2 citations · 5 across the 6 of their papers we have counts for
7 papers
When Does AI Augment Work? A Workflow-Level Framework for Human-Agent Collaboration
AI Collaboration, Jiaying Wu, Caleb Ziems +19
We aim to characterise the value of artificial intelligence in the workplace. Current studies largely measure this value in terms of the current automation capabilities and public…
Bridging Talk and Thought: Understanding Dialogue Dynamics Across Collaborative Problem-Solving Contexts
Zhengyuan Liu, Stella Xin Yin, Min-Yen Kan +1
We present a conceptual framework for analyzing dialogue in collaborative problem-solving contexts, with an emphasis on the emerging dynamics of human-AI and multi-agent collaborat…
The Imperfect Learner: Incorporating Developmental Trajectories in Memory-based Student Simulation
Zhengyuan Liu, Stella Xin Yin, Bryan Chen Zhengyu Tan +5
User simulation is important for developing and evaluating human-centered AI, yet current student simulation in educational applications has significant limitations. Existing appro…
COGENT: A Curriculum-oriented Framework for Generating Grade-appropriate Educational Content
Zhengyuan Liu, Stella Xin Yin, Dion Hoe-Lian Goh +1
While Generative AI has demonstrated strong potential and versatility in content generation, its application to educational contexts presents several challenges. Models often fail…
SingaKids: A Multilingual Multimodal Dialogic Tutor for Language Learning
Zhengyuan Liu, Geyu Lin, Hui Li Tan +8
The integration of generative artificial intelligence into educational applications has enhanced personalized and interactive learning experiences, and it shows strong potential to…
Scaffolding Language Learning via Multi-modal Tutoring Systems with Pedagogical Instructions
Zhengyuan Liu, Stella Xin Yin, Carolyn Lee +1
Intelligent tutoring systems (ITSs) that imitate human tutors and aim to provide immediate and customized instructions or feedback to learners have shown their effectiveness in edu…
Personality-aware Student Simulation for Conversational Intelligent Tutoring Systems
Zhengyuan Liu, Stella Xin Yin, Geyu Lin +1
Intelligent Tutoring Systems (ITSs) can provide personalized and self-paced learning experience. The emergence of large language models (LLMs) further enables better human-machine…