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Description: This study introduces Tsukuba Eye-tracking Corpus (TECO), a dataset of eye-tracking records from Japanese L2 English learners engaged in text reading. TECO encompasses eye-tracking data for over 410,000 tokens, collected from 41 Japanese students who each read 30 English passages ranging in length from 300–400 words. In this article, we detail the design of TECO and report on the reliability of commonly used eye-tracking measures (e.g., skipping, first fixation duration, and regression) along with their descriptive statistics and distribution. We also validate the corpus by illustrating the impact of several lexical and reader factors (e.g., word length and reading proficiency) on some eye-tracking measures. TECO will serve as a valuable resource for researchers who are keen on exploring the cognitive processes involved in L2 reading.

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