Bringing Authoring Tools for Intelligent Tutoring Systems and Serious Games Closer Together: Integrating GIFT with the Unity Game Engine

In an effort to bring intelligent tutoring system (ITS) authoring tools closer to content authoring tools, the authors are working to integrate GIFT with the Unity game engine and editor. The paper begins by describing challenges faced by modern intelligent tutors and the motivation behind the integration effort, with special consideration given to how this work will better meet the needs of future serious games. The next three sections expand on these major hurdles more thoroughly, followed by proposed design enhancements that would allow GIFT to overcome these issues. Finally, an overview is given of the authors’ current progress towards implementing the proposed design. The key contribution of this work is an abstraction of the interface between intelligent tutoring systems and serious games, thus enabling ITS authors to implement more complex training behaviors

Invisible Intelligent Authoring Tools

Imagine that you, an expert in technology and in the learning sciences, have decided to help your colleagues pass on their expertise to others by helping them build intelligent tutors systems (ITSs). Your expert colleagues can be in only one place at a time, and an ITS would multiply the impact of their expertise better than an online video, since an ITS can personalize the instruction. ITSs have demonstrated significant learning gains in a variety of disciplines, after all (Anderson, 1989; Koedinger, 1997; Lesgold, Lajoie, Bunzo & Eggan, 1992; Ritter, Kulikowich, Lei, McGuire & Morgan, 2007; VanLehn, et al., 2005), so this approach makes sense

Characteristics of a Multi-User Tutoring Architecture

Intelligent tutor systems have been quite successful in instruction of individuals (Koedinger, Anderson, Hadley, & Mark, 1997; Ritter, Kulikowich, Lei, McGuire, & Morgan, 2007; Vanlehn, et al., 2005), but multiple challenges exist when attempting to tutor a team. Sottilare, Holden, Brawner, and Goldberg (2011) describe some of the architectural challenges of team tutoring at a high level in terms of functional requirements. In this paper we describe specific challenges in terms of implementing a team architecture within the Generalized Intelligent Framework for Tutoring (GIFT), including simultaneous startup and synchronization with distributed team members, maintaining state of multiple users, and timing feedback for teams and individuals appropriately

Lowering the Bar for Creating Model-Tracing Intelligent Tutoring Systems

The main goal of the work presented here is to allow for the broader dissemination of intelligent tutoring technology. To accomplish this goal, we have two clear objectives. First, we want to allow different types of people to author model-tracing intelligent tutoring systems (ITSs) than can now do so. Second, we want to enable an author to create a tutor for software that was not initially designed with an ITS in mind. Accomplishing these two objectives should increase the number of such ITSs that are produced. We have created the first iteration of an authoring system that addresses both objectives. Non-cognitive scientists and non-programmers have used the system to create a tutor, and the system can interface with third-party software that was not originally designed with the ITS