Dergiler / Participatory Educational Research / 2021 / Cilt: 8 - Sayı: 4

Examining the Differential Rater Functioning in the Process of Assessing Writing Skills of Middle School 7th Grade Students

Sayfa
239–252
Yayın Tarihi
2021-12-01
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

In the present study, it was observed that the raters showing DRF was also the most lenient raters, while these raters did not show DRF in terms of the gender of the student.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:When students present writing tasks that require higher order thinking skills to work, one of the most important problems is scoring these writing tasks objectively.
📊
Temel Bulgular & Veri:The fact that raters give scores below or above their performance based on several environmental factors affects the consistency of the measurements.
💡
Sonuç & Katkı:In the present study, it was observed that the raters showing DRF was also the most lenient raters, while these raters did not show DRF in terms of the gender of the student.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Writing assessment · differential rater functioning · many facet rasch measurement

Abstract

When students present writing tasks that require higher order thinking skills to work, one of the most important problems is scoring these writing tasks objectively. The fact that raters give scores below or above their performance based on several environmental factors affects the consistency of the measurements. Inconsistencies in scoring negatively affect the validity and reliability of student performance and cause the scores obtained to be questioned. In regard to the validity and reliability of these measurements, it is significant to identify the rater behavior and correct the sources of error. This study aims to analyze the differential rater functioning (DRF), which is one of the problematic rater behaviors, in evaluating compositions written by middle school 7th-grade students within the scope of the Turkish course. 86 students attending a public school were participated the study. Students' compositions were rated using an analytical rubric by 8 teachers from different institutions. In this correlational research, the many facet Rasch model was used, and five variables including students, raters’ and, students’ gender, students’ qualification, and evaluation criteria were examined. it was examined whether the raters show DRF on an individual and group basis based on the dual interaction analysis, including the gender of the student x rater and the student's competence x rater. The findings have revealed that DRF at the group level does not interfere with the measurements, while the individual level DRF is involved in the measurements. It was determined that the level of DRF mixing in the measurements of successful students was the lowest. Especially rigid and lenient raters were found to show DRF. In the present study, it was observed that the raters showing DRF was also the most lenient raters, while these raters did not show DRF in terms of the gender of the student.

🔖

Bu Makaleye Atıf Yap

ASLANOĞLU, A. E., ŞATA, M. (2021). Examining the Differential Rater Functioning in the Process of Assessing Writing Skills of Middle School 7th Grade Students. Participatory Educational Research, Cilt: 8 - Sayı: 4, 239–252. https://ajindex.com/articles/239019

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (6)

  1. Aslanoğlu, A. E. ve Kutlu, Ö. (2003). Öğretimde sunu becerilerinin değerlendirilmesinde dereceli puanlama anahtarı (rubric) kullanılmasına ilişkin bir araştırma [Research on rubric in evaluating the presentation skills in education]. Ankara Üniversitesi Eğitim Bilimleri Fakültesi Dergisi [Ankara University Faculty of Educational Sciences Journal], 36(1-2), 25-36.
  2. Bond, T. G., & Fox, C. M. (2015). Applying the rasch model: Fundamental measurement in the human sciences (3rd ed.). New York: Routledge. Collins, J. L. (2000). Review of key concepts in strategic reading and writing instruction. J. L. Collins (Ed.), in Cheektowaga-sloan handbook of practical reading and writing strategies (pp. 5-10). Retrieved from http://gse.buffalo.edu/org/writingstrategies/PDFFiles/CHEEKTOWAGA-SLOAN.PDF
  3. Du, Y.,Wright, B. D., & Brown, W. L. (1996, April). Differential facet functioning detection in direct writing assessment. Paper presented at the Annual Meeting of the American Educational Research Association, New York. Eckes, T. (2005). Examining rater effects in test of writing and speaking performance assessments: A many-facet rasch analysis. Language Assessment Quarterly, 2(3), 197-221. https://doi.org/10.1207/s15434311laq0203_2
  4. Eckes, T. (2008). Rater types in writing performance assessments: A classification approach to rater variability. Language Testing, 25(2), 155-185. https://doi.org/10.1177/0265532207086780
  5. Eckes, T. (2019). Many-Facet Rasch measurement: Implications for rater-mediated language assesment. In Quantitative Data Analysis for Language Assessment (1st ed.) (pp.153-175). UK: Routledge. Englert, C. S., & Mariage, T. (2003). The sociocultural model in special education interventions: Apprenticing students in higher-order thinking. In L. H. Swanson, K. Harris, & S. Graham (Eds.), Handbook of Learning Disabilities (pp. 450-467). New York: Guilford. Erhardt, R. P., & Meade, V. (2005). Improving handwriting without teaching handwriting: The consultative clinical reasoning process. Australian Occupational Therapy Journal, 52(3), 199-210. https://doi.org/10.1111/j.1440-1630.2005.00505.x
  6. Engelhard, G. Jr. (1994). Examining rater errors in the assessment of written composition with a many-faceted Rasch model. Journal of Educational Measurement, 31(2), 93- 112. Engelhard, G., &Myford, C. M. (2003). Monitoring faculty consultant performance in the advanced placement English Literature and composition program with a many‐faceted Rasch model. ETS Research Rep