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Journal articles on the topic 'Rasch model'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Otiv, Sunil. "The Rasch Model." Plastic and Reconstructive Surgery 131, no. 2 (2013): 283e—286e. http://dx.doi.org/10.1097/prs.0b013e318278d5ac.

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2

van der Linden, Wim J. "Applying the Rasch Model." International Journal of Testing 1, no. 3-4 (2001): 319–26. http://dx.doi.org/10.1080/15305058.2001.9669478.

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3

SNYDER, SCOTT, and ROBERT SHEEHAN. "The Rasch Measurement Model." Journal of Early Intervention 16, no. 1 (1992): 87–95. http://dx.doi.org/10.1177/105381519201600108.

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4

Wang, Wen-Chung, and Mark Wilson. "The Rasch Testlet Model." Applied Psychological Measurement 29, no. 2 (2005): 126–49. http://dx.doi.org/10.1177/0146621604271053.

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5

van der Linden, Wim. "Applying the Rasch Model." International Journal of Testing 1, no. 3 (2001): 319–26. http://dx.doi.org/10.1207/s15327574ijt013&4_10.

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6

Robitzsch, Alexander. "Regularized Mixture Rasch Model." Information 13, no. 11 (2022): 534. http://dx.doi.org/10.3390/info13110534.

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The mixture Rasch model is a popular mixture model for analyzing multivariate binary data. The drawback of this model is that the number of estimated parameters substantially increases with an increasing number of latent classes, which, in turn, hinders the interpretability of model parameters. This article proposes regularized estimation of the mixture Rasch model that imposes some sparsity structure on class-specific item difficulties. We illustrate the feasibility of the proposed modeling approach by means of one simulation study and two simulated case studies.

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7

Sen, Sedat, Allan S. Cohen, and Seock-Ho Kim. "Model Selection for Multilevel Mixture Rasch Models." Applied Psychological Measurement 43, no. 4 (2018): 272–89. http://dx.doi.org/10.1177/0146621618779990.

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Mixture item response theory (MixIRT) models can sometimes be used to model the heterogeneity among the individuals from different subpopulations, but these models do not account for the multilevel structure that is common in educational and psychological data. Multilevel extensions of the MixIRT models have been proposed to address this shortcoming. Successful applications of multilevel MixIRT models depend in part on detection of the best fitting model. In this study, performance of information indices, Akaike information criterion (AIC), Bayesian information criterion (BIC), consistent Akai

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DeMars, Christine E. "Multilevel Rasch Modeling: Does Misfit to the Rasch Model Impact the Regression Model?" Journal of Experimental Education 88, no. 4 (2019): 605–19. http://dx.doi.org/10.1080/00220973.2019.1610859.

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9

Roskam, Edward E., and Paul G. W. Jansen. "Conditions for rasch-dichotomizability of the unidimensional polytomous rasch model." Psychometrika 54, no. 2 (1989): 317–32. http://dx.doi.org/10.1007/bf02294523.

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10

Weitzman, R. A. "The Rasch Model Plus Guessing." Educational and Psychological Measurement 56, no. 5 (1996): 779–90. http://dx.doi.org/10.1177/0013164496056005005.

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11

Maier, Kimberly S. "A Rasch Hierarchical Measurement Model." Journal of Educational and Behavioral Statistics 26, no. 3 (2001): 307–30. http://dx.doi.org/10.3102/10769986026003307.

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In this article, a hierarchical measurement model is developed that enables researchers to measure a latent trait variable and model the error variance corresponding to multiple levels. The Rasch hierarchical measurement model (HMM) results when a Rasch IRT model and a one-way ANOVA with random effects are combined ( Bryk & Raudenbush, 1992 ; Goldstein, 1987 ; Rasch, 1960 ). This model is appropriate for modeling dichotomous response strings nested within a contextual level. Examples of this type of structure include responses from students nested within schools and multiple response strin

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Andrich, David. "Controversy and the Rasch Model." Medical Care 42, Supplement (2004): I—7. http://dx.doi.org/10.1097/01.mlr.0000103528.48582.7c.

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13

Holster, Trevor A., and J. Lake. "Guessing and the Rasch Model." Language Assessment Quarterly 13, no. 2 (2016): 124–41. http://dx.doi.org/10.1080/15434303.2016.1160096.

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14

Kelderman, Henk. "Common Item Equating Using the Loglinear Rasch Model." Journal of Educational Statistics 13, no. 4 (1988): 319–36. http://dx.doi.org/10.3102/10769986013004319.

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A method is proposed to equate different sets of items administered to different groups of individuals using the Rasch model. A Rasch equating model is formulated that describes one common Rasch scale in different groups with different but overlapping sets of items. The item parameters can then be estimated simultaneously, avoiding different parameter estimates of common items in different groups. The model can be tested globally to test the hypothesis of one common Rasch scale, and the goodness of link can be tested. The method is based on the quasi-loglinear Rasch model.

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Robitzsch, Alexander. "Relating the One-Parameter Logistic Diagnostic Classification Model to the Rasch Model and One-Parameter Logistic Mixed, Partial, and Probabilistic Membership Diagnostic Classification Models." Foundations 3, no. 3 (2023): 621–33. http://dx.doi.org/10.3390/foundations3030037.

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Diagnostic classification models (DCMs) are statistical models with discrete latent variables (so-called skills) to analyze multiple binary variables (i.e., items). The one-parameter logistic diagnostic classification model (1PLDCM) is a DCM with one skill and shares desirable measurement properties with the Rasch model. This article shows that the 1PLDCM is indeed a latent class Rasch model. Furthermore, the relationship of the 1PLDCM to extensions of the DCM to mixed, partial, and probabilistic memberships is treated. It is argued that the partial and probabilistic membership models are also

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16

Nitta, Hideo, and Takuya Aiba. "An Alternative Learning Gain Based on the Rasch Model." Physics Educator 01, no. 01 (2019): 1950005. http://dx.doi.org/10.1142/s2661339519500057.

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Using the Rasch model for the pretest–posttest analysis, a learning gain, the “Rasch gain”, is introduced as the simple difference of the estimated ability parameter for students. It is shown that, although the Rasch gain strongly correlates with the normalized learning gain introduced by Hake, the Rasch gain has advantages over the Hake gain as a scientific measure.

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17

de Jong, John H. A. L. "Le Modele De Rasch." Taaltoetsen 31 (January 1, 1988): 57–70. http://dx.doi.org/10.1075/ttwia.31.07jon.

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This paper provides an elementary introduction to the one parameter psychometric model known as the Rasch model. It explains the basic principles underlying the model and the concepts of unidimensionality, local stochastic independence, and additivity in non-mathematical terms. The requirements of measurement procedures, the measurement of latent traits, the control on model fit, and the definition of a trait are discussed. It is argued that the Rasch model is particularly appropriate to understand the mutual dependence of test reliability and validity. Examples from foreign language listening

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Khotimah, Khotimah, Tb Sofwan Hadi, and Indri Lestari. "Application of The Rasch Model in Research Publications: A Bibliometric Analysis." Plusminus: Jurnal Pendidikan Matematika 4, no. 2 (2024): 229–40. https://doi.org/10.31980/plusminus.v4i2.1466.

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Model Rasch merupakan teknik yang ideal untuk menilai respons secara teratur dan meningkatkan analisis data. Model ini merupakan instrumen yang berguna untuk mengukur pencapaian dalam tes pendidikan dan psikologi. Namun, penting untuk mengidentifikasi potensi keterbatasan model dan mempelajarinya dalam penelitian di masa depan. Analisis bibliometrik penelitian digunakan untuk menentukan tren penelitian tentang penggunaan model Rasch. Pencarian literatur ekstensif dilakukan dengan menggunakan database scopus pada tanggal 19 Februari 2023, dengan menggunakan kata kunci "model Rasch". Temuan menu

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Tarigan, Elsa Febrina, Suriati Nilmarito, Khairani Islamiyah, Ayi Darmana, and Retno Dwi Suyanti. "Analisis Instrumen Tes Menggunakan Rasch Model dan Software SPSS 22.0." Jurnal Inovasi Pendidikan Kimia 16, no. 2 (2022): 92–96. http://dx.doi.org/10.15294/jipk.v16i2.30530.

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Penelitian ini bertujuan untuk membandingkan perbedaan validitas dan reliabilitas instrumen tes menggunakan Rasch model dan software SPSS 22.0. Penelitian ini merupakan penelitian kualitatif dengan metode deskriptif, yang di ujicobakan kepada 40 mahasiswa Universitas Negeri Medan yang berjumlah 40 butir soal dengan 5 opsi (a, b, c, d, dan e). Selanjutnya data yang diperoleh dianalisis melalui pendekatan teori tes klasik menggunakan bantuan program model Rasch dengan softwareWinsteps dan SPSS versi 22.0. Hasil penelitian menggunakan SPSS 22.0 dan Rasch model memiliki keakuratan validitas yang b

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Basran, Afiqah, and Denis Lajium. "APPLICATION OF RASCH MODEL IN TESTING FORCE CONCEPT INVENTORY." International Journal of Modern Education 2, no. 6 (2020): 14–27. http://dx.doi.org/10.35631/ijmoe.26003.

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Inventori Konsep Daya is an instrument that is adapted from the Force Concept Inventory (FCI). It is an instrument consisting of 30 diagnostic items related to the concept of force and motion. This instrument is widely used in physics education. However, the validity of this instrument in Bahasa Malaysia is not well studied to ensure that the items in the instrument function properly. Based on previous research, one of the major issues that are often questioned in the FCI is the reliability of the instrument when administered to different groups. When studies conducted in this country, researc

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Widhiarso, Wahyu. "APLIKASI MODEL RASCH CAMPURAN DALAM MENGEVALUASI PENGUKURAN HARGA DIRI." Jurnal Penelitian dan Evaluasi Pendidikan 17, no. 1 (2013): 172–87. http://dx.doi.org/10.21831/pep.v17i1.1367.

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Penelitian ini bertujuan untuk mengeksplorasi keberadaan kelompok responden yang menyebabkan estimasi parameter butir melalui pemodelan Rasch tidak invarian pada keseluruhan responden. Teknik analisis yang dipakai adalah model Rasch campuran yang merupakan penggabungan antara Model Rasch dan analisis kelas laten. Dengan menggunakan data hasil pengukuran harga diri didapatkan hasil analisis bahwa keseluruhan responden penelitian sebanyak 2.987 dapat dikategorikan menjadi tiga kelas berdasarkan pola respons mereka pada skala. Hasil estimasi parameter butir pada responden pada masing-masing kelas

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22

ZHAN, Peida, WANG Wen-Chung, Lijun WANG, and Xiaomin LI. "The Multidimensional Testlet-Effect Rasch Model." Acta Psychologica Sinica 46, no. 8 (2014): 1208. http://dx.doi.org/10.3724/sp.j.1041.2014.01208.

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23

Praekanata, I. Wayan Indra, Kadek Suranata, I. Ketut Gading, and Luh Putu Sri Lestari. "Analisis Politomi Rasch Model Skala PTSD." Jurnal Konseling dan Pendidikan 12, no. 4 (2024): 12–24. https://doi.org/10.29210/1119800.

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Post-Traumatic Stress Disorder (PTSD) is a significant mental health issue, particularly in Indonesia with its complex cultural diversity. This study aims to assess the validity of the Indonesian Version DSM-V PTSD scale using an Item Response Theory (IRT) approach through the Rasch model. The research method involved 70 respondents who experienced trauma, measured using a Likert scale consisting of 20 items. Data were collected from an online questionnaire and analysed using the Rasch Polytomous model. The results indicate that the PTSD scale has good reliability, with a Person Reliability va

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24

Smith, Richard M. "Person Fit in the Rasch Model." Educational and Psychological Measurement 46, no. 2 (1986): 359–72. http://dx.doi.org/10.1177/001316448604600210.

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25

Müller, Hans. "A rasch model for continuous ratings." Psychometrika 52, no. 2 (1987): 165–81. http://dx.doi.org/10.1007/bf02294232.

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26

Andersen, Erling B. "Residualanalysis in the polytomous rasch model." Psychometrika 60, no. 3 (1995): 375–93. http://dx.doi.org/10.1007/bf02294382.

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27

Glas, C. A. W. "The Rasch Model and Multistage Testing." Journal of Educational Statistics 13, no. 1 (1988): 45–52. http://dx.doi.org/10.3102/10769986013001045.

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This paper concerns the problem of estimating the item parameters of latent trait models in a multistage testing design. It is shown that using the Rasch model and conditional maximum likelihood estimates does not lead to solvable estimation equations. It is also shown that marginal maximum likelihood estimation, which assumes a sample of subjects from a population with a specified distribution of ability, will lead to solvable estimation equations, both in the Rasch model and in the Birnbaum model.

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Glas, C. A. W. "The Rasch Model and Multistage Testing." Journal of Educational Statistics 13, no. 1 (1988): 45. http://dx.doi.org/10.2307/1164950.

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29

Avlund, Kirsten, Svend Kreiner, and Kirsten Schultz-Larsen. "Construct validation and the Rasch model." Scandinavian Journal of Social Medicine 21, no. 4 (1993): 233–44. http://dx.doi.org/10.1177/140349489302100403.

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30

Graßhoff, Ulrike, Heinz Holling, and Rainer Schwabe. "Optimal Designs for the Rasch Model." Psychometrika 77, no. 4 (2012): 710–23. http://dx.doi.org/10.1007/s11336-012-9276-2.

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31

Triana, Apri. "Analisis Model Rasch pada Tes Diagnostik Kesulitan Belajar Matematika Siswa SMA." Jurnal Tarbiyah dan Ilmu Keguruan Borneo 5, no. 1 (2024): 119–32. http://dx.doi.org/10.21093/jtikborneo.v5i3.7135.

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Penelitian ini bertujuan untuk mengetahui karakteristik tes diagnostik kesulitan belajar Matematika menggunakan analisis model Rasch. Data yang dianalisis dengan model Rasch adalah sebanyak 323 respon jawaban siswa kelas XII IPA pada bidang studi Matematika. Hasil penelitian menunjukkan bahwa setiap butir tes diagnostik cocok dengan analisis model Rasch. Dari 323 siswa yang mengikuti tes, hanya sebanyak 298 respon jawaban siswa yang cocok dan bisa dianalisis dengan model Rasch. Analisis dengan model Rasch memiliki karakteristik satu parameter, yaitu tingkat kesulitan butir. Tingkat kesulitan b

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Baghaei, Purya, and Philipp Doebler. "Introduction to the Rasch Poisson Counts Model: An R Tutorial." Psychological Reports 122, no. 5 (2018): 1967–94. http://dx.doi.org/10.1177/0033294118797577.

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The Rasch Poisson Counts Model is the oldest Rasch model developed by the Danish mathematician Georg Rasch in 1952. Nevertheless, the model has had limited applications in psychoeducational assessment. With the rise of neurocognitive and psychomotor testing, there is more room for new applications of the model where other item response theory models cannot be applied. In this paper, we give a general introduction to the Rasch Poisson Counts Model and then using data of an attention test walk the reader through how to use the “lme4” package in R to estimate the model and interpret the outputs.

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Komboz, Basil, Carolin Strobl, and Achim Zeileis. "Tree-Based Global Model Tests for Polytomous Rasch Models." Educational and Psychological Measurement 78, no. 1 (2016): 128–66. http://dx.doi.org/10.1177/0013164416664394.

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Psychometric measurement models are only valid if measurement invariance holds between test takers of different groups. Global model tests, such as the well-established likelihood ratio (LR) test, are sensitive to violations of measurement invariance, such as differential item functioning and differential step functioning. However, these traditional approaches are only applicable when comparing previously specified reference and focal groups, such as males and females. Here, we propose a new framework for global model tests for polytomous Rasch models based on a model-based recursive partition

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Preinerstorfer, David, and Anton K. Formann. "Parameter recovery and model selection in mixed Rasch models." British Journal of Mathematical and Statistical Psychology 65, no. 2 (2011): 251–62. http://dx.doi.org/10.1111/j.2044-8317.2011.02020.x.

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Herwin, Herwin, Andi Tenriawaru, and Abdoulaye Fane. "Math elementary school exam analysis based on the Rasch model." Jurnal Prima Edukasia 7, no. 2 (2019): 106–13. http://dx.doi.org/10.21831/jpe.v7i2.24450.

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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, answe

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Khair, Muhammad Dhiyaul, and Sukaesi Marianti. "Individual ability on high-stakes test: Choosing cumulative score or rasch for scoring model." Jurnal Penelitian dan Evaluasi Pendidikan 28, no. 1 (2024): 79–93. https://doi.org/10.21831/pep.v28i1.71661.

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In a test, a method is required to estimate an individual's ability based on their responses. Typically, this is done by summing the correct responses or calculating a cumulative score. An alternative method is the Rasch model. This study aims to determine whether an individual's position, based on cumulative score estimates, remains unchanged or changes when compared with ability estimates using Rasch on dichotomous responses. The study uses open-source data from the 2018 Program for International Student Assessment (PISA) by the Organization for Economic Co-operation and Development (OECD) a

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Wright, BD, JM Linacre, RM Smith, AW Heinemann, and CV Granger. "FIM measurement properties and Rasch model details." Journal of Rehabilitation Medicine 29, no. 4 (1997): 267–72. http://dx.doi.org/10.2340/165019771997267272.

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To summarize, we take issue with the criticisms of Dickson & Köhler for two main reasons: 1. Rasch analysis provides a model from which to approach the analysis of the FIM, an ordinal scale, as an interval scale. The existence of examples of items or individuals which do not fit the model does not disprove the overall efficacy of the model; and 2. the principal components analysis of FIM motor items as presented by Dickson & Köhler tends to undermine rather than support their argument. Their own analyses produce a single major factor explaining between 58.5 and 67.1% of the variance, d

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Agust, Satria. "How Does Rasch Model Reveal Dishonesty between Coastal Students and Easy Grammar Test?" Jurnal Iqra' : Kajian Ilmu Pendidikan 4, no. 2 (2019): 214–30. http://dx.doi.org/10.25217/ji.v4i2.531.

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Academic dishonesty can occur with the supports of the technology devices and it also can be prevented with the help of the technology with its applications like Rasch Model. It can give detail information of the analyzed data and can trace the academic dishonesty like cheating. The aims of this research are to (1) analyze the grammar test items whether they are difficult items or easy ones using Rasch Model, (2) know the percentage of those who are assumed to do cheating based upon their origins and sex, and (3) expose their patterns in working on the grammar test in the form of multiple choi

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Paek, Insu, and Mark Wilson. "Formulating the Rasch Differential Item Functioning Model Under the Marginal Maximum Likelihood Estimation Context and Its Comparison With Mantel–Haenszel Procedure in Short Test and Small Sample Conditions." Educational and Psychological Measurement 71, no. 6 (2011): 1023–46. http://dx.doi.org/10.1177/0013164411400734.

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This study elaborates the Rasch differential item functioning (DIF) model formulation under the marginal maximum likelihood estimation context. Also, the Rasch DIF model performance was examined and compared with the Mantel–Haenszel (MH) procedure in small sample and short test length conditions through simulations. The theoretically known relationship of the DIF estimators between the Rasch DIF model and the MH procedure was confirmed. In general, the MH method showed a conservative tendency for DIF detection rates compared with the Rasch DIF model approach. When there is DIF, the z test (whe

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Jaya, Petrus Redy Partus, Beata Palmin, and Theresia Alviani Sum. "Pengujian Instrumen Akreditasi PAUD dengan Model Rasch." Jurnal Obsesi : Jurnal Pendidikan Anak Usia Dini 8, no. 4 (2024): 687–98. http://dx.doi.org/10.31004/obsesi.v8i4.5953.

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Kualitas Pendidikan Anak Usia Dini (PAUD) sangat dipengaruhi oleh instrumen akreditasi yang valid dan reliabel, yang dapat memberikan penilaian objektif terhadap stimulasi kognitif yang diberikan oleh guru. Penelitian ini bertujuan untuk mengevaluasi dan mengkritisi validitas serta reliabilitas instrumen visitasi akreditasi PAUD menggunakan Model Rasch 1 Parameter Logistic (1PL). Penelitian ini menggunakan pendekatan kuantitatif dengan melibatkan 124 lembaga PAUD dan 47 asesor pada tahun 2023. Data dikumpulkan melalui penilaian performa guru dalam menstimulasi aspek kognitif anak usia dini. An

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Zafrullah, Sa'adatul Ulwiyah, and Nofriyandi. "RASCH MODEL ANALYSIS ON MATHEMATICS TEST INSTRUMENTS: BIBLIOSHINY (1983-2023)." Mathematics Research and Education Journal 7, no. 2 (2023): 1–13. http://dx.doi.org/10.25299/mrej.2023.vol7(2).14550.

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The Rasch Model is a very useful tool in testing the quality of a measurement instrument, including mathematics tests. The Rasch model is part of item response theory which can classify item and person calculations in one distribution map. This research analyzes research trends regarding Rasch models in mathematics instruments, using bibliometric analysis to understand the current state of research in this field. From the analysis obtained, it can be said that publications regarding Rasch models in mathematical instruments have increased rapidly from 1983 to 2023, with a total of 173 articles.

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Lee, Seungbak, Hyo-Jun Yun, Minsoo Jeon, and Minsoo Kang. "Validating Athletes’ Subjective Performance Scale: A Rasch Model Analysis." IJASS(International Journal of Applied Sports Sciences) 35, no. 2 (2023): 238–50. http://dx.doi.org/10.24985/ijass.2023.35.2.238.

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This study aimed to validate the athletes’ subjective performance scale (ASPS) and examine its optimal categorization measuring Korean university athletes using the Rasch model. A six-item ASPS with ten response categories was administered to 201 Korean university athletes participating in team sport events. The Rash measurement program, Winsteps (version 4.6.2.1), was used to perform Rasch analysis. The results showed that the model was a good fit for the data. The Wright-Andrich map indicated ceiling and floor effects, as ASPS items were unable to measure individuals with logits beyond 3 or

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Carvalho, Lucas de Francisco, Ricardo Primi, and Gregory J. Meyer. "Application of the Rasch model in measuring personality disorders." Trends in Psychiatry and Psychotherapy 34, no. 2 (2012): 101–9. http://dx.doi.org/10.1590/s2237-60892012000200009.

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OBJECTIVE: To describe item and person parameters obtained with the Rasch model, one of the item response theory models, in the assessment of personality disorders based on Millon's theory. METHOD: A total of 350 people participated in the study. Age ranged from 18 to 67 years (mean ± standard deviation = 27.02±10.13), and 71.7% of the participants (n = 251) were female. Of the 350 individuals, 21.1% (n = 74) answered affirmatively about being under psychiatric treatment and taking psychiatric medications. The Personality Disorders Dimensional Inventory (PDDI), an instrument designed to assess

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44

De Leeuw, Jan, and Norman Verhelst. "Maximum Likelihood Estimation in Generalized Rasch Models." Journal of Educational Statistics 11, no. 3 (1986): 183–96. http://dx.doi.org/10.3102/10769986011003183.

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We review various models and techniques that have been proposed for item analysis according to the ideas of Rasch. A general model is proposed that unifies them, and maximum likelihood procedures are discussed for this general model. We show that unconditional maximum likelihood estimation in the functional Rasch model, as proposed by Wright and Haberman, is an important special case. Conditional maximum likelihood estimation, as proposed by Rasch and Andersen, is another important special case. Both procedures are related to marginal maximum likelihood estimation in the structural Rasch model

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Priyani, Tanti, and Bowo Sugiharto. "Analysis of biology midterm exam items using a comparison of the classical theory test and the Rasch model." JPBI (Jurnal Pendidikan Biologi Indonesia) 10, no. 3 (2024): 939–58. http://dx.doi.org/10.22219/jpbi.v10i3.34345.

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In biology learning, test instruments are essential for assessing students' understanding of complex concepts. A test instrument is a crucial factor in learning evaluation; however, its implementation remains minimal. This descriptive quantitative study aims to analyze the quality of test items using the classical approach in terms of validity, reliability, difficulty index, discrimination power, distractor effectiveness, and the Rasch model analysis. The data consists of 30 multiple-choice questions from a biology midterm exam administered to 40 students. Classical test data analysis uses Mic

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Permatasari, Nila. "Analisis kualitas instrumen penilaian materi keanekaragaman hayati melalui tes klasik dan Rasch model." Bio-Pedagogi 14, no. 1 (2025): 10. https://doi.org/10.20961/bio-pedagogi.v14i1.88470.

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EN<br />Learning evaluation functions as an indicator. Assessment is an activity that involves the interpretation of measurement data in accordance with certain criteria or rules. An effective assessment instrument must meet the requirements including validity, reliability, level of difficulty, discriminatory power, and distractor effectiveness. This study aims to compare the results of the analysis of assessment instruments between classical test theory and the Rasch model on the assessment of Biodiversity material. The study was conducted in class VII at one of the junior high schools

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Mursidi, Andi, and Soeharto Soeharto. "AN INTRODUCTION: EVALUATION OF QUALITY ASSURANCE FOR HIGHER EDUCATIONAL INSTITUTIONS USING RASCH MODEL." JETL (Journal Of Education, Teaching and Learning) 1, no. 1 (2017): 1. http://dx.doi.org/10.26737/jetl.v1i1.25.

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This is a descriptive qualitatif research about quality assurance evaluation. the research aims to introduce analyzing using Rasch model to evaluate higher education institution based on quality assurance standars that have been developed to evaluate each member including instructor and staff in higher education institution. The instrument have been developed to conduct the experiment to provide raw data sample to doing practical analyzing using Rasch model in this research. The first part of this research will explain definition of the quality assurance and Rasch model analysis. The second pa

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Strobl, Carolin, Julia Kopf, and Achim Zeileis. "Rasch Trees: A New Method for Detecting Differential Item Functioning in the Rasch Model." Psychometrika 80, no. 2 (2013): 289–316. http://dx.doi.org/10.1007/s11336-013-9388-3.

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Iseppi, Luca, Marcella Rizzo, Enrico Gori, Federico Nassivera, Ivana Bassi, and Alessandro Scuderi. "Rasch Model for Assessing Propensity to Entomophagy." Sustainability 13, no. 8 (2021): 4346. http://dx.doi.org/10.3390/su13084346.

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The Food and Agriculture Organization of the United Nations supports the production of edible insects as a promising and sustainable source of nutrients to meet the increasing demand for animal-derived products by the growing world population. Even if insects are part of the diet of more than two billion people worldwide, the practice of eating insects (entomophagy) raises challenging questions for Western countries where this is not a habit. The research applied the Rasch models and showed that, in the case of hunger or need, 70.8% of the sample declared that they would be willing to eat inse

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Anandita, Rina, and Lukman Cahyadi. "Aplikasi Model Rasch dalam Mengukur Komitmen Dosen." Jurnal Manajemen dan Supervisi Pendidikan 4, no. 3 (2020): 220–31. http://dx.doi.org/10.17977/um025v4i32020p220.

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