Automated Socratic Tutors for High-Level Command Skills

Abstract

Under stress, human decision-makers revert to their best-practiced habits. This includes military commanders who may fail to act effectively under pressure for lack of sufficient practice. The US Army Research Institute (ARI) developed a training methodology emphasizing repeated exposure to small challenging vignettes enabling drill on command decision-making. Rather than role-play to a simulated conclusion, mentors focus on analyses and dialogues that explore reasoning and rationale. Adoption of this methodology in courses at Forts Leavenworth and Knox is helping to validate this approach to honing command skills. However, intense practice with human mentors is problematic as there are generally too few expert mentors available. This paper describes an ongoing Small Business Innovative Research (SBIR) project to develop automated intelligent tutors to fill the role of expert mentors. This project is developing a novel capability to understand, critique, and discuss proposed courses of action in a Socratic mode, guiding the student as an expert would. The approach emphasizes multi-modal interaction (e.g., language and graphics), models of expert human tutors, and development of authoring tools to reduce training system costs.The paper presents data from analyses of expert mentor and student dialogues during "tactical decision games." It then describes how this data is used to develop and assess the project's intelligent tutor. Additional preliminary data from early informal formative evaluation of the Phase I prototype system, and initial student feedback on some Phase II refinements is also reported.Ongoing complementary efforts include a related Phase II SBIR with a different ITS approach, and a computerbased program developed by ARI that human instructors are using in the Armor Captains Course at Fort Knox's University of Mounted Warfare. Author's BiographiesDr. Eric A. Domeshek is an Artificial Intelligence (AI) Project Manager at Stottler Henke Associates, Inc. He received his Ph.D. in Computer Science from Yale University, where his work focused on cognitive modeling and technology, most especially on development of Case Based Reasoning (CBR). While working as Research Faculty at the Georgia Institute of Technology, he helped launch the EduTech institute, and became involved in educational applications of AI and CBR. He continued to work on educational and training technology while on faculty at Northwestern University's Institute for the Learning Sciences. For the last three years, Dr. Domeshek has conceived and managed a variety of Intelligent Tutoring System (ITS) projects at Stottler Henke. His main effort currently focuses on dialogue-oriented tutors such as the ComMentor system described here. Mr. Elias Holman is an Report Documentation PageForm Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and revi...

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“…Domeshek et al (2002) conceptualized the Socratic method as follows: "Socratic instruction is a kind of teaching interaction typically applied in high-level professional education (e.g., law and business) and most often characterized by its external form: the teacher asks a lot of questions, and the student answers." Based on this notion of the Socratic method, Domeshek et al (2004) developed ComMentor, an automated Socratic tutoring system, for command skills for high-level professional education such as law and business. This system is claimed to be able to guide the student in a Socratic mode as an expert would: the teacher asks questions and the student answers.…”

“…The sequence of the questions is intended to help the student reconstruct the logic of expert situation analysis and decision-making. Domeshek et al (2004) described four characteristics of a typical Socratic session: (1) a thoughtprovoking problem, (2) a student's attempt to provide solutions, (3) the instructor's repeated exploration and challenging of the student's solutions, and (4) incremental justification, elaboration, refinement, and revision of both the student's understanding of the situation under discussion and their proposed solution.…”

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“…The level of ambition and proven capability for ITSs has also been increasing, and research is pushing practical ITS tools from the level of straightforward procedural tasks (e.g. Munro & Pizzini, 1995) or closed-world formal reasoning tasks (Anderson, et al, 1985) to more open-ended analysis and decision tasks such as tactical decision-making (Domeshek, Holman, & Ross, 2002).…”