This paper presents a technique to generate distractors for cloze questions in the context of a Computer-Assisted Language Learning tutoring system. The document will focus on an evaluation process used to measure the quality of the distractors that were automatically generated. The main goal of the present study is to be able to include this feature in the tutoring system.

OBJECTIVE To explore the way the doctor-patient communication process may be improved by adopting the patients' conversational style in the development of written materials for surgical patients. METHODS Written information prepared by doctors, specialists in abdominal surgery, was tested for comprehension on patients undergoing cholecystectomy, using the standard Cloze test procedure. At the...

*Correspondence: Fabrizio Consorti , Department of Surgical Sciences, Sapienza University of Rome, Viale del Policlinico, Rome 00161, Italy e-mail: [email protected] Distance learning is used in medical education, even if some recent meta-analyses indicated that it is no more effective than traditional methods. To exploit the technological capabilities, adaptive distance learning sy...

Commonsense question answering (CQA) aims to test if models can answer questions regarding commonsense knowledge that everyone knows. Prior works incorporate external bases have shown promising results, but are expensive construct and often limited a fixed set of relations. In this paper, we instead focus on better utilizing the implicit stored in pre-trained language models. While researchers ...

Prediction or expectancy is thought to play an important role in both music and language processing. However, prediction is currently studied independently in the two domains, limiting research on relations between predictive mechanisms in music and language. One limitation is a difference in how expectancy is quantified. In language, expectancy is typically measured using the cloze probability...

Language proficiency tests are a useful tool for evaluating learner progress, if the test difficulty fits the level of the learner. In this work, we describe a generalized framework for test difficulty prediction that is applicable to several languages and test types. In addition, we develop two ranking strategies for candidate evaluation inspired by automatic solving methods based on language ...

An incremental dependency parser’s probability model is entered as a predictor in a linear mixed-effects model of German readers’ eye-fixation durations. This dependencybased predictor improves a baseline that takes into account word length, n-gram probability, and Cloze predictability that are typically applied in models of human reading. This improvement obtains even when the dependency parse...