Literature DB >> 34176998

On Interim Cognitive Diagnostic Computerized Adaptive Testing in Learning Context.

Chun Wang1.   

Abstract

Interim assessment occurs throughout instruction to provide feedback about what students know and have achieved. Different from the current available cognitive diagnostic computerized adaptive testing (CD-CAT) design that focuses on assessment at a single time point, the authors discuss several designs of interim CD-CAT that are suitable in the learning context. The interim CD-CAT differs from the current available CD-CAT designs primarily because students' mastery profile (i.e., skills mastery) changes due to learning, and new attributes are added periodically. Moreover, hierarchies exist among attributes taught sequentially and such information could be used during item selection. Two specific designs are considered: The first one is when new attributes are taught in Stage II, but the student mastery status of the previously taught attributes stays the same. The second design is when both new attributes are taught, and previously taught attributes can be further learned or forgotten in Stage II. For both designs, the authors propose an individual prior, which considers a person's learning history and population learning model, to start an interim CD-CAT. Simulation results show that the Stage II CD-CAT using individual prior outperforms the methods using population priors. The GDINA (generalized deterministic inputs, noisy, "and" gate) diagnostic index (GDI) is extended to accommodate item hierarchies, and analytic results are provided to further illustrate the types of items that are most popular during item selection. As the first study that focuses on the application of CD-CAT in a learning context, the methods and results present herein showed the great promise of using CD-CAT to monitor learning.
© The Author(s) 2021.

Entities:  

Keywords:  cognitive diagnostic computerized adaptive testing; item selection; learning

Year:  2021        PMID: 34176998      PMCID: PMC8202977          DOI: 10.1177/0146621621990755

Source DB:  PubMed          Journal:  Appl Psychol Meas        ISSN: 0146-6216


  8 in total

1.  Technology and testing.

Authors:  Edys S Quellmalz; James W Pellegrino
Journal:  Science       Date:  2009-01-02       Impact factor: 47.728

2.  New Item Selection Methods for Cognitive Diagnosis Computerized Adaptive Testing.

Authors:  Mehmet Kaplan; Jimmy de la Torre; Juan Ramón Barrada
Journal:  Appl Psychol Meas       Date:  2014-11-13

3.  A Hidden Markov Model for Learning Trajectories in Cognitive Diagnosis With Application to Spatial Rotation Skills.

Authors:  Yinghan Chen; Steven Andrew Culpepper; Shiyu Wang; Jeffrey Douglas
Journal:  Appl Psychol Meas       Date:  2017-09-05

4.  A Latent Transition Analysis Model for Assessing Change in Cognitive Skills.

Authors:  Feiming Li; Allan Cohen; Brian Bottge; Jonathan Templin
Journal:  Educ Psychol Meas       Date:  2015-06-15       Impact factor: 2.821

5.  Assessing Growth in a Diagnostic Classification Model Framework.

Authors:  Matthew J Madison; Laine P Bradshaw
Journal:  Psychometrika       Date:  2018-09-27       Impact factor: 2.500

6.  Hierarchical diagnostic classification models: a family of models for estimating and testing attribute hierarchies.

Authors:  Jonathan Templin; Laine Bradshaw
Journal:  Psychometrika       Date:  2014-01-30       Impact factor: 2.500

7.  On initial item selection in cognitive diagnostic computerized adaptive testing.

Authors:  Gongjun Xu; Chun Wang; Zhuoran Shang
Journal:  Br J Math Stat Psychol       Date:  2016-11       Impact factor: 3.380

8.  Nonparametric CAT for CD in Educational Settings With Small Samples.

Authors:  Yuan-Pei Chang; Chia-Yi Chiu; Rung-Ching Tsai
Journal:  Appl Psychol Meas       Date:  2018-12-10
  8 in total

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