Eye tracking can identify which words a second-language reader had trouble understanding¶

Claim · All claims
Evidence · 1 study · design r2 · q2
Currency · newest study 2013 · not yet checked against its sources · not reviewed by a person · overdue for a recheck since 2016: tool and model accuracy changes quickly

Subclaims¶

q2 i? Fixation histograms mapped onto digitized passages revealed words readers marked as difficult, and the method worked for all words marked as difficult by the participants. → Kai Kunze 2013

Evidence¶

Kai Kunze 2013¶

Kai Kunze, Masakazu Iwamura, Koichi Kise, Seiichi Uchida, and Shinichiro Omachi. (2013). Activity Recognition for the Mind: Toward a Cognitive “Quantified Self.” Computer, IEEE Computer Society, October 2013. http://kaikunze.de/papers/2013Kunze-1.pdf

q2 · i? · design · r2

Study of 10 native Japanese speakers learning English who read 10 TOEIC passages while wearing the iView X eye tracker, then marked words they did not understand. Eye gaze was mapped to digitized passages using locally likely arrangement hashing (LLAH), and fixation histograms revealed trouble words; the method "worked for all words marked as difficult". No effect size is printed.

"The method worked for all words marked as difficult by the partici- pants."

Discussion¶

Related Claims¶

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