Demo Data from EDBT 2026 / reviewers in the wild / expert
Richard Ko
dblp:374/8822
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0001-4300-9625ORCID · 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 |
Human-AI interaction · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-AI interaction
stakeholder perspectives |
0.8 | 1 | 2024 | Teachers, Parents, and Students' perspectives on Integrating Generative AI into Elementary Literacy Education · CHI 2024 |
Methods — techniques the papers use, named apart from their topics
workshop · 0.8interviews · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Teachers, Parents, and Students' perspectives on Integrating Generative AI into Elementary Literacy EducationabstractThe viral launch of new generative AI (GAI) systems, such as ChatGPT and Text-to-Image (TTL) generators, sparked questions about how they can be effectively incorporated into writing education. However, it is still unclear how teachers, parents, and students perceive and suspect GAI systems in elementary school settings. We conducted a workshop with twelve families (parent-child dyads) with children ages 8-12 and interviewed sixteen teachers in order to understand each stakeholder’s perspectives and opinions on GAI systems for learning and teaching writing. We found that the GAI systems could be beneficial in generating adaptable teaching materials for teachers, enhancing ideation, and providing students with personalized, timely feedback. However, there are concerns over authorship, students’ agency in learning, and uncertainty concerning bias and misinformation. In this article, we discuss design strategies to mitigate these constraints by implementing an adults-oversight system, balancing AI-role allocation, and facilitating customization to enhance students’ agency over writing projects. Ariel Han, Xiaofei Zhou 0004, Zhenyao Cai, Shenshen Han, Richard Ko, Seth Corrigan, Kylie Peppler |
CHI | 5 |