47 citations · 113 across the 11 of their papers we have counts for
11 papers
Nanomentoring: Investigating How Quickly People Can Help People Learn Feature-Rich Software
Ian Drosos, Jo Vermeulen, George Fitzmaurice +1
People frequently use online forums to get help from experts to answer questions about feature-rich software. However, they may have to wait minutes, hours, or even days to receive…
Vibe coding: programming through conversation with artificial intelligence
Advait Sarkar, Ian Drosos
We examine "vibe coding": an emerging programming paradigm where developers primarily write code by interacting with code-generating large language models rather than writing code…
"It makes you think": Provocations Help Restore Critical Thinking to AI-Assisted Knowledge Work
Ian Drosos, Advait Sarkar, Xiaotong +2
Recent research suggests that the use of Generative AI tools may result in diminished critical thinking during knowledge work. We study the effect on knowledge work of provocations…
When Copilot Becomes Autopilot: Generative AI's Critical Risk to Knowledge Work and a Critical Solution
Advait Sarkar, Xiaotong, Xu +3
Generative AI, with its tendency to "hallucinate" incorrect results, may pose a risk to knowledge work by introducing errors. On the other hand, it may also provide unprecedented o…
Dynamic Prompt Middleware: Contextual Prompt Refinement Controls for Comprehension Tasks
Ian Drosos, Jack Williams, Advait Sarkar +1
Effective prompting of generative AI is challenging for many users, particularly in expressing context for comprehension tasks such as explaining spreadsheet formulas, Python code,…
Evaluating the Evaluator: Measuring LLMs' Adherence to Task Evaluation Instructions
Bhuvanashree Murugadoss, Christian Poelitz, Ian Drosos +5
LLMs-as-a-judge is a recently popularized method which replaces human judgements in task evaluation (Zheng et al. 2024) with automatic evaluation using LLMs. Due to widespread use…
Improving Steering and Verification in AI-Assisted Data Analysis with Interactive Task Decomposition
Majeed Kazemitabaar, Jack Williams, Ian Drosos +4
LLM-powered tools like ChatGPT Data Analysis, have the potential to help users tackle the challenging task of data analysis programming, which requires expertise in data processing…
"It's like a rubber duck that talks back": Understanding Generative AI-Assisted Data Analysis Workflows through a Participatory Prompting Study
Ian Drosos, Advait Sarkar, Xiaotong Xu +3
Generative AI tools can help users with many tasks. One such task is data analysis, which is notoriously challenging for non-expert end-users due to its expertise requirements, and…
"My toxic trait is thinking I'll remember this": gaps in the learner experience of video tutorials for feature-rich software
Ian Drosos, Advait Sarkar, Andrew D. Gordon
Video tutorials are a popular medium for informal and formal learning. However, when learners attempt to view and follow along with these tutorials, they encounter what we call gap…
Participatory prompting: a user-centric research method for eliciting AI assistance opportunities in knowledge workflows
Advait Sarkar, Ian Drosos, Rob Deline +5
Generative AI, such as image generation models and large language models, stands to provide tremendous value to end-user programmers in creative and knowledge workflows. Current re…
Co-audit: tools to help humans double-check AI-generated content
Andrew D. Gordon, Carina Negreanu, José Cambronero +9
Users are increasingly being warned to check AI-generated content for correctness. Still, as LLMs (and other generative models) generate more complex output, such as summaries, tab…