How EFL postgraduate students engage with automated written corrective feedback provided by Pigai in their academic writing?

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Article / Journal

Author(s) / editor(s):
Bei Cai et al

Year: 2026

Keywords: automated written corrective feedback, eye-tracking, learner engagement
Language(s): English

Abstract:
Case study of two English postgraduates using Pigai’s automated written corrective feedback (AWCF) on doctoral proposals, combining behavioral, cognitive (eye-tracking), and affective measures. Results show individual differences in engagement—eye-tracking revealed whether attention followed color-coded severity—linked to differing revision effort and trust, leading to implications for genre-adaptive AWE tools, tool–genre alignment, trust calibration, and personalized feedback via eye-tracking.

https://doi.org/10.1080/09588221.2026.2685747

Post created by: Virginia Signorini

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