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Copyright © 2019 for the individual papers by the papers' authors. Copyright © 2019 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License

Attribution 4.0 International (CC BY 4.0).

Artificial Intelligence in Education 2019

Chicago, IL, USA June 29, 2019

Workshop Proceedings:

Approaches and Challenges in Team Tutoring

Workshop Co-Chairs:

Anne M. Sinatra, Ph.D.

U.S. Army Combat Capabilities Development Command (CCDC) – Soldier Center – Simulation & Training Technology Center (STTC)

Jeanine A. DeFalco, Ph.D.

Oak Ridge Associated Universities & U.S. Army CCDC Soldier Center STTC

Workshop Program Committee:

Benjamin Goldberg, Ph.D.

U.S. Army CCDC Soldier Center STTC

Art Graesser, Ph.D.

University of Memphis

Xiangen Hu, Ph.D.

University of Memphis

Rodney Long

U.S. Army CCDC Soldier Center STTC

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Preface

The Approaches and Challenges in Team Tutoring Workshop was conducted in conjunction with the 20th Artificial Intelligence in Education Conference (AIED) in Chicago, IL, in June 2019. This workshop focused on different approaches and challenges of team tutoring within intelligent tutoring systems (ITSs). The workshop included many examples of team tutoring in action in different domains, as well as lessons learned from the development of the team tutors. The goals of this workshop included identifying challenges and approaches in team tutoring. One representative element of challenges in team tutoring included how they were overcome by our presenters, findings that can assist other researchers in the future. The workshop concluded with a discussion of the current gaps in the team tutoring domain, commonalities in the challenges that were identified, as well as steps forward for team tutoring. The challenges and approaches identified are captured in the papers included in this proceedings.

June 2019 Anne M. Sinatra and Jeanine A. DeFalco

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Table of Contents

Introduction to Approaches and Challenges in Team Tutoring 1-4

Anne M. Sinatra, & Jeanine A. DeFalco

Team Data Analysis Using FATE: Framework for Automated Team 5-14 Evaluation

Alec Ostrander, Stephen Gilbert & Michael Dorneich

Sensing Team Interaction to Enhance Learning and Performance during 15-29 Adaptive Instruction

Robert Sottilare & Ross Hoehn

Toward Computational Models of Team Effectiveness with Natural Language 30-39 Processing

Randall Spain, Michael Geden, Wookhee Min, Bradford Mott, and James Lester

Intelligent After-Action Review Support Tools for Large Team Training 40-49

Sowmya Ramachandran & Randy Jensen

Team Tutoring Automated Content Discovery and Learning Objective 50-58 Alignment

Benjamin Bell, Keith Brawner, Elaine Kelsey, & Debbie Brown

Towards Dynamic Intelligent Support for Collaborative Problem Solving 59-65 Sidney D’Mello, Angela E.B. Stewart, Mary Jean Amon, Chen Sun, Nicholas Duran,

& Valerie Shute

An Appraisal of a Collaboration-Metric Model based on Text Discourse 66-76

Adetunji Adeniran, Judith Mastho, & Nigel Beacham

The Effects of Rejection Sensitivity on Confusion Regulation during Learning 77-86 in Multiagent Intelligent Tutoring System Environments

Zhou Long, Dehong Luo, Hongli Gao, & Xiangen Hu

Simulating Team Tutoring in Multiagent Environments 87-96

Max Johnson, Ning Wang, & David V. Pynadath

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