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Eiji Ikeda

dblp:162/0789 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0000-0003-0420-4564ORCID · 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 · 44% Human-AI interaction · 44% Human-robot interaction · 13%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Learning and educational technologies
skill training
1.012026
ViSTAR: Virtual Skill Training with Augmented Reality with 3D Avatars and LLM coaching agent · CHI 2026

Methods — techniques the papers use, named apart from their topics

large language model · 1.0behavioral skills training framework · 1.03d motion reconstruction · 1.0
YearPublicationVenuePosition
2026 ViSTAR: Virtual Skill Training with Augmented Reality with 3D Avatars and LLM coaching agent
abstract
We present ViSTAR, a Virtual Skill Training system in AR that supports self-guided basketball skill practice, with feedback on balance, posture, and timing. From a formative study with basketball players and coaches, the system addresses three challenges: understanding skills, identifying errors, and correcting mistakes. ViSTAR follows the Behavioral Skills Training (BST) framework-instruction, modeling, rehearsal, and feedback. It provides feedback through visual overlays, rhythm and timing cues, and an AI-powered coaching agent using 3D motion reconstruction. We generate verbal feedback by analyzing spatio-temporal joint data and mapping features to natural-language coaching cues via a Large Language Model (LLM). A key novelty is this feedback generation: motion features become concise coaching insights. In two studies (N=16), participants generally preferred our AI-generated feedback to coach feedback and reported that ViSTAR helped them notice posture and balance issues and refine movements beyond self-observation.
Chunggi Lee, Hayato Saiki, Tica Lin, Eiji Ikeda, Kenji Suzuki 0002, Chen Zhu-Tian, Hanspeter Pfister
CHI4