Estimating Probabilities of Passing for Examinees With Incomplete Data in Mastery Tests

Administrative problems such as computer malfunction and power outage occasionally lead to missing item scores and hence to incomplete data on mastery tests such as the AP and U.S. Medical Licensing examinations. Investigators are often interested in estimating the probabilities of passing of the examinees with incomplete data on mastery tests. However, there is a lack of research on this estimation problem. The goal of this article is to suggest two new approaches—one each based on classical test theory and item response theory—for estimating the probabilities of passing of the examinees with incomplete data on mastery tests. The two approaches are demonstrated to have high accuracy and negligible misclassification rates.

The Implementation of Duolingo Mobile Application in English Vocabulary Learning

The purposes of this research are as follows: to obtain data and to analyze the effects of the implementation of Duolingo mobile application in English vocabulary. The research was held at SDN 02 Ciputat. All data variables were taken through tests. For vocabulary mastery tests, the data was taken in the questionnaires form. The method used was to conduct a system quality test (Software Quality Assurance) of software quality based on the factors and the criteria established. The data shows that the application gets a score with a pretty good predicate (73,8%), so learning media using the Duolingo mobile application can be applied especially for students in understanding English.<p class="Author"> </p>