Hyungyu Shin

schoolKorea Advanced Institute of Science and Technologybar_chart#1470 Global Rank

Total Papers

HCI Rank

#1470

Research Areas

Years Active

Recent Publications

PlanTogether: Facilitating AI Application Planning Using Information Graphs and Large Language Models

In client-AI expert collaborations, the planning stage of AI application development begins from the client; a client outlines their needs and expectations while assessing available resources (pre-collaboration planning). Despite the importance of pre-collaboration plans for discussions with AI experts for iteration a…

DIS '245th+ AuthorHuman-LLM Collaboration +1

Co-Creating Question-and-Answer Style Articles with Large Language Models for Research Promotion

Research promotion enables researchers to share advanced knowledge with pertinent academic communities. The question-and-answer (QA) style articles are effective for researchers to promote their research by enabling readers to understand research on complex subjects. Recent advances in large language models (LLMs) hav…

DIS '242nd AuthorHuman-LLM Collaboration +1

AINeedsPlanner: A Workbook to Support Effective Collaboration Between AI Experts and Clients

Clients often partner with AI experts to develop AI applications tailored to their needs. In these partnerships, careful planning and clear communication are critical, as inaccurate or incomplete specifications can result in misaligned model characteristics, expensive reworks, and potential friction between collaborat…

CHI '243rd AuthorHonorable MentionHuman-LLM Collaboration +1

Teach AI How to Code: Using Large Language Models as Teachable Agents for Programming Education

This work investigates large language models (LLMs) as teachable agents for learning by teaching (LBT). LBT with teachable agents helps learners identify knowledge gaps and discover new knowledge. However, teachable agents require expensive programming of subject-specific knowledge. While LLMs as teachable agents can…

CHI '222nd AuthorProgramming Education & Computational Thinking +1

AlgoSolve: Supporting Subgoal Learning in Algorithmic Problem-Solving with Learnersourced Microtasks

Designing solution plans before writing code is critical for successful algorithmic problem-solving. Novices, however, often plan on-the-fly during implementation, resulting in unsuccessful problem-solving due to lack of mental organization of the solution. Research shows that subgoal learning helps learners develop m…

CSCW '204th AuthorCrowds and Collaboration

ProtoChat: Supporting the Conversation Design Process with Crowd Feedback

Similar to a design process for designing graphical user interfaces, conversation designers often apply an iterative design process by defining a conversation flow, testing with users, reviewing user data, and improving the design. While it is possible to iterate on conversation design with existing chatbot prototypin…

CHI '181st AuthorOnline Learning & MOOC Platforms +1

Understanding the Effect of In-Video Prompting on Learners and Instructors

Online instructional videos are ubiquitous, but it is difficult for instructors to gauge learners' experience and their level of comprehension or confusion regarding the lecture video. Moreover, learners watching the videos may become disengaged or fail to reflect and construct their own understanding. This paper expl…

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