%0 Journal Article %J Applied Psychological Measurement %D 2020 %T New Efficient and Practicable Adaptive Designs for Calibrating Items Online %A Yinhong He %A Ping Chen %A Yong Li %X When calibrating new items online, it is practicable to first compare all new items according to some criterion and then assign the most suitable one to the current examinee who reaches a seeding location. The modified D-optimal design proposed by van der Linden and Ren (denoted as D-VR design) works within this practicable framework with the aim of directly optimizing the estimation of item parameters. However, the optimal design point for a given new item should be obtained by comparing all examinees in a static examinee pool. Thus, D-VR design still has room for improvement in calibration efficiency from the view of traditional optimal design. To this end, this article incorporates the idea of traditional optimal design into D-VR design and proposes a new online calibration design criterion, namely, excellence degree (ED) criterion. Four different schemes are developed to measure the information provided by the current examinee when implementing this new criterion, and four new ED designs equipped with them are put forward accordingly. Simulation studies were conducted under a variety of conditions to compare the D-VR design and the four proposed ED designs in terms of calibration efficiency. Results showed that the four ED designs outperformed D-VR design in almost all simulation conditions. %B Applied Psychological Measurement %V 44 %P 3-16 %U https://doi.org/10.1177/0146621618824854 %R 10.1177/0146621618824854 %0 Conference Paper %B IACAT 2017 Conference %D 2017 %T New Challenges (With Solutions) and Innovative Applications of CAT %A Chun Wang %A David J. Weiss %A Xue Zhang %A Jian Tao %A Yinhong He %A Ping Chen %A Shiyu Wang %A Susu Zhang %A Haiyan Lin %A Xiaohong Gao %A Hua-Hua Chang %A Zhuoran Shang %K CAT %K challenges %K innovative applications %X

Over the past several decades, computerized adaptive testing (CAT) has profoundly changed the administration of large-scale aptitude tests, state-wide achievement tests, professional licensure exams, and health outcome measures. While many challenges of CAT have been successfully addressed due to the continual efforts of researchers in the field, there are still many remaining, longstanding challenges that have yet to be resolved. This symposium will begin with three presentations, each of which provides a sound solution to one of the unresolved challenges. They are (1) item calibration when responses are “missing not at random” from CAT administration; (2) online calibration of new items when person traits have non-ignorable measurement error; (3) establishing consistency and asymptotic normality of latent trait estimation when allowing item response revision in CAT. In addition, this symposium also features innovative applications of CAT. In particular, there is emerging interest in using cognitive diagnostic CAT to monitor and detect learning progress (4th presentation). Last but not least, the 5th presentation illustrates the power of multidimensional polytomous CAT that permits rapid identification of hospitalized patients’ rehabilitative care needs in health outcomes measurement. We believe this symposium covers a wide range of interesting and important topics in CAT.

Session Video

%B IACAT 2017 Conference %I Niigata Seiryo University %C Niigata, Japan %8 08/2017 %G eng %U https://drive.google.com/open?id=1Wvgxw7in_QCq_F7kzID6zCZuVXWcFDPa