irtDemo R Package: Pedagogical Interactive Web Applications for Estimation, Scoring, and Multi Dimensionality in Item Response Theory
Öz
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.
Anahtar Kelimeler
item response theory multidimensional item response theory maximum likelihood estimation expected a posteriori ability estimation maximum a posteriori ability estimation
Destekleyen Kurum
University of Missouri
Kaynakça
- 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
Öz
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.
Anahtar Kelimeler
madde tepki kuramı çok boyutlu madde tepki kuramı maksimum olabilirlik kestirimi beklenen sonsal yetenek kestirimi maksimum sonsal yetenek kestirimi
Kaynakça
- 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.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Eğitim Üzerine Çalışmalar |
| Bölüm | Teknik Not |
| Yazarlar | |
| Yayımlanma Tarihi | 10 Şubat 2022 |
| Yayımlandığı Sayı | Yıl 2022 Cilt: 6 Sayı: 1 |
Kaynak Göster
Eğitim Fakültesi Dergisi - Anadolu Üniversitesi Eğitim Fakültesi
Tel: +90 222 335 05 79 Faks: +90 222 335 05 73 E-posta: aujef@anadolu.edu.tr
İnternet Adresi: dergipark.org.tr/tr/pub/aujef
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