dc.contributor | 統計系 | en_US |
dc.creator (作者) | 張源俊 | zh_TW |
dc.creator (作者) | Chang, Yuan-chin I. ;Lu, Hung-Yi | en_US |
dc.date (日期) | 2009-07 | en_US |
dc.date.accessioned | 23-十二月-2014 15:18:51 (UTC+8) | - |
dc.date.available | 23-十二月-2014 15:18:51 (UTC+8) | - |
dc.date.issued (上傳時間) | 23-十二月-2014 15:18:51 (UTC+8) | - |
dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/72222 | - |
dc.description.abstract (摘要) | Item calibration is an essential issue in modern item response theory based psychological or educational testing. Due to the popularity of computerized adaptive testing, methods to efficiently calibrate new items have become more important than that in the time when paper and pencil test administration is the norm. There are many calibration processes being proposed and discussed from both theoretical and practical perspectives. Among them, the online calibration may be one of the most cost effective processes. In this paper, under a variable length computerized adaptive testing scenario, we integrate the methods of adaptive design, sequential estimation, and measurement error models to solve online item calibration problems. The proposed sequential estimate of item parameters is shown to be strongly consistent and asymptotically normally distributed with a prechosen accuracy. Numerical results show that the proposed method is very promising in terms of both estimation accuracy and efficiency. The results of using calibrated items to estimate the latent trait levels are also reported. | en_US |
dc.format.extent | 520675 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en_US | - |
dc.relation (關聯) | Psychometrika,75(1), 140-157 | en_US |
dc.title (題名) | Online Calibration Via Variable Length Computerized Adaptive Testing | en_US |
dc.type (資料類型) | article | en |