.org/10.15611/dm.2013.10.08




DOI: https://doi.org/10.21831/jpe.v7i2.24450

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