Demo Data from EDBT 2026 / reviewers in the wild / expert
Stephen P. Kaputsos
dblp:249/3252
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 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% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computing education › AI education
K-12 AI education |
0.5 | 1 | 2021 | Teacher Perspectives on How To Train Your Robot: A Middle School AI and Ethics Curriculum · AAAI 2021 |
Computing education
teacher professional development |
0.1 | 1 | 2021 | Teacher Perspectives on How To Train Your Robot: A Middle School AI and Ethics Curriculum · AAAI 2021 |
Methods — techniques the papers use, named apart from their topics
teacher interviews · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Teacher Perspectives on How To Train Your Robot: A Middle School AI and Ethics CurriculumabstractTo enable a diverse citizenry to fully participate in future society, we must prepare all students to construct and critique emerging technologies like Artificial Intelligence (AI). Classrooms are important spaces to teach students these skills, however there are few AI curricula that have been developed for and used by K-12 teachers. We developed the \textit{How to Train Your Robot: AI and Ethics Curriculum} for middle school teachers who want to introduce AI to their students. This paper describes the curriculum and professional development we used to prepare teachers to run a five-day AI course. Before and after they ran the curriculum, we interviewed teachers to understand their opinions on pedagogical approaches to teaching AI, meeting students' needs, and the feasibility of doing the activities in the classroom. Our results indicate that, with appropriate training, even teachers who were new to computer science felt prepared and successfully engaged their students in the topic. We hope our insights will inform future efforts to realize AI education in primary and secondary classrooms. Randi Williams, Stephen P. Kaputsos, Cynthia Breazeal |
AAAI | 2 |