ANALISIS POLYCHOTOMOUS RASCH MODEL UNTUK KALIBRASI SOAL ANALISIS REAL PADA PROGRAM STUDI TADRIS MATEMATIKA

  • Jerhi wahyu fernanda Institut Agama Islam Negeri (IAIN) Kediri
  • Eka Resti Wulan IAIN Kediri
Keywords: calibration, Partial Credit Model, Wrightmap

Abstract

Student scores in real analysis courses are still not optimal with some students still having grades in the lower category. Efforts that can be made is to ensure that the exam questions are appropriate to be used to measure student abilities. Calibration of exam questions is carried out to ensure that the questions used are accurate in predicting participants' abilities. The Polychotomous Rasch Model is the development of the Rasch model which is used for polychotomous cases. Partial Credit Model (PCM) is part of the Polychotomous Rasch Model which is used to analyze polychotomous questions where each question has a different category. This study aims to examine the feasibility of midterm and final semester exam questions for real analysis courses in the form of essay questions using the PCM method in the Mathematics Tadris study program at IAIN Kediri. Research uses the type of research and development. The instrument used is a matter of real analysis ability which is essay in nature and consists of 10 questions. Data collection is done by using total sampling technique. The results of the descriptive statistical analysis showed that the average UTS and UAS scores were 64.53 and 56.42, respectively. The results of the analysis using PCM concluded that the UTS and UAS questions fulfilled validity because they had infit and outfit values in the specified range. The results of the analysis through the wright map provide wrightmap information. Information is obtained for the easiest midterm exam question which is question number 6 and the most difficult is question number 5. In the wrightmap image for UAS questions, the easiest question is question number 1 and the most difficult is question number 5.

References

Bond, T. G., Yan, Z., & Heene, M. (2021). Applying the Rasch Model: Fundamental Measurement in the Human Sciences (4th ed.). New York: Routledge.

Dogan, E. (2018). An application of the partial credit IRT model in identifying benchmarks for polytomous rating scale instruments. Practical Assessment, Research and Evaluation, 23(7), 1–10.

Fernanda, J. W., & Hidayah, N. (2020). Classical Test Theory dan Rasch Model. SQUARE : Journal of Mathematics and Mathematics Education, 2(1), 49–60. https://doi.org/https://doi.org/10.21580/square.2020.2.1.5363

Hamad, M., Rude, N., Mesbah, M., Siu-Paredes, F., & Denis, F. (2022). Study of the Unidimensionality of the Subjective Measurement Scale of Schizophrenia Coping Oral Health Profile and Index: SCOOHPI. Behavioral Sciences, 12(11), 442. https://doi.org/10.3390/bs12110442

Magdalena, I., Fauzi, H. N., & Putri, R. (2020). Pentingnya Evaluasi Dalam Pembelajaran Dan Akibat Memanipulasinya. Jurnal Pendidikan Dan Sains, 2(2), 244–257. https://ejournal.stitpn.ac.id/index.php/bintang

Nurhasanah, N. (2018). Pengembangan Tes Untuk Mengukur Kemampuan Penalaran Mahasiswa Mata Kuliah Geometri. Pepatudzu : Media Pendidikan Dan Sosial Kemasyarakatan, 14(1), 62. https://doi.org/10.35329/fkip.v14i1.186

Nuryanti, S., Masykuri, M., & Susilowati, E. (2018). Analisis iteman dan model rasch pada pengembangan instrumen kemampuan berpikir kritis peserta didik sekolah menengah kejuruan. Jurnal Inovasi Pendidikan IPA, 4(2), 224–233. http://journal.uny.ac.id/index.php/jipi

Osiesi, M. P. (2020). Educational Evaluation: Functions, Essence and Applications in Primary Schools’ Teaching and Learning. Society & Sustainability, 2(2), 1–9. https://doi.org/10.38157/society_sustainability.v2i2.134

Ravand, H., & Firoozi, T. (2016). Examining construct validity of the master’s ueeusing the Rasch model and the six aspects of the Messick’s framework. International Journal of Language Testing, 6(1), 1–23.

Ul Hassan, M., & Miller, F. (2019). Optimal item calibration for computerized achievement tests. psychometrika, 84(4), 1101-1128.

Wahyuningsih, S. (2021). Using the Rasch’s Partial Credit Model to Analyze the Quality of an Essay Math Test. Proceedings of the 1st International Conference on Mathematics and Mathematics Education (ICMMEd 2020), 550(Icmmed 2020), 257–265. https://doi.org/10.2991/assehr.k.210508.073

Winarti, A., & Mubarak, A. (2019). Rasch Modeling: A Multiple Choice Chemistry Test. Indonesian Journal on Learning and Advanced Education (IJOLAE), 2(1), 1–9. https://doi.org/10.23917/ijolae.v2i1.8985

Wind, S. A., & Hua, C. (2022). Rasch Measurement Theory Analysis in R (First edit). CRC Press.

Wu, M., Tam, H. P., & Jen, T.-H. (2016). Educational Measurement for Applied Researchers Theory into Practice. Springer Nature Singapore Pte Ltd.

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(November 2014), 212–217. https://doi.org/10.1016/j.sbspro.2015.08.143

Khairani, A.Z.B. & Razak, N.B.A. (2015). Modeling a Multiple Choice Mathematics Test with the Rasch Model. Indian Journal of Science and Technology, 8(12), 1-6.

Published
2024-03-15
Section
Articles