Comparison of GDINA, DINA, DINO Model Fit in Cognitive Diagnosis at Item and Test Level Based on Real Data

Yıl 2022, Cilt: 42 Sayı: 2, 1083 - 1108, 29.08.2022

Seyhan Sarıtaş Akyol Mehtap Çakan

https://doi.org/10.17152/gefad.1005950

Öz

Cognitive diagnostic models enable the creation of individuals' attribute profiles through
particular categorical latent variables. In order to collect evidence of whether the inferences
drawn from these models are valid or not, it is of great importance to reveal the model-data fit
and to identify the models that fit. This study aims to determine whether reduced DINA and DINO
models can be used instead of the saturated GDINA model determined within cognitive diagnostic
modelling framework by using Wald statistics for each item level and to specify the model that
best fits the data by comparing it at the item and test level. The data set of the study was obtained
from 478 students and the answer pattern of the Symbolic Number Comparison test comprising
36 items. Analyses were performed in R 3.5.3 program and the GDINA package in the R program
was used. In the first stage, the saturated GDINA model was taken as the basis, and the absolute
and relative fit indices were evaluated together and it was seen that the saturated model gave the
best fit. Afterward, using Wald statistics, instead of the saturated GDINA model, the availability
of reduced DINA and DINO models for each item-level with no significant loss in model-data fit
was examined.

Anahtar Kelimeler

Wald test, Model comparison, Model fit, CDM

Bilişsel Tanı Çerçevesinde GDINA, DINA, DINO Model Uyumlarının Madde ve Test Düzeyinde Gerçek Veriye Dayalı Olarak Karşılaştırılması

Öz

Bilişsel tanı modelleri belirli kategorik gizil özellikler aracılığıyla bireylerin nitelik profillerinin oluşturulmasına imkân vermektedir. Bu modellerden elde edilen çıkarımların geçerli olup olmadığına yönelik kanıt toplamak için model veri uyumunun ortaya konması ve uygun modellerin belirlenmesi büyük önem taşımaktadır. Bu çalışmada, bilişsel tanı yaklaşımı kapsamında belirlenen doymuş GDINA modeli yerine indirgenmiş (reduced) DINA ve DINO modellerinin çalışma verisi için kullanılıp kullanılamayacağı her madde düzeyi için Wald istatistiğinin kullanılarak belirlenmesi ve veriye en iyi uyum sağlayan modelin madde ve test düzeyinde karşılaştırılarak belirlenmesi amaçlanmıştır. Veri seti olarak 478 öğrenciden elde edilen, 36 maddeden oluşan Sayı Karşılaştırma testine ait cevap örüntüsü kullanılmıştır. Analizler R 3.5.3 programında yürütülmüş R programındaki GDINA paketinden yararlanılmıştır. Çalışmada ilk olarak, temele doymuş GDINA modeli alınarak mutlak ve göreli uyum indeksleri birlikte değerlendirilmiş ve doymuş modelin en iyi uyumu verdiği görülmüştür. Devamında Wald istatistiği kullanılarak doymuş GDINA modeli yerine her madde düzeyi için model veri uyumunda
manidar bir kayıp olmadan indirgenmiş DINA ve DINO modellerinin kullanılabilme durumu incelenmiştir.

Anahtar Kelimeler

Wald testi, Model karşılaştırma, Model uyumu, BTM

Kaynakça

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