Intelligent Coaching Agents for Enhancing Helping Behavior in Human Teamwork

Open Access
Author:
Chen, Cong
Graduate Program:
Information Sciences and Technology
Degree:
Doctor of Philosophy
Document Type:
Dissertation
Date of Defense:
August 04, 2006
Committee Members:
  • John Yen, Committee Chair
  • John Millar Carroll, Committee Member
  • Brian K Smith, Committee Member
  • Tracy Mullen, Committee Member
  • Guohong Cao, Committee Member
Keywords:
  • Feedback Generatioin
  • Diagnosis
  • Agent-based Coaching
  • Performance Assessment
  • Intelligent Training
  • Teamwork
Abstract:
Teamwork is the joint work of individuals who act together productively. Recent technological advancement, global competition and world events made teamwork vitally important to the success of many organizations in both military and civilian sectors. Team training is arguably one of the most intensively studied topics for cognitive science researchers in the past decades, yet there are few effective software tools that automate team performance assessment and coaching. The goal of this research is to develop an intelligent training framework where software agents are used to automate team performance assessment and coaching, with a focus on helping behavior. One of the design challenges in coaching for team training is that the performance of a team is affected by multiple factors, which include the quality of the team¡¯s plan and each individual¡¯s execution of the plan. To address this difficulty, our framework uses a two-phase training protocol that provides coaching for two phases: a mission planning phase and a mission execution phase. We adopt two user modeling approaches (overlay and error taxonomy) in Intelligent Tutoring System (ITS) for the two phases, according to different complexity involved in modeling expert behavior. In the planning phase, intelligent coaching feedback is generated based on an expert model for resource allocation. In the execution phase, coaching feedback is generated based on error taxonomy to assess team¡¯s execution performance of their planned activities. Due to the broad scope of team training, this research stresses one important dimension of teamwork¡ªthe helping behavior among team members, in case of an unbalanced workload and resource distribution. Coaching feedback is provided in a debriefing session at the end of each mission execution with a goal of improving trainee performance during the next mission. We have implemented the framework within a team-based agent architecture and applied it to train helping behaviors for a simulated command and control (C2) task. To evaluate the effectiveness of the agent-based team training approach, we designed and conducted a human subject experiment that applied the agent-based two-phase training protocol and provided teams in the experiment group with feedback generated by the coaching agents. Results have suggested that the coaching agents have a positive impact on trainees¡¯ learning of how to effectively helping each other to achieve mission success in time-critical and complex task domains.