Model Data Fit Comparison between DINA and G-DINA in Cognitive Diagnostic Models

T. Oguz Basokcu; Tuncay Ogretmen; Hulya Kelecioglu

doi:doi:10.11648/j.edu.20130206.18

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Model Data Fit Comparison between DINA and G-DINA in Cognitive Diagnostic Models

T. Oguz Basokcu, Tuncay Ogretmen, Hulya Kelecioglu

Published in Education Journal (Volume 2, Issue 6)

Received: 3 December 2013 Published: 20 December 2013

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Abstract

In this study, item and model data fit indices, calculated by DINA and G-DINA Models using the same sample and Q matrix, are analyzed. Fit indices for these two models from Cognitive Diagnostic Models are analyzed using 2LL, AIC and BIC statistics. Item fit indices are analyzed using residual correlations and probabilities. Analysis results showed G-DINA model had better fit results than DINA model. DINA model could give rather better results to estimate student profile in tests where higher level and progressive behaviors are used together. On the other hand, G-DINA model weights required attributes for an item when estimating student profile. Therefore in items requiring more than one attributes, contributions of attributes to probability that a student answers the item correctly are not equal. This provides an important advantage to testers to evaluate multiple choice items in assessing complex and prerequisite forming patterns.

Published in	Education Journal (Volume 2, Issue 6)
DOI	10.11648/j.edu.20130206.18
Page(s)	256-262
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2013. Published by Science Publishing Group

Keywords

Cognitive Diagnostic Models, DINA Model, G-DINA Model, Model Fit Indices

References

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APA Style

T. Oguz Basokcu, Tuncay Ogretmen, Hulya Kelecioglu. (2013). Model Data Fit Comparison between DINA and G-DINA in Cognitive Diagnostic Models. Education Journal, 2(6), 256-262. https://doi.org/10.11648/j.edu.20130206.18

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ACS Style

T. Oguz Basokcu; Tuncay Ogretmen; Hulya Kelecioglu. Model Data Fit Comparison between DINA and G-DINA in Cognitive Diagnostic Models. Educ. J. 2013, 2(6), 256-262. doi: 10.11648/j.edu.20130206.18

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AMA Style

T. Oguz Basokcu, Tuncay Ogretmen, Hulya Kelecioglu. Model Data Fit Comparison between DINA and G-DINA in Cognitive Diagnostic Models. Educ J. 2013;2(6):256-262. doi: 10.11648/j.edu.20130206.18

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@article{10.11648/j.edu.20130206.18,
  author = {T. Oguz Basokcu and Tuncay Ogretmen and Hulya Kelecioglu},
  title = {Model Data Fit Comparison between DINA and G-DINA in Cognitive Diagnostic Models},
  journal = {Education Journal},
  volume = {2},
  number = {6},
  pages = {256-262},
  doi = {10.11648/j.edu.20130206.18},
  url = {https://doi.org/10.11648/j.edu.20130206.18},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.edu.20130206.18},
  abstract = {In this study, item and model data fit indices, calculated by DINA and G-DINA Models using the same sample and Q matrix, are analyzed. Fit indices for these two models from Cognitive Diagnostic Models are analyzed using 2LL, AIC and BIC statistics. Item fit indices are analyzed using residual correlations and probabilities.  Analysis results showed G-DINA model had better fit results than DINA model. DINA model could give rather better results to estimate student profile in tests where higher level and progressive behaviors are used together.  On the other hand, G-DINA model weights required attributes for an item when estimating student profile. Therefore in items requiring more than one attributes, contributions of attributes to probability that a student answers the item correctly are not equal. This provides an important advantage to testers to evaluate multiple choice items in assessing complex and prerequisite forming patterns.},
 year = {2013}
}

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TY  - JOUR
T1  - Model Data Fit Comparison between DINA and G-DINA in Cognitive Diagnostic Models
AU  - T. Oguz Basokcu
AU  - Tuncay Ogretmen
AU  - Hulya Kelecioglu
Y1  - 2013/12/20
PY  - 2013
N1  - https://doi.org/10.11648/j.edu.20130206.18
DO  - 10.11648/j.edu.20130206.18
T2  - Education Journal
JF  - Education Journal
JO  - Education Journal
SP  - 256
EP  - 262
PB  - Science Publishing Group
SN  - 2327-2619
UR  - https://doi.org/10.11648/j.edu.20130206.18
AB  - In this study, item and model data fit indices, calculated by DINA and G-DINA Models using the same sample and Q matrix, are analyzed. Fit indices for these two models from Cognitive Diagnostic Models are analyzed using 2LL, AIC and BIC statistics. Item fit indices are analyzed using residual correlations and probabilities.  Analysis results showed G-DINA model had better fit results than DINA model. DINA model could give rather better results to estimate student profile in tests where higher level and progressive behaviors are used together.  On the other hand, G-DINA model weights required attributes for an item when estimating student profile. Therefore in items requiring more than one attributes, contributions of attributes to probability that a student answers the item correctly are not equal. This provides an important advantage to testers to evaluate multiple choice items in assessing complex and prerequisite forming patterns.
VL  - 2
IS  - 6
ER  -

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Author Information

T. Oguz Basokcu

Department of Assessment and Evaluation in Education, Ege University, ?zmir, Turkey
Tuncay Ogretmen

Department of Assessment and Evaluation in Education, Ege University, ?zmir, Turkey
Hulya Kelecioglu

Department of Assessment and Evaluation in Education, Hacettepe University, Ankara, Turkey

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APA Style

T. Oguz Basokcu, Tuncay Ogretmen, Hulya Kelecioglu. (2013). Model Data Fit Comparison between DINA and G-DINA in Cognitive Diagnostic Models. Education Journal, 2(6), 256-262. https://doi.org/10.11648/j.edu.20130206.18

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ACS Style

T. Oguz Basokcu; Tuncay Ogretmen; Hulya Kelecioglu. Model Data Fit Comparison between DINA and G-DINA in Cognitive Diagnostic Models. Educ. J. 2013, 2(6), 256-262. doi: 10.11648/j.edu.20130206.18

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AMA Style

T. Oguz Basokcu, Tuncay Ogretmen, Hulya Kelecioglu. Model Data Fit Comparison between DINA and G-DINA in Cognitive Diagnostic Models. Educ J. 2013;2(6):256-262. doi: 10.11648/j.edu.20130206.18

Copy | Download

@article{10.11648/j.edu.20130206.18,
  author = {T. Oguz Basokcu and Tuncay Ogretmen and Hulya Kelecioglu},
  title = {Model Data Fit Comparison between DINA and G-DINA in Cognitive Diagnostic Models},
  journal = {Education Journal},
  volume = {2},
  number = {6},
  pages = {256-262},
  doi = {10.11648/j.edu.20130206.18},
  url = {https://doi.org/10.11648/j.edu.20130206.18},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.edu.20130206.18},
  abstract = {In this study, item and model data fit indices, calculated by DINA and G-DINA Models using the same sample and Q matrix, are analyzed. Fit indices for these two models from Cognitive Diagnostic Models are analyzed using 2LL, AIC and BIC statistics. Item fit indices are analyzed using residual correlations and probabilities.  Analysis results showed G-DINA model had better fit results than DINA model. DINA model could give rather better results to estimate student profile in tests where higher level and progressive behaviors are used together.  On the other hand, G-DINA model weights required attributes for an item when estimating student profile. Therefore in items requiring more than one attributes, contributions of attributes to probability that a student answers the item correctly are not equal. This provides an important advantage to testers to evaluate multiple choice items in assessing complex and prerequisite forming patterns.},
 year = {2013}
}

Copy | Download

TY  - JOUR
T1  - Model Data Fit Comparison between DINA and G-DINA in Cognitive Diagnostic Models
AU  - T. Oguz Basokcu
AU  - Tuncay Ogretmen
AU  - Hulya Kelecioglu
Y1  - 2013/12/20
PY  - 2013
N1  - https://doi.org/10.11648/j.edu.20130206.18
DO  - 10.11648/j.edu.20130206.18
T2  - Education Journal
JF  - Education Journal
JO  - Education Journal
SP  - 256
EP  - 262
PB  - Science Publishing Group
SN  - 2327-2619
UR  - https://doi.org/10.11648/j.edu.20130206.18
AB  - In this study, item and model data fit indices, calculated by DINA and G-DINA Models using the same sample and Q matrix, are analyzed. Fit indices for these two models from Cognitive Diagnostic Models are analyzed using 2LL, AIC and BIC statistics. Item fit indices are analyzed using residual correlations and probabilities.  Analysis results showed G-DINA model had better fit results than DINA model. DINA model could give rather better results to estimate student profile in tests where higher level and progressive behaviors are used together.  On the other hand, G-DINA model weights required attributes for an item when estimating student profile. Therefore in items requiring more than one attributes, contributions of attributes to probability that a student answers the item correctly are not equal. This provides an important advantage to testers to evaluate multiple choice items in assessing complex and prerequisite forming patterns.
VL  - 2
IS  - 6
ER  -

Copy | Download