3 citations · 7 across the 9 of their papers we have counts for
9 papers
Analyzing Middle School Students' Dialogue and Behaviors during Collaborative AI Chatbot Development Using Ordered Network Analysis
Shan Zhang, Andres Felipe Zambrano, Xiaoyi Tian +5
As Artificial Intelligence (AI) education has become a key component of K-12 curricula, activities such as designing and developing conversational agents are increasingly used as i…
Do Role-Playing Agents Practice What They Preach? Belief-Behavior Consistency in LLM-Based Simulations of Human Trust
Amogh Mannekote, Adam Davies, Guohao Li +4
As LLMs are increasingly studied as role-playing agents to generate synthetic data for human behavioral research, ensuring that their outputs remain coherent with their assigned ro…
Combining Log Data and Collaborative Dialogue Features to Predict Project Quality in Middle School AI Education
Conrad Borchers, Xiaoyi Tian, Kristy Elizabeth Boyer +1
Project-based learning plays a crucial role in computing education. However, its open-ended nature makes tracking project development and assessing success challenging. We investig…
Can LLMs Reliably Simulate Human Learner Actions? A Simulation Authoring Framework for Open-Ended Learning Environments
Amogh Mannekote, Adam Davies, Jina Kang +1
Simulating learner actions helps stress-test open-ended interactive learning environments and prototype new adaptations before deployment. While recent studies show the promise of…
Making Task-Oriented Dialogue Datasets More Natural by Synthetically Generating Indirect User Requests
Amogh Mannekote, Jinseok Nam, Ziming Li +3
Indirect User Requests (IURs), such as "It's cold in here" instead of "Could you please increase the temperature?" are common in human-human task-oriented dialogue and require worl…
Can Similarity-Based Domain-Ordering Reduce Catastrophic Forgetting for Intent Recognition?
Amogh Mannekote, Xiaoyi Tian, Kristy Elizabeth Boyer +1
Task-oriented dialogue systems are expected to handle a constantly expanding set of intents and domains even after they have been deployed to support more and more functionalities.…
Automatically Detecting Confusion and Conflict During Collaborative Learning Using Linguistic, Prosodic, and Facial Cues
Yingbo Ma, Yukyeong Song, Mehmet Celepkolu +4
During collaborative learning, confusion and conflict emerge naturally. However, persistent confusion or conflict have the potential to generate frustration and significantly imped…
A Review of Digital Learning Environments for Teaching Natural Language Processing in K-12 Education
Xiaoyi Tian, Kristy Elizabeth Boyer
Natural Language Processing (NLP) plays a significant role in our daily lives and has become an essential part of Artificial Intelligence (AI) education in K-12. As children grow u…
Agreement Tracking for Multi-Issue Negotiation Dialogues
Amogh Mannekote, Bonnie J. Dorr, Kristy Elizabeth Boyer
Automated negotiation support systems aim to help human negotiators reach more favorable outcomes in multi-issue negotiations (e.g., an employer and a candidate negotiating over is…