One form of evaluation of student learning outcomes is the Final Semester Examination. This exam is designed to measure the extent of achievement of educational objectives. A good evaluation must meet several criteria, including good item validity and reliability, a variety of difficulty levels, and the power of differentiation. This study aims to describe the results of a comparative analysis of the quality of measurement instruments in the form of multiple-choice questions using the classical test theory approach and the Rasch model in terms of validity, reliability, difficulty level, and question differentiation. Data were obtained through a website that presents multiple choice exam results of grade XI students at SMA Negeri 3 Gorontalo, consisting of 26 female students and 10 male students. The results showed that in the instrument validity analysis, the Rasch model showed more valid items with a determination category of 0.4 < pt measure corr < 0.8. This means that the Rasch model provides a better analysis compared to the classical test theory analysis. In the reliability analysis, the reliability value of items in the Rasch model is higher but in almost the same category. In analyzing the difficulty level of the instrument, the classical test theory approach shows that the items are in the easy, medium, and difficult categories, so they are still considered capable of measuring students' abilities. However, in the Rasch model, items are only in the very easy, difficult, and extremely difficult categories. In analyzing the power of differentiation, the classical test theory method and the Rasch model have not provided good enough results to identify respondents in several groups based on their level of understanding
CITATION STYLE
Yulisharyasti, L., Nurdin, A., Aulia, N., Arfa, F. A. H., & Fadjryani. (2023). ANALYZING THE QUALITY OF MEASUREMENT INSTRUMENTS OF MULTIPLE CHOICE QUESTIONS ON CLASS XI ECONOMICS MATERIAL IN PUBLIC HIGH SCHOOL 3 GORONTALO THROUGH CLASSICAL TEST THEORY AND RASCH MODELS. Parameter: Journal of Statistics, 3(1), 28–38. https://doi.org/10.22487/27765660.2023.v3.i1.16417
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