These are the papers we talked:
Charisma and Learning: Designing Charismatic Behaviors for Virtual Human Tutors – Ning Wang
State of the art: Sequence-to-sequence modeling – Kumar Abhinav
Data-Driven Approaches to Item Difficulty Prediction — James P. Bywater
Affect-Targeted Interviews for Understanding Student Frustration – Ryan S. Baker
Affective Teacher Tools: Affective Class Report Card and Dashboard – Ankit Gupta
Evaluating Critical Reinforcement Learning Framework in the Field – Song Ju
Predicting Co-occurring Emotions from Eye-Tracking and Interaction Data in MetaTutor – Sébastien Lallé
The Challenge of Noisy Classrooms: Speaker Detection During Elementary Students’ Collaborative Dialogue – Yingbo Ma,
Deep Performance Factors Analysis for Knowledge Tracing – Shi Pu
Towards Sharing Student Models Across Learning Systems – Ryan S. Baker
Interactive Personas: Towards the Dynamic Assessment of Student Motivation within ITS – Ishrat Ahmed
Artificial Intelligence Ethics Guidelines for K-12 Education: A Review of the Global Landscape – Cathy Adams
Personal Vocabulary Recommendation to Support Real Life Needs – Victoria Abou-Khalil
Early Prediction of Children’s Disengagement in a Tablet Tutor Using Visual Features¥ – Bikram Boote
Designing Intelligent Systems to Support Medical Diagnostic Reasoning Using Process Data – Elizabeth B. Cloude,
Identifying Struggling Students by Comparing Online Tutor Clickstreams – Ethan Prihar
Using AI to Promote Equitable Classroom Discussions: The TalkMoves Application – Abhijit Suresh
Modeling Frustration Trajectories and Problem-Solving Behaviors in Adaptive Learning Environments for Introductory Computer Science – Xiaoyi Tian
Using Adaptive Experiments to Rapidly Help Students – Angela Zavaleta-Bernuy
This is the conference I strongly recommend check about AI in Education: