Demo Data from EDBT 2026 / reviewers in the wild / expert
H. Nicole Pang
dblp:341/9006
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2023
0000-0003-1097-7037ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021Human-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% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computing education
AI education |
0.7 | 1 | 2023 | "How Can I Code A.I. Responsibly?": The Effect of Computational Action on K-12 Students Learning and Creating Socially Responsible A.I · AAAI 2023 |
Computing education › ethics education
AI ethics education |
0.7 | 1 | 2023 | "How Can I Code A.I. Responsibly?": The Effect of Computational Action on K-12 Students Learning and Creating Socially Responsible A.I · AAAI 2023 |
Computing education › AI education
K-12 AI education |
0.7 | 1 | 2023 | "How Can I Code A.I. Responsibly?": The Effect of Computational Action on K-12 Students Learning and Creating Socially Responsible A.I · AAAI 2023 |
Methods — techniques the papers use, named apart from their topics
impact matrix · 0.7computational action process · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | "How Can I Code A.I. Responsibly?": The Effect of Computational Action on K-12 Students Learning and Creating Socially Responsible A.IabstractTeaching young people about artificial intelligence (A.I.) is recognized globally as an important education effort by organizations and programs such as UNICEF, OECD, Elements of A.I., and AI4K12. A common theme among K-12 A.I. education programs is teaching how A.I. can impact society in both positive and negative ways. We present an effective tool that teaches young people about the societal impact of A.I. that goes one step further: empowering K-12 students to use tools and frameworks to create socially responsible A.I. The computational action process is a curriculum and toolkit that gives students the lessons and tools to evaluate positive and negative impacts of A.I. and consider how they can create beneficial solutions that involve A.I. and computing technology. In a human-subject research study, 101 U.S. and international students between ages 9 and 18 participated in a one-day workshop to learn and practice the computational action process. Pre-post questionnaires measured on the Likert scale students’ perception of A.I. in society and students' desire to use A.I. in their projects. Analysis of the results shows that students who identified as female agreed more strongly with having a concern about the impacts of A.I. than those who identified as male. Students also wrote open-ended responses to questions about what socially responsible technology means to them pre- and post-study. Analysis shows that post-intervention, students were more aware of ethical considerations and what tools they can use to code A.I. responsibly. In addition, students engaged actively with tools in the computational action toolkit, specifically the novel impact matrix, to describe the positive and negative impacts of A.I. technologies like facial recognition. Students demonstrated breadth and depth of discussion of various A.I. technologies' far-reaching positive and negative impacts. These promising results indicate that the computational action process can be a helpful addition to A.I. education programs in furnishing tools for students to analyze the effects of A.I. on society and plan how they can create and use socially responsible A.I. H. Nicole Pang, Robert Parks, Cynthia Breazeal, Harold Abelson |
AAAI | 1 |
| 2023 | Designing a Computational Action Program to Tackle Global ChallengesabstractAs artificial intelligence involves and shapes personal and professional lives, there is a critical need to nurture and prepare AI-enabled problem-solvers. FutureMakers is designed as a six-week program that introduces foundational knowledge and essential skills to develop innovative solutions with AI responsibly. Our study utilized a convergent mixed-method design to evaluate the impact of the FutureMakers program on students' learning outcomes and shifting perspectives on AI. Quantitative data showed a shift in students' AI literacy with a large effect size. Qualitative data, based on student interviews, showed an awareness of an ethical engineering design process in applying technical skills to solve real-world problems. The program showed the impact of the computational action approach to tackle authentic challenges. Xiaoxue Du, Robert Parks, Selim Tezel, Jeff Freilich, H. Nicole Pang, Harold Abelson, Cynthia Breazeal |
SIGCSE (2) | 5 |