Abstract
In order to further validate and extend the application of GIKS (Graphical Interface of Knowledge Structure) beyond English, this investigation applies the GIKS to capture, visually represent, and compare text structures inherent in two “contrasting” languages. The English and parallel Korean versions of 50 expository and 50 narrative texts from Newsweek, Popular Science and Vogue magazines were converted into Pathfinder network graphs for analysis, based on key concepts and their relative proximity relationships in the texts. Results indicate that the novel text structures obtained by this approach reveal unique, useful, and interesting linguistic differences for the English and Korean texts, confirming prior linguistic literature (Sohn 2001). Particularly, the analyses show that the expository text structures are somewhat similar between these two languages while the narrative text structures are quite different. These findings demonstrate the utility of the GIKS for representing the nature of texts as manifested in different languages. If further confirmed in other languages, this computer-based approach could offer a new way for students and instructors to interact with lesson texts by providing a visual representation of text structure, regardless of language.
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Funding was provided by the Pennsylvania State University’s Center for Online Innovation in Learning (Grant No. 05-042-23 UP10010).
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Kim, K. An Automatic Measure of Cross-Language Text Structures. Tech Know Learn 23, 301–314 (2018). https://doi.org/10.1007/s10758-017-9320-5
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DOI: https://doi.org/10.1007/s10758-017-9320-5