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Addressing gaps in knowledge while reading
Abstract Reading is a common everyday activity for Reading is a common everyday activity for most of us. In this article, we examine the potential for using Wikipedia to fill in the gaps in one's own knowledge that may be encountered while reading. If gaps are encountered frequently while reading, then this may detract from the reader's final understanding of the given document. Our goal is to increase access to explanatory text for readers by retrieving a single Wikipedia article that is related to a text passage that has been highlighted. This approach differs from traditional search methods where the users formulate search queries and review lists of possibly relevant results. This explicit search activity can be disruptive to reading. Our approach is to minimize the user interaction involved in finding related information by removing explicit query formulation and providing a single relevant result. To evaluate the feasibility of this approach, we first examined the effectiveness of three contextual algorithms for retrieval. To evaluate the effectiveness for readers, we then developed a functional prototype that uses the text of the abstract being read as context and retrieves a single relevant Wikipedia article in response to a passage the user has highlighted. We conducted a small user study where participants were allowed to use the prototype while reading abstracts. The results from this initial study indicate that users found the prototype easy to use and that using the prototype significantly improved their stated understanding and confidence in that understanding of the academic abstracts they read.nding of the academic abstracts they read.
Added by wikilit team Added on initial load  +
Collected data time dimension Cross-sectional  +
Conclusion The prototype tool, LiteraryMark, developeThe prototype tool, LiteraryMark, developed for this study employs a less intrusive approach to retrieving related information. The user simply highlights text in the passage and a relevant Wikipedia article is displayed in a pop-up box. In this study, we examined six algorithms exploiting the language of the abstract, as well as links and categories of the Wikipedia articles, as the context to narrow the results to one relevant Wikipedia article. The most effective algorithm, using the terms of the abstract alone, was successful over 70% of the cases in a user study.ful over 70% of the cases in a user study.
Data source Experiment responses  + , Wikipedia pages  +
Doi 10.1002/asi.21168 +
Google scholar url http://scholar.google.com/scholar?ie=UTF-8&q=%22Addressing%2Bgaps%2Bin%2Bknowledge%2Bwhile%2Breading%22  +
Has author Christopher Jordan + , Carolyn Watters +
Has domain Computer science +
Has topic Reading support +
Issue 11  +
Pages 2255-2268  +
Peer reviewed Yes  +
Publication type Journal article  +
Published in Journal of the American Society for Information Science and Technology +
Research design Experiment  +
Research questions In this article, we examine the potential In this article, we examine the potential for using Wikipedia to fill in the gaps in one's own knowledge that may be encountered while reading. If gaps are encountered frequently while reading, then this may detract from the reader's final understanding of the given document. Our goal is to increase access to explanatory text for readers by retrieving a single Wikipedia article that is related to a text passage that has been highlighted. a text passage that has been highlighted.
Revid 10,649  +
Theories Undetermined
Theory type Design and action  +
Title Addressing gaps in knowledge while reading
Unit of analysis Article  +
Url http://dx.doi.org/10.1002/asi.21168  +
Volume 60  +
Wikipedia coverage Sample data  +
Wikipedia data extraction Dump  +
Wikipedia language English  +
Wikipedia page type Article  +
Year 2009  +
Creation dateThis property is a special property in this wiki. 15 March 2012 20:02:44  +
Categories Reading support  + , Computer science  + , Publications with missing comments  + , Publications  +
Modification dateThis property is a special property in this wiki. 30 January 2014 20:20:02  +
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