Demo Data from SIGIR 2026 / reviewers in the wild / expert
Juhwan Ma
dblp:427/0610
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0000-4687-1491ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Learning and educational technologies · 50% Human-AI interaction · 50% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-AI interaction › AI agent
AI self-clones |
1.0 | 1 | 2026 | AI Twin: Enhancing ESL Speaking Practice through AI Self-Clones of a Better Me · CHI 2026 |
Learning and educational technologies
language learning |
1.0 | 1 | 2026 | AI Twin: Enhancing ESL Speaking Practice through AI Self-Clones of a Better Me · CHI 2026 |
Human-AI interaction
conversational agents |
0.3 | 1 | 2026 | AI Twin: Enhancing ESL Speaking Practice through AI Self-Clones of a Better Me · CHI 2026 |
Learning and educational technologies › personalized learning
personalized learning support |
0.3 | 1 | 2026 | AI Twin: Enhancing ESL Speaking Practice through AI Self-Clones of a Better Me · CHI 2026 |
Methods — techniques the papers use, named apart from their topics
within-subject study · 1.0second language acquisition theory · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | AI Twin: Enhancing ESL Speaking Practice through AI Self-Clones of a Better MeabstractAdvances in AI have enabled ESL learners to practice speaking through conversational systems. However, most tools rely on explicit correction, which can interrupt the conversation and undermine confidence. Grounded in second language acquisition and motivational psychology, we present AI Twin, a system that rephrases learner utterances into more fluent English and delivers them in the learner’s voice. Embodying a more confident and proficient version of the learner, AI Twin reinforces motivation through alignment with their aspirational Ideal L2 Self. Also, its use of implicit feedback through rephrasing preserves conversational flow and fosters an emotionally supportive environment. In a within-subject study with 20 adult ESL learners, we compared AI Twin with explicit correction and a non-personalized rephrasing agent. Results show that AI Twin elicited higher emotional engagement, with participants describing the experience as more motivating. These findings highlight the potential of self-representative AI for personalized, psychologically grounded support in ESL learning. Minju Park, Juhwan Ma, Dongwook Yoon |
CHI | 3 |