Demo Data from VLDB 2026 / reviewers in the wild / expert
Atefeh Mahdavi Goloujeh
dblp:248/9596
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2024
0009-0005-2369-7263ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 2 · 1 first-author · 2 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
2 papers |
Human-AI interaction · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computing education · 100% | |
| Artificial intelligence
1 paper |
Generative modeling · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computing education › AI education
AI literacy |
0.8 | 1 | 2024 | Testing, Socializing, Exploring: Characterizing Middle Schoolers' Approaches to and Conceptions of ChatGPT · CHI 2024 |
Human-AI interaction › generative AI
text-to-image generation |
0.8 | 1 | 2024 | Is It AI or Is It Me? Understanding Users' Prompt Journey with Text-to-Image Generative AI Tools · CHI 2024 |
Machine learning › Generative modeling › diffusion model
text-to-image generation |
0.2 | 1 | 2024 | Is It AI or Is It Me? Understanding Users' Prompt Journey with Text-to-Image Generative AI Tools · CHI 2024 |
Human-AI interaction
generative AI |
0.2 | 1 | 2024 | Testing, Socializing, Exploring: Characterizing Middle Schoolers' Approaches to and Conceptions of ChatGPT · CHI 2024 |
Methods — techniques the papers use, named apart from their topics
thematic analysis · 1.5semi-structured interviews · 1.5focus groups · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Testing, Socializing, Exploring: Characterizing Middle Schoolers' Approaches to and Conceptions of ChatGPTabstractAs generative AI rapidly enters everyday life, educational interventions for teaching about AI need to cater to how young people, in particular middle schoolers who are at a critical age for reasoning skills and identity formation, conceptualize and interact with AI. We conducted nine focus groups with 24 middle school students to elicit their interests, conceptions of, and approaches to a popular generative AI tool, ChatGPT. We highlight a) personally and culturally-relevant topics to this population, b) three distinct approaches in students’ open-ended interactions with ChatGPT: AI testing-oriented, AI socializing-oriented, and content exploring-oriented, and 3) an improved understanding of youths’ conceptions and misconceptions of generative AI. While misconceptions highlight gaps in understanding what generative AI is and how it works, most learners show interest in learning about what AI is and what it can do. We discuss the implications of these conceptions for designing AI literacy interventions in museums. Yasmine Belghith, Atefeh Mahdavi Goloujeh, Brian Magerko, Duri Long, Tom McKlin |
CHI | 2 |
| 2024 | Is It AI or Is It Me? Understanding Users' Prompt Journey with Text-to-Image Generative AI ToolsabstractGenerative Artificial Intelligence (AI) has witnessed unprecedented growth in text-to-image AI tools. Yet, much remains unknown about users’ prompt journey with such tools in the wild. In this paper, we posit that designing human-centered text-to-image AI tools requires a clear understanding of how individuals intuitively approach crafting prompts, and what challenges they may encounter. To address this, we conducted semi-structured interviews with 19 existing users of a text-to-image AI tool. Our findings (1) offer insights into users’ prompt journey including structures and processes for writing, evaluating, and refining prompts in text-to-image AI tools and (2) indicate that users must overcome barriers to aligning AI to their intents, and mastering prompt crafting knowledge. From the findings, we discuss the prompt journey as an individual yet a social experience and highlight opportunities for aligning text-to-image AI tools and users’ intents. Atefeh Mahdavi Goloujeh, Anne Sullivan, Brian Magerko |
CHI | 1 |