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A System for Generating Multiple Choice Questions: With a Novel Approach for Sentence Selection

Mukta Majumder, Sujan Kumar Saha
2015 Proceedings of the 2nd Workshop on Natural Language Processing Techniques for Educational Applications  
Multiple Choice Question (MCQ) plays a major role in educational assessment as well as in active learning.  ...  All the sentences in a text are not capable of generating MCQs; the first step of the system is to select the informative sentences.  ...  A few examples of the generated MCQs are given below: Conclusion In this paper we have presented a novel technique for selecting informative sentences for multiple choice questions generation from an  ... 
doi:10.18653/v1/w15-4410 dblp:conf/acl-tea/MajumderS15 fatcat:fdndbubrw5e6zgvzsebyxswlqu

PolyAQG Framework: Auto-generating assessment questions

Tee Hean Tan, Phoey Lee Teh, Zaharin Yusoff
2021 2021 IEEE International Conference on Computing (ICOCO)  
of question selections, as well as providing a better quality of questions.  ...  Designing and setting assessment questions for examinations is always a necessary task for educators.  ...  Seyler [9] also used the Template-based approach in his AQG. He developed multiple-choice questions by selecting a named entity from the knowledge graph as its answer.  ... 
doi:10.1109/icoco53166.2021.9673579 fatcat:6lyrqcyth5bdbgo2pmycicbkxe

Automatic Generation of Multiple Choice Questions Using Wikipedia [chapter]

Arjun Singh Bhatia, Manas Kirti, Sujan Kumar Saha
2013 Lecture Notes in Computer Science  
In this paper we present a system for automatic generation of multiple choice test items using Wikipedia.  ...  The sentences are selected using a set of pattern extracted from the existing questions. We also propose a novel technique for generating named entity distractors.  ...  Introduction Multiple choice question (MCQ) is a very popular form of assessment in which respondents are asked to select the best possible answer out of a set of choices.  ... 
doi:10.1007/978-3-642-45062-4_104 fatcat:c72nrw2owvgd3eq2p36hdxav3e

Web-Based Multiple Choice Question Answering for English and Arabic Questions [chapter]

Rawia Awadallah, Andreas Rauber
2006 Lecture Notes in Computer Science  
Answering multiple-choice questions, where a set of possible answers is provided together with the question, constitutes a simplified but nevertheless challenging area in question answering research.  ...  This paper introduces and evaluates two novel techniques for answer selection.  ...  Different approaches to improve system performance exist, such as using probabilistic algorithms to learn the best question paraphrase [2] or training a QA system to find possible sentence-length answers  ... 
doi:10.1007/11735106_54 fatcat:b5ef4c5sobgtxgxwzxmq7irhim

Massive Development of E-Testing Questions

Sasko Ristov, Marjan Gusev, Goce Armenski
2015 International Journal of Emerging Technologies in Learning (iJET)  
A pilot project is presented in achieved speedup of questing development for single- and multiple-choice questions, as well as questions with two options (true/false).  ...  This paper presents several techniques and strategies for massive e-testing questions generation. These techniques can be used to develop a large set of questions and assessment content.  ...  They can be considered as a variant of a multiple choice question, since for each question part, a set of multiple choice options is offered.  ... 
doi:10.3991/ijet.v10i4.4688 fatcat:nfw4utbe5jcudi3zz2yys2jcwa

QASC: A Dataset for Question Answering via Sentence Composition [article]

Tushar Khot, Peter Clark, Michal Guerquin, Peter Jansen, Ashish Sabharwal
2020 arXiv   pre-print
We present a multi-hop reasoning dataset, Question Answering via Sentence Composition(QASC), that requires retrieving facts from a large corpus and composing them to answer a multiple-choice question.  ...  Guided by these annotations, we present a two-step approach to mitigate the retrieval challenges. We use other multiple-choice datasets as additional training data to strengthen the reasoning model.  ...  tasks, Dirk Groeneveld for his help collecting seed facts, and Sumithra Bhakthavatsalam for helping generate the QASC fact corpus.  ... 
arXiv:1910.11473v2 fatcat:fivtavvtgba6bgk5p5ashvalfq

Semantic Attributes Model for Automatic Generation of Multiple Choice Questions

Ibrahim EldesokyFattoh, Amal Elsayed Aboutabl, Mohamed Hassan Haggag
2014 International Journal of Computer Applications  
In this research, an automatic multiple choice question generation system for evaluating semantic role labels and named entities is proposed.  ...  The system is tested using a set of sentences extracted from the data set for question answering.  ...  An approach for multiple choice questions generation for understanding the evaluation of adjectives in a text was proposed [4] .  ... 
doi:10.5120/18038-8544 fatcat:dgxvfc37y5avnpn4ajdjs72wle

AQG: Arabic Question Generator

Kheira Z. Bousmaha, Nour H. Chergui, Mahfoud Sid Ali Mbarek, Lamia Belguith Hadrich
2020 Revue d'intelligence artificielle : Revue des Sciences et Technologies de l'Information  
This paper presents a novel automatic question generation approach that generates questions as a form of support for children learning through the platform QUIZZITO.  ...  Our goal is to enrich Quizzito's online quiz platform, which contains more than 254.5k quizzes, and to provide it with a generator of Arabic language questions for children's texts.  ...  INTRODUCTION There are many uses of an automatic question generator (QG): the creation of multiple-choice tests and quizzes for learning materials, human-machine dialogue systems, or interactive Question-Answer  ... 
doi:10.18280/ria.340606 fatcat:ffuol73adzd4xa65rzvemv6gdq

Resolving Intent Ambiguities by Retrieving Discriminative Clarifying Questions [article]

Kaustubh D. Dhole
2020 arXiv   pre-print
In order to disambiguate queries which are ambiguous between two intents, we propose a novel method of generating discriminative questions using a simple rule based system which can take advantage of any  ...  question generation system without requiring annotated data of clarification questions.  ...  Acknowledgments We are grateful to the members of Amelia Science, RnD, IPsoft, Bangalore for their invaluable suggestions.  ... 
arXiv:2008.07559v1 fatcat:nk5rrvutsvgbjprd5cm6fa2fee

Generating Question-Answer Hierarchies

Kalpesh Krishna, Mohit Iyyer
2019 Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics  
The process of knowledge acquisition can be viewed as a question-answer game between a student and a teacher in which the student typically starts by asking broad, open-ended questions before drilling  ...  Acknowledgements We thank the anonymous reviewers for their insightful comments.  ...  This work was supported in part by research awards from the Allen Institute for Artificial Intelligence and Adobe Research.  ... 
doi:10.18653/v1/p19-1224 dblp:conf/acl/KrishnaI19 fatcat:mkdkkrl355alrh44zm3ki2p2by

Proposing Plausible Answers for Open-ended Visual Question Answering [article]

Omid Bakhshandeh, Trung Bui, Zhe Lin, Walter Chang
2016 arXiv   pre-print
We study the importance of generating plausible answers to a given question by introducing the novel task of 'Answer Proposal': for a given open-ended question, a system should generate a ranked list of  ...  We experiment with various models including a neural generative model as well as a semantic graph matching one.  ...  The answer is either selected from a list of choices (for a multiple-choice question), or is generated (for an open-ended question) , where the open-ended task is more challenging than the multiple-choice  ... 
arXiv:1610.06620v2 fatcat:ckfirkpdszhnhdvju67bsnrsnu

QASC: A Dataset for Question Answering via Sentence Composition

Tushar Khot, Peter Clark, Michal Guerquin, Peter Jansen, Ashish Sabharwal
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
We present a multi-hop reasoning dataset, Question Answering via Sentence Composition (QASC), that requires retrieving facts from a large corpus and composing them to answer a multiple-choice question.  ...  Guided by these annotations, we present a two-step approach to mitigate the retrieval challenges. We use other multiple-choice datasets as additional training data to strengthen the reasoning model.  ...  tasks, Dirk Groeneveld for his help collecting seed facts, and Sumithra Bhakthavatsalam for helping generate the QASC fact corpus.  ... 
doi:10.1609/aaai.v34i05.6319 fatcat:tnr4rubg7rearcbzmtuzw2jr5u

Crowdsourcing Multiple Choice Science Questions

Johannes Welbl, Nelson F. Liu, Matt Gardner
2017 Proceedings of the 3rd Workshop on Noisy User-generated Text  
We present a novel method for obtaining high-quality, domain-targeted multiple choice questions from crowd workers.  ...  It produces model suggestions for document selection and answer distractor choice which aid the human question generation process.  ...  The first contribution of this paper is a general method for mitigating the difficulties of crowdsourcing QA data, with a particular focus on multiple choice science questions.  ... 
doi:10.18653/v1/w17-4413 dblp:conf/aclnut/WelblLG17 fatcat:djxqvrctrzcsxnfhtlg3o75bn4

MappSent: a Textual Mapping Approach for Question-to-Question Similarity

Amir Hazem, Basma El Amal Boussaha, Nicolas Hernandez
2017 RANLP 2017 - Recent Advances in Natural Language Processing Meet Deep Learning  
Inspired by Mikolov et al. (2013a); Arora et al. (2017) findings and by a bilingual word mapping technique presented in Artetxe et al. (2016), we introduce MappSent, a novel approach for textual similarity  ...  Based on a linear sentence embedding representation, its principle is to build a matrix that maps sentences in a joint-subspace where similar sets of sentences are pushed closer.  ...  In this paper, we propose MappSent, a novel approach for textual similarity that we evaluate on the SemEval question-to-question similarity task.  ... 
doi:10.26615/978-954-452-049-6_040 dblp:conf/ranlp/HazemBH17 fatcat:hzzytcacgbab5b36v6uby6iusq

A question-entailment approach to question answering

Asma Ben Abacha, Dina Demner-Fushman
2019 BMC Bioinformatics  
Results: We propose a novel QA approach based on Recognizing Question Entailment (RQE) and we describe the QA system and resources that we built and evaluated on real medical questions.  ...  Second, we combine IR models with the best RQE method to select entailed questions and rank the retrieved answers.  ...  Shooshan (NLM/NIH) for her help with the judgment of the retrieved answers, and Ellen Voorhees (NIST) for her help with the TREC LiveQA evaluation.  ... 
doi:10.1186/s12859-019-3119-4 fatcat:ztrn5jaiwjdizmicuscn466ghq
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