文章基本信息

标题：Instructor-aided asynchronous question answering system for online education and distance learning
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作者：Dunwei Wen ; John Cuzzola ; Lorna Brown 等
期刊名称：The International Review of Research in Open and Distributed Learning
印刷版ISSN：1492-3831
出版年度：2012
卷号：13
期号：5
页码：102-125
语种：English
出版社：AU Press
摘要：Question answering systems have frequently been explored for educational use. However, their value was somewhat limited due to the quality of the answers returned to the student. Recent question answering (QA) research has started to incorporate deep natural language processing (NLP) in order to improve these answers. However, current NLP technology involves intensive computing and thus it is hard to meet the real-time demand of traditional search. This paper introduces a question answering (QA) system particularly suited for delayed-answered questions that are typical in certain asynchronous online and distance learning settings. We exploit the communication delay between student and instructor and propose a solution that integrates into an organization’s existing learning management system. We present how our system fits into an online and distance learning situation and how it can better assist supporting students. The prototype system and its running results show the perspective and potential of this research.
关键词：automated question answering;natural language processing;information retrieval;LMS;distance education;online learning