Penny

Product or Programme · All products and programmes
Evidence · 4 claims (4 for) · 1 study (1 associational), q2 · 0 of 1 report an effect size · 4 claims rest on one study

Description

Penny is a GPT-4o-powered chatbot developed by Steve Woollaston and colleagues to support Japanese junior-high EFL learners' English writing practice through structured corrective feedback.

Components

Claims

• Learner-chatbot EFL writing interaction follows two dominant behavioural loops: a Revision Loop and a Chat Loop [+W]
• Learners engaged extensively with the chatbot, overwhelmingly communicating in Japanese rather than English [+W]
• EFL proficiency significantly shapes chatbot interaction: high-proficiency learners over-engage in dialogue while low-proficiency learners over-rely on feedback requests [+W]
• Revision after chatbot feedback predominantly results in successful uptake, indicating effective error correction [+W]

Related Products and Programmes

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Key Sources

• 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.

Page metadata

Field	Value
type	product
id	penny
title	Penny
description	Penny is a GPT-4o-powered chatbot developed by Steve Woollaston and colleagues to support Japanese junior-high EFL learners' English writing practice through structured corrective feedback.
status	review
product_kind	software
generated	by process:settle-candidates on 2026-10-11
trust	unverified — no one has confirmed this page's content

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