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.

*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 ...

The objectives of this study are to analyze about the different and similar multiple choice cloze test in reading comprehension, perception toward among students that influence comprehension. This used descriptive qualitative method. In collecting data, used, Observation, Interview, Questionnaire, Documentaton. data were taken by choice. was conducted there 21 informants which 7 boys 13 girls S...

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 ...