Demo Data from EDBT 2026 / reviewers in the wild / expert
Zijing Tang
dblp:433/4813
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0004-5931-6453ORCID · 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 · 70% Human-AI interaction · 30% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Learning and educational technologies › video-based learning
instructional video |
1.0 | 1 | 2026 | Epimopilot : An LLM-infused Epistemic Emotion Support System to Boost Self-regulated Asynchronous Online Video Learning · CHI 2026 |
Learning and educational technologies
self-regulated learning |
1.0 | 1 | 2026 | Epimopilot : An LLM-infused Epistemic Emotion Support System to Boost Self-regulated Asynchronous Online Video Learning · CHI 2026 |
Learning and educational technologies › online learning
asynchronous learning |
0.3 | 1 | 2026 | Epimopilot : An LLM-infused Epistemic Emotion Support System to Boost Self-regulated Asynchronous Online Video Learning · CHI 2026 |
Methods — techniques the papers use, named apart from their topics
knowledge graph · 1.0emotion recognition · 1.0LLM-powered intervention · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Epimopilot : An LLM-infused Epistemic Emotion Support System to Boost Self-regulated Asynchronous Online Video LearningabstractSelf-regulated learning through asynchronous online videos lacks direct social-emotional interactions, often resulting in isolated learning experiences. We present Epimopilot, a system transforming emotional cues from time-synchronized comments (danmaku) into personified virtual companions to create a sense of community. Epimopilot visualizes collective epistemic emotions through emotional companions while providing LLM-powered interventions upon detecting learning difficulties through emotional cues. A within-subjects experiment (N=32) comparing Epimopilot with a baseline system demonstrated significant improvements in learning persistence, engagement, and knowledge comprehension. Results revealed that emotion-infused companion interactions combined with targeted AI assistance significantly enhanced self-regulated learning experiences. The analysis yielded design principles for recognizing epistemic emotions and integrating collective emotional cues with a knowledge graph. This work contributes an innovative approach to foster a co-presence learning experience in asynchronous environments through emotion recognition and adaptive cognitive support. Weihang Qin, Yuefan Fang, Zijing Tang, Shimin Kang |
CHI | 4 |