Yeon Su Park, Sieun Kim, Keighley Overbay, Seoyoung Kim, Sewook Wee, Daho Jung, Juho Kim (2026) — arXiv:2606.22609 (cs.HC) 📄 Full text (arXiv)
Park et al. (2026) explore AI-powered automated feedback for tutors on Ringle, a popular online English tutoring platform in the gig economy. Their research probe analyzed tutors' lessons and provided automated feedback, followed by a survey of 36 tutors. Findings reveal that while tutors perceived automated feedback more negatively than learner feedback, they valued it for self-monitoring and understanding platform expectations. However, discrepancies between automated and learner feedback often caused confusion. The study proposes design considerations for feedback systems on educational gig platforms. This work contributes to ai-feedback-quality research by highlighting the social and affective dimensions of AI feedback in tutoring contexts, and connects to teacher-role evolution and intelligent-tutoring system design in language-learning and higher-ed settings.
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