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dc.contributor.authorAbualsaud, Mustafa
dc.date.accessioned2017-04-26 20:41:03 (GMT)
dc.date.available2017-04-26 20:41:03 (GMT)
dc.date.issued2017-04-26
dc.date.submitted2017-04-20
dc.identifier.urihttp://hdl.handle.net/10012/11758
dc.description.abstractAn important use of search engines is as a tool for learning. Search engines help users find learning material and increases their knowledge in various topics. The underlying process of learning while web searching and which documents a search engine should return to enhance the learner's comprehension and learning is a new area of research. In order to build better search engines to supplement the learning process and overall satisfaction, documents the learner searches for should be investigated. In this thesis, we propose six different factors that may be associated with learning and show which are significant in determining document-level satisfaction. We describe a lab-based user study in which each participant was assigned to a learning task with a pre and post quiz to measure their increase in knowledge after reading the selected documents. Using data collected at different stages of the study, our results indicate that documents with broadness of content, as well as novelty of information, are significant in determining satisfaction. We also show qualitative results that indicate a broader to more specific ordering of documents content is preferred for easier processing and retention of information. Our study provides insight into the characteristics of documents learners prefer to read and the order these documents should be presented to the learner, and provides us a better understanding of the learning process that occurs during search-as-learning related tasks.en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.subjectinformation retrievalen
dc.subjectsearch-as-learningen
dc.subjecthuman learningen
dc.titleLearning Factors and Determining Document-level Satisfaction In Search-as-Learningen
dc.typeMaster Thesisen
dc.pendingfalse
uws-etd.degree.departmentDavid R. Cheriton School of Computer Scienceen
uws-etd.degree.disciplineComputer Scienceen
uws-etd.degree.grantorUniversity of Waterlooen
uws-etd.degreeMaster of Mathematicsen
uws.contributor.advisorMark, Smucker
uws.contributor.advisorCharlie, Clarke
uws.contributor.affiliation1Faculty of Mathematicsen
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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