An automatic measure of cross-language text structures

• In Event: Learning Analytics, AI, and Immersive Learning

Short Description

The purpose of this investigation is to further confirm and extend the utility of the computational approach for measuring knowledge structures (KS) inherent in lesson text artifacts beyond English into Korean language texts. The English and parallel Korean versions of fifty expository and fifty narrative texts were converted into KS network graphs for analysis, based on key concepts and their relative proximity relationships in the texts.

Authors

• Presenter: Kyung Kim, Northern Illinois University

• Contributor: Kioh Kim, University of Louisiana at Monroe