Predicting Knowledge Gain during Web Search based on Eye-movement Patterns

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dc.identifier.uri http://dx.doi.org/10.15488/13172
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/13278
dc.contributor.author Khawatmi, Ahmad eng
dc.date.accessioned 2022-12-22T11:23:48Z
dc.date.available 2022-12-22T11:23:48Z
dc.date.issued 2022
dc.identifier.citation Khawatmi, Ahmad: Predicting Knowledge Gain during Web Search based on Eye-movement Patterns. Hannover : Gottfried Wilhelm Leibniz Universität, Institut für Verteilte Systeme, Bachelor Thesis, 2022, XVI, 52 S. DOI: https://doi.org/10.15488/13172 eng
dc.description.abstract The content on the internet is expanding exponentially, and the virtual space has become a messy place. Therefore, acquiring information to fulfill the learning need is a difficult task. Search as Learning (SAL) is a new domain that investigates the importance of the learning process and supports individuals in acquiring information. Therefore, a solution to make obtaining information easier for knowledge seekers from a web search. Prior work in this field focused extensively on resource data (e.g., text and multimedia resources) and behavioral data (e.g., search interactions) to make a knowledge gain (KG) prediction during a web search. However, eye movement and reading pattern data are yet to be explored. Thereby, in this work, we introduce a set of features related to eye movements that would help us predict knowledge gain based on the reading pattern of the participants. For this purpose, we relied on data from a prior work-study, in which 114 participants had to acquire information about the foundation of lightning and thunder from a web search. We used a cutting-edge approach for the evaluation. Moreover, we extended with a word-level mapping to eye fixations of web pages, unlike prior work that attempted to rely on the eye’s central vision to map the eye fixations. Experimental results demonstrate the ability to predict knowledge gain based on the reading pattern and eye movements. eng
dc.language.iso eng eng
dc.publisher Hannover : Gottfried Wilhelm Leibniz Universität, Institut für Verteilte Systeme
dc.rights Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. eng
dc.subject Knowledge Gain eng
dc.subject Knowledge Gain Predicition eng
dc.subject Eye-movement eng
dc.subject Reading Patterns eng
dc.subject Informational Search eng
dc.subject Search as Learning eng
dc.subject SAL eng
dc.subject Information Retrieval eng
dc.subject IR eng
dc.subject.ddc 004 | Informatik eng
dc.title Predicting Knowledge Gain during Web Search based on Eye-movement Patterns eng
dc.type BachelorThesis eng
dc.type Text eng
dcterms.extent XVI, 52 S. eng
dc.description.version publishedVersion eng
tib.accessRights frei zug�nglich eng


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