Crowdsourcing has applications where machine learning falls short. We describe the design, implementation, and deployment of CrowdReply, a crowdsourced multiple choice question answering (MCQA) system. We deployed an Android app to enable the audience watching “Who wants to be millionaire?” quiz-show on TV to play along on their smartphones simultaneously. The app enabled us to collect data fro...

The article presents the experiments carried out as part of the participation in the pilot task of QA4MRE@CLEF 2013. In the developed system, we have first generated answer pattern by combining the question and each answer option to form the Hypothesis (H). Stop words and interrogative word are removed from each H and query words are identified to retrieve the most relevant sentences from the a...

In this paper, we present a study of MCQ aiming to define criteria in order to automatically select distractors. We are aiming to show that distractor editing follows rules like syntactic and semantic homogeneity according to associated answer, and the possibility to automatically identify this homogeneity. Manual analysis shows that homogeneity rule is respected to edit distractors and automat...

Multiple choice questions (MCQs) are widely used in digital learning systems, as they allow for automating the assessment process. However, due to increased literacy of students and advent social media platforms, MCQ tests shared online, teachers continuously challenged create new questions, which is an expensive time-consuming task. A particularly sensitive aspect creation devise relevant dist...

Introduction: Clinical reasoning is one of the most importantskills in the process of training a medical student to become anefficient physician. Assessment of the reasoning skills in a medicalschool program is important to direct students’ learning. One ofthe tests for measuring the clinical reasoning ability is ClinicalReasoning Problems (CRPs). The major aim of this study is tomeasure psycho...