IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v74y2009i4p619-632.html
   My bibliography  Save this article

When Cognitive Diagnosis Meets Computerized Adaptive Testing: CD-CAT

Author

Listed:
  • Ying Cheng

Abstract

No abstract is available for this item.

Suggested Citation

  • Ying Cheng, 2009. "When Cognitive Diagnosis Meets Computerized Adaptive Testing: CD-CAT," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 619-632, December.
  • Handle: RePEc:spr:psycho:v:74:y:2009:i:4:p:619-632
    DOI: 10.1007/s11336-009-9123-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11336-009-9123-2
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11336-009-9123-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xueli Xu & Jeff Douglas, 2006. "Computerized adaptive testing under nonparametric IRT models," Psychometrika, Springer;The Psychometric Society, vol. 71(1), pages 121-137, March.
    2. Hua-Hua Chang & Jinming Zhang, 2002. "Hypergeometric family and item overlap rates in computerized adaptive testing," Psychometrika, Springer;The Psychometric Society, vol. 67(3), pages 387-398, September.
    3. Curtis Tatsuoka & Thomas Ferguson, 2003. "Sequential classification on partially ordered sets," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 143-157, February.
    4. Curtis Tatsuoka, 2002. "Data analytic methods for latent partially ordered classification models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 51(3), pages 337-350, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yan Li & Chao Huang & Jia Liu, 2023. "Diagnosing Primary Students’ Reading Progression: Is Cognitive Diagnostic Computerized Adaptive Testing the Way Forward?," Journal of Educational and Behavioral Statistics, , vol. 48(6), pages 842-865, December.
    2. Miguel A Sorrel & Juan R Barrada & Jimmy de la Torre & Francisco José Abad, 2020. "Adapting cognitive diagnosis computerized adaptive testing item selection rules to traditional item response theory," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-17, January.
    3. Ping Chen & Tao Xin & Chun Wang & Hua-Hua Chang, 2012. "Online Calibration Methods for the DINA Model with Independent Attributes in CD-CAT," Psychometrika, Springer;The Psychometric Society, vol. 77(2), pages 201-222, April.
    4. Hung-Yu Huang, 2018. "Effects of Item Calibration Errors on Computerized Adaptive Testing under Cognitive Diagnosis Models," Journal of Classification, Springer;The Classification Society, vol. 35(3), pages 437-465, October.
    5. Chia-Yi Chiu & Yuan-Pei Chang, 2021. "Advances in CD-CAT: The General Nonparametric Item Selection Method," Psychometrika, Springer;The Psychometric Society, vol. 86(4), pages 1039-1057, December.
    6. Jingchen Liu & Zhiliang Ying & Stephanie Zhang, 2015. "A Rate Function Approach to Computerized Adaptive Testing for Cognitive Diagnosis," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 468-490, June.
    7. Nathan D. Minchen & Jimmy de la Torre & Ying Liu, 2017. "A Cognitive Diagnosis Model for Continuous Response," Journal of Educational and Behavioral Statistics, , vol. 42(6), pages 651-677, December.
    8. Pasquale Anselmi & Egidio Robusto & Luca Stefanutti & Debora Chiusole, 2016. "An Upgrading Procedure for Adaptive Assessment of Knowledge," Psychometrika, Springer;The Psychometric Society, vol. 81(2), pages 461-482, June.
    9. Hua-Hua Chang, 2015. "Psychometrics Behind Computerized Adaptive Testing," Psychometrika, Springer;The Psychometric Society, vol. 80(1), pages 1-20, March.
    10. Qingrong Tan & Yan Cai & Fen Luo & Dongbo Tu, 2023. "Development of a High-Accuracy and Effective Online Calibration Method in CD-CAT Based on Gini Index," Journal of Educational and Behavioral Statistics, , vol. 48(1), pages 103-141, February.
    11. Hong-Yun Liu & Xiao-Feng You & Wen-Yi Wang & Shu-Liang Ding & Hua-Hua Chang, 2013. "The Development of Computerized Adaptive Testing with Cognitive Diagnosis for an English Achievement Test in China," Journal of Classification, Springer;The Classification Society, vol. 30(2), pages 152-172, July.
    12. Chun Wang & Hua-Hua Chang, 2011. "Item Selection in Multidimensional Computerized Adaptive Testing—Gaining Information from Different Angles," Psychometrika, Springer;The Psychometric Society, vol. 76(3), pages 363-384, July.
    13. Xuliang Gao & Daxun Wang & Yan Cai & Dongbo Tu, 2020. "Cognitive Diagnostic Computerized Adaptive Testing for Polytomously Scored Items," Journal of Classification, Springer;The Classification Society, vol. 37(3), pages 709-729, October.
    14. Magis, David & Barrada, Juan Ramon, 2017. "Computerized Adaptive Testing with R: Recent Updates of the Package catR," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(c01).
    15. Ragip Terzi & Sedat Sen, 2019. "A Nondiagnostic Assessment for Diagnostic Purposes: Q-Matrix Validation and Item-Based Model Fit Evaluation for the TIMSS 2011 Assessment," SAGE Open, , vol. 9(1), pages 21582440198, February.
    16. Wenyi Wang & Lihong Song & Teng Wang & Peng Gao & Jian Xiong, 2020. "A Note on the Relationship of the Shannon Entropy Procedure and the Jensen–Shannon Divergence in Cognitive Diagnostic Computerized Adaptive Testing," SAGE Open, , vol. 10(1), pages 21582440198, January.
    17. Crabbe, Marjolein & Akinc, Deniz & Vandebroek, Martina, 2014. "Fast algorithms to generate individualized designs for the mixed logit choice model," Transportation Research Part B: Methodological, Elsevier, vol. 60(C), pages 1-15.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yunxiao Chen & Xiaoou Li & Jingchen Liu & Zhiliang Ying, 2017. "Regularized Latent Class Analysis with Application in Cognitive Diagnosis," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 660-692, September.
    2. Hong-Yun Liu & Xiao-Feng You & Wen-Yi Wang & Shu-Liang Ding & Hua-Hua Chang, 2013. "The Development of Computerized Adaptive Testing with Cognitive Diagnosis for an English Achievement Test in China," Journal of Classification, Springer;The Classification Society, vol. 30(2), pages 152-172, July.
    3. Wenyi Wang & Lihong Song & Teng Wang & Peng Gao & Jian Xiong, 2020. "A Note on the Relationship of the Shannon Entropy Procedure and the Jensen–Shannon Divergence in Cognitive Diagnostic Computerized Adaptive Testing," SAGE Open, , vol. 10(1), pages 21582440198, January.
    4. S. Ferguson, T.Thomas & Tatsuoka, Curtis, 2004. "An optimal strategy for sequential classification on partially ordered sets," Statistics & Probability Letters, Elsevier, vol. 68(2), pages 161-168, June.
    5. Xuliang Gao & Daxun Wang & Yan Cai & Dongbo Tu, 2020. "Cognitive Diagnostic Computerized Adaptive Testing for Polytomously Scored Items," Journal of Classification, Springer;The Classification Society, vol. 37(3), pages 709-729, October.
    6. Jingchen Liu & Zhiliang Ying & Stephanie Zhang, 2015. "A Rate Function Approach to Computerized Adaptive Testing for Cognitive Diagnosis," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 468-490, June.
    7. Chen, Yunxiao & Li, Xiaoou & Liu, Jingchen & Ying, Zhiliang, 2017. "Regularized latent class analysis with application in cognitive diagnosis," LSE Research Online Documents on Economics 103182, London School of Economics and Political Science, LSE Library.
    8. Matthew S. Johnson & Sandip Sinharay, 2020. "The Reliability of the Posterior Probability of Skill Attainment in Diagnostic Classification Models," Journal of Educational and Behavioral Statistics, , vol. 45(1), pages 5-31, February.
    9. Hans-Friedrich Köhn & Chia-Yi Chiu, 2017. "A Procedure for Assessing the Completeness of the Q-Matrices of Cognitively Diagnostic Tests," Psychometrika, Springer;The Psychometric Society, vol. 82(1), pages 112-132, March.
    10. Kazuhiro Yamaguchi & Kensuke Okada, 2020. "Variational Bayes Inference for the DINA Model," Journal of Educational and Behavioral Statistics, , vol. 45(5), pages 569-597, October.
    11. Jimmy de la Torre, 2011. "The Generalized DINA Model Framework," Psychometrika, Springer;The Psychometric Society, vol. 76(2), pages 179-199, April.
    12. Chen, Yunxiao & Liu, Jingchen & Xu, Gongjun & Ying, Zhiliang, 2015. "Statistical analysis of Q-matrix based diagnostic classification models," LSE Research Online Documents on Economics 103183, London School of Economics and Political Science, LSE Library.
    13. Chun Wang & Hua-Hua Chang & Keith Boughton, 2011. "Kullback–Leibler Information and Its Applications in Multi-Dimensional Adaptive Testing," Psychometrika, Springer;The Psychometric Society, vol. 76(1), pages 13-39, January.
    14. Chia-Yi Chiu & Yuan-Pei Chang, 2021. "Advances in CD-CAT: The General Nonparametric Item Selection Method," Psychometrika, Springer;The Psychometric Society, vol. 86(4), pages 1039-1057, December.
    15. Chen-Wei Liu & Björn Andersson & Anders Skrondal, 2020. "A Constrained Metropolis–Hastings Robbins–Monro Algorithm for Q Matrix Estimation in DINA Models," Psychometrika, Springer;The Psychometric Society, vol. 85(2), pages 322-357, June.
    16. Yuqi Gu & Jingchen Liu & Gongjun Xu & Zhiliang Ying, 2018. "Hypothesis Testing of the Q-matrix," Psychometrika, Springer;The Psychometric Society, vol. 83(3), pages 515-537, September.
    17. Jared D. Huling & Menggang Yu, 2022. "Sufficient dimension reduction for populations with structured heterogeneity," Biometrics, The International Biometric Society, vol. 78(4), pages 1626-1638, December.
    18. Debora Chiusole & Luca Stefanutti & Pasquale Anselmi & Egidio Robusto, 2013. "Assessing Parameter Invariance in the BLIM: Bipartition Models," Psychometrika, Springer;The Psychometric Society, vol. 78(4), pages 710-724, October.
    19. Chia-Yi Chiu & Jeffrey Douglas & Xiaodong Li, 2009. "Cluster Analysis for Cognitive Diagnosis: Theory and Applications," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 633-665, December.
    20. Jürgen Heller & Luca Stefanutti & Pasquale Anselmi & Egidio Robusto, 2015. "On the Link between Cognitive Diagnostic Models and Knowledge Space Theory," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 995-1019, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:psycho:v:74:y:2009:i:4:p:619-632. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.