EDBT 2026 Demo / reviewers in the wild / expert
Alicia Wanyi Liu
dblp:433/1518
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0005-8535-2981ORCID · 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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computing education · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Human-AI interaction · 77% Learning and educational technologies · 23% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computing education › programming education
block-based programming |
1.0 | 1 | 2026 | Exploring the Impacts and Challenges of Vibe Coding Paradigm to Children's Programming Learning and Practices · CHI 2026 |
Computing education
programming education |
1.0 | 1 | 2026 | Exploring the Impacts and Challenges of Vibe Coding Paradigm to Children's Programming Learning and Practices · CHI 2026 |
Methods — techniques the papers use, named apart from their topics
workshop study · 2.0qualitative analysis · 2.0interview study · 2.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Exploring the Impacts and Challenges of Vibe Coding Paradigm to Children's Programming Learning and PracticesabstractRecent advances in generative AI have introduced a new programming paradigm—vibe coding, a natural language–driven mode of AI collaboration. While promising for adults, little is known about how children engage with this approach, especially in block-based environments. To explore this gap, we conducted workshops with children of varying Scratch experience (n=41) and interviewed five Scratch teachers. Our study investigates how vibe coding impacts children’s programming learning and practice, and what challenges arise. Findings show that vibe coding has both positive and negative impacts across three key contexts of children’s programming experience: acquisition, application, and creation. Across the stages of vibe coding—goal articulation, information interpretation, and outcome evaluation—children encounter distinct challenges. By examining the mismatches between core assumptions of vibe coding and children’s needs, and analyzing its applicability across different contexts, we offer child-centered design implications for future vibe coding systems and GenAI tools. Janice Jianing Si, Qiuning Wang, Alicia Wanyi Liu, Xin Lin 0006, Yujun Zhu, Xiaobo Zhou 0002, April Yi Wang, Kanye Ye Wang |
CHI | 4 |