One major problem of state-of-the-art Cross Language Question Answering systems is the translation of user questions. This paper proposes combining the potential of multiple translation machines in order to improve the final answering precision. In particular, it presents three different methods for this purpose. The first one focuses on selecting the most fluent translation from a given set; t...

We performed 4 experiments assessing the learning that occurs when taking a test. Our experiments used multiple-choice tests because the processes deployed during testing can be manipulated by varying the nature of the choice alternatives. Previous research revealed that a multiple-choice test that includes “none of the above” (NOTA) produces better performance on a subsequent test only when th...

The German question answering (QA) system IRSAW (formerly: InSicht) participated in QA@CLEF for the fifth time. IRSAW was introduced in 2007 by integrating the deep answer producer InSicht, several shallow answer producers, and a logical validator. InSicht builds on a deep QA approach: it transforms documents to semantic representations using a parser, draws inferences on semantic representatio...

We describe the development of a ten-question diagnostic designed to characterize the estimation skills of undergraduate students in science and engineering. In order to establish a baseline and look for possible gains in skill level we have developed a multiple-choice assessment designed to probe student ability and confidence in estimating physical quantities such as mass, size, and time. The...

Study Tips Hints to help you review more effectively. Answer Sheets Write the letter of the correct answer for the questions in the review tests. Although only one set of answer sheets are included, you can take these tests as often as you want. Review Session A 100-multiple-choice question Review Session to help you determine where you need more study emphasis. However, be aware that none of t...