چکیده

The social distancing in the age of COVID-19 pandemic by the governments has a significant impact on education industry. Almost all educational institutes migrated to employ online learning platforms as the main medium to educate their audiences. The problem with such migration becomes acute when we intend to perform the assessment. Converting the traditional paper-and-pencil testing to the online version may cause chaotic situations in a way that we may no longer be able to certify the learner s ability. Computer adaptive testing aims to handle the issues and facilitate more accurate estimations of examinee s ability. Most of the institutes both in private and public sectors around the world are using computer adaptive testing. A computer adaptive testing features various settings with different possible configurations. However there have been no systematic studies on the effects of these settings on test performance and robustness. Furthermore the exact impact of various parameters for computer adaptive testings are poorly understood. This work presents a large set of experiments conducted to investigate these issues using a simulator. Our experiments reveal effective settings and configurations of computer adaptive testing. The findings presented will be useful to institutions seeking to design and implement computer adaptive testing more systematically and also open up new areas of research for academics in the area of computer adaptive testings.

کليدواژه ها

Item response theory Computer adaptive testing Simulation

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محمد رضا صالح صدق پور , 1400 , Evaluation of Computer Adaptive Testing (CAT) in onlinelearning platforms A performance engineering approach to CAT using simulation , سیزدهمین همایش ملی آموزش