Learners engaged extensively with the chatbot, overwhelmingly communicating in Japanese rather than English¶

Claim · All claims
Evidence · 1 study · associational r1 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Across the semester learners averaged about 39 writing sessions and 177 messages each, and chose Japanese for 98.16% of chatbot messages versus 1.84% in English. → Steve Woollaston 2026

Evidence¶

Steve Woollaston 2026¶

Steve Woollaston, Brendan Flanagan, Yuko Toyokawa and Hiroaki Ogata. (2026). Penny: Transition Network Analysis of Learner-Chatbot Interactions in Scaffolded EFL Writing. Preprint, accepted at the 1st Workshop on Transition Network Analysis (TNA) at LAK '26. https://arxiv.org/abs/2607.14575 doi:10.48550/arxiv.2607.14575

q2 · i? · associational · r1

Descriptive analysis of 4,651 writing sessions and 21,061 messages from 119 learners (Table 1): mean 39.06 sessions (SD = 12.57) and 176.92 messages (SD = 156.53) per learner; "Learners overwhelmingly chose to interact with Penny in their native language of Japanese (98.16%)".

"Learners overwhelmingly chose to interact with Penny in their native language of Japanese (98.16%) instead of English (1.84%)."

Discussion¶

Related Claims¶

• Chatbot engagement was highly uneven: 8 of 15 voluntary users interacted continuously while 7 interacted superficially — related
• Voluntary StatBot use was highly uneven and deadline-driven, with about 27% of students never using the chatbot — related
• Student chatbot queries were overwhelmingly task-oriented initial inquiries, dominated by definition requests and pasted assignment questions rather than iterative critique — related
• Most unrestricted-mode interactions were direct answer retrieval: 52.9% of exercise interactions were copy-paste of the question, and participant answers were linguistically near-identical to chatbot text in 25.3% of cases — related