The paper provides a survey of 18 years’ progress that my colleagues, students (both former and current) and I made in a prominent research area in Psychometrics—Computerized Adaptive Testing (CAT). We start with a historical review of the establishment of a large sample foundation for CAT. It is worth noting that the asymptotic results were derived under the framework of Martingale Theory, a very theoretical perspective of Probability Theory, which may seem unrelated to educational and psychological testing. In addition, we address a number of issues that emerged from large scale implementation and show that how theoretical works can be helpful to solve the problems. Finally, we propose that CAT technology can be very useful to support individualized instruction on a mass scale. We show that even paper and pencil based tests can be made adaptive to support classroom teaching.
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I wish to thank Ying Cheng, Edison Choe, Rui Guo, Hyeon-Ah Kang, Justin Kern, Ya-Hui Su, Poh Hua Tay, Chun Wang, Shiyu Wang, Wen Zeng, Changjin Zheng, and Yi Zheng for their suggestions and comments which lead to numerous improvements.
This article is based on the Presidential Address Hua-Hua Chang gave on June 25, 2013 at the 78th Annual Meeting of the Psychometric Society held in Arnhem, the Netherlands.
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Chang, H. Psychometrics Behind Computerized Adaptive Testing. Psychometrika 80, 1–20 (2015). https://doi.org/10.1007/s11336-014-9401-5
- computerized adaptive testing
- multidimensional CAT
- sequential design
- martingale theory
- a-stratified item selection
- response time
- constraint management