Technical Brief
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irtDemo R Package: Pedagogical Interactive Web Applications for Estimation, Scoring, and Multi Dimensionality in Item Response Theory

Year 2022, Volume: 6 Issue: 1, 92 - 108, 10.02.2022
https://doi.org/10.34056/aujef.913781

Abstract

Comprehension of foundational but fairly complex statistical theories may require assistive interactive tools to understand underlying equations and theory. We provide a collection of interactive web applications to demonstrate or explore some of the fundamental yet complex item response theory concepts such as estimation, scoring and multidimensionality. Interactive web applications were developed via shiny R package. Users can access to these applications through irtDemo R package or links provided in this article. We hope that these applications give a head-start to emerging practitioners and researchers interested in advanced measurement topics.

Supporting Institution

University of Missouri

References

  • Birnbaum, A. (1968). Some latent trait models and their use in inferring an examinee's ability. In F. M. Lord and M. R.
  • Novick (Eds.), Statistical theories of mental test scores (pp. 397-472), Reading, MA: Addison-Wesley.
  • Bock, R. D., & Mislevy, R. J. (1982). Adaptive EAP estimation of ability in a microcomputer environment. Applied Psychological Measurement, 6(4), 431-444.
  • Bonifay, W. (2019). Multidimensional item response theory. SAGE Publications.
  • Braun, J. W., White, B. J., & Craig, G. (2014). R tricks for kids. Teaching Statistics, 36, 7–12.
  • Bulus, M., & Bonifay, W. (2018). irtDemo: Item response theory demo collection. R package version 0.1.4. Available at https://CRAN.R-project.org/package=irtDemo
  • Chang, W., Cheng, J., Allaire, J., Xie, Y., & McPherson, J. (2017). shiny: Web Application Framework for R. R package version 1.0.3. Available at https://CRAN.R-project.org/package=shiny
  • De Ayala, R. J. (2013). The theory and practice of item response theory. Guilford Publications. Garfield, J., and Ben-Zvi, D. (2007). How students learn statistics revisited: a current review of research on teaching and learning statistics. International Statistical Review, 75, 372–396.
  • R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org.
  • Reckase, M. D. (2009). Multidimensional Item Response Theory Models. In Multidimensional Item Response Theory (pp. 79-112). New York, NY: Springer.

irtDemo R Paketi: Madde Tepki Kuramında Tahmin, Puanlama ve Çok Boyutluluk için Pedagojik Amaçlı Etkileşimli Web Uygulamaları

Year 2022, Volume: 6 Issue: 1, 92 - 108, 10.02.2022
https://doi.org/10.34056/aujef.913781

Abstract

Temel düzeyde ancak oldukça karmaşık istatistiksel teorilerin anlaşılması, temellerinde yatan denklemleri ve teoriyi anlamak için yardımcı etkileşimli teknolojik araçlar gerektirebilir. Bu çalışmada, tahmin, puanlama ve çok boyutluluk gibi bazı temel ancak karmaşık madde tepki kuramı kavramlarını göstermek veya keşfetmek için interaktif web uygulamaları koleksiyonu sunulmuştur. İnteraktif web uygulamaları shiny R paketi kullanılarak oluşturulmuştur. Kullanıcılar bu uygulamalara hem irtDemo R paketinden hem de bu çalışmada verilen linkleri kullanarak erişebilirler. Bu uygulamaların, gelişmiş ölçme konularıyla ilgilenen uygulayıcılara ve araştırmacılara başlangıç için bir avantaj sağlayacağını düşünülmektedir.

References

  • Birnbaum, A. (1968). Some latent trait models and their use in inferring an examinee's ability. In F. M. Lord and M. R.
  • Novick (Eds.), Statistical theories of mental test scores (pp. 397-472), Reading, MA: Addison-Wesley.
  • Bock, R. D., & Mislevy, R. J. (1982). Adaptive EAP estimation of ability in a microcomputer environment. Applied Psychological Measurement, 6(4), 431-444.
  • Bonifay, W. (2019). Multidimensional item response theory. SAGE Publications.
  • Braun, J. W., White, B. J., & Craig, G. (2014). R tricks for kids. Teaching Statistics, 36, 7–12.
  • Bulus, M., & Bonifay, W. (2018). irtDemo: Item response theory demo collection. R package version 0.1.4. Available at https://CRAN.R-project.org/package=irtDemo
  • Chang, W., Cheng, J., Allaire, J., Xie, Y., & McPherson, J. (2017). shiny: Web Application Framework for R. R package version 1.0.3. Available at https://CRAN.R-project.org/package=shiny
  • De Ayala, R. J. (2013). The theory and practice of item response theory. Guilford Publications. Garfield, J., and Ben-Zvi, D. (2007). How students learn statistics revisited: a current review of research on teaching and learning statistics. International Statistical Review, 75, 372–396.
  • R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org.
  • Reckase, M. D. (2009). Multidimensional Item Response Theory Models. In Multidimensional Item Response Theory (pp. 79-112). New York, NY: Springer.
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Details

Primary Language English
Subjects Studies on Education
Journal Section Technical Note
Authors

Metin Bulus 0000-0003-4348-6322

Wes Bonifay This is me 0000-0003-3853-7607

Publication Date February 10, 2022
Published in Issue Year 2022 Volume: 6 Issue: 1

Cite

APA Bulus, M., & Bonifay, W. (2022). irtDemo R Package: Pedagogical Interactive Web Applications for Estimation, Scoring, and Multi Dimensionality in Item Response Theory. Anadolu University Journal of Education Faculty, 6(1), 92-108. https://doi.org/10.34056/aujef.913781

Anadolu University Journal of Education Faculty

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