Eye Tracking Technology in Detecting the Switch Cost in the Intra-sentential Code-Switching Contexts
DOI:
https://doi.org/10.3991/ijet.v13i05.8109Keywords:
eye tracking, switch cost, unilingual, intra-sentential code-switching, word frequencyAbstract
Switch cost and cost site have been controversial issues in the code-switching studies. This research conducted an eye tracking experiment on eight bilingual subjects to measure their switch cost and cost site in comprehending the intra-sentential code-switching (Chinese and English) and the unilingual (pure Chinese) stimuli. The English words and their Chinese translations or equivalents were assumed as the key words in either a unilingual or an intra-sentential code-switching paragraph. These key words were located as areas of interest (AOI) with the same height and consisted of three word-frequency levels. After the experiment, the subjects were required to do a comprehension test to ensure their real understanding of the English words. Their performances in two different reading contexts were compared by adopting a paired sample t-test. Their eye movement data were validated by using 2 x 3 repeated measures ANOVA. It was revealed that: 1) the subjects’ scores in the intra-sentential code-switching contexts were higher than those in the unilingual ones, i.e. reading efficiency increased in the intra-sentential code-switching contexts; 2) word frequency had little effect on word recognition speed in the intra-sentential code-switching contexts, i.e., the least frequently used words did not necessarily take the subjects’ more time or vice versa; 3) even if a switch cost occurred(on rare occasions), it was not necessarily at the switching site, and low frequency words in alternating languages did impair performance even when the switch occurred at a sentence boundary.
Downloads
Published
2018-04-30
How to Cite
Wu, L., & Xi, C. (2018). Eye Tracking Technology in Detecting the Switch Cost in the Intra-sentential Code-Switching Contexts. International Journal of Emerging Technologies in Learning (iJET), 13(05), pp. 117–129. https://doi.org/10.3991/ijet.v13i05.8109
Issue
Section
Papers