ConceptGrid provides a template-style approach to check natural language responses by students using a model-tracing style intelligent tutoring system. The tutor-author creates, using a web-based authoring system, a latticestyle structure that contains the set of required concepts that need to be in a student response. The author can also create just-in-time feedback based on the concepts present or absent in the student's response. ConceptGrid is integrated within the xPST authoring tool and was tested in two experiments, both of which show the efficacy of the technique to check student answers. The first study tested the tutor's effectiveness overall in the domain of statistics. The second study investigated ConceptGrid's use by non-programmers and non-cognitive scientists. ConceptGrid extends existing capabilities for authoring of intelligent tutors by using this template-based approach for checking sentence-length natural language input.

We describe an evaluation of two intelligent tutoring system authoring tool paradigms, graphical user interface-based and text-based by taking the examples of CTAT and xPST respectively, in two domains, statistics and geometry. We conducted a study with 16 tutor-authors divided into 2 groups (programmers and non-programmers). Our results showed that the GUI-based approach, aided by the visualization of problem-solving strategies, provides a much lower bar for entry when compared to the text-based approach. However, the difference in tutor-authoring time between the two approaches decreases as the tutor-authors gain experience using the respective authoring tools. We also do a theoretical comparison of the two paradigms by applying the cognitive dimensions framework. This research contributes design guidance for architects of tutor authoring systems.

Using natural language as a way for students to interact with an ITS has many advantages. However, creating the intelligence with which the tutor evaluates a student’s natural language input is challenging. We describe a system, ConceptGrid, that allows non-programmers to create the instruction for checking natural language input. Three tutor authors used the system to develop answer templates for conceptual-based questions in statistics. Results indicate ConceptGrid is a viable system for non-programmers to use to allow students to use natural language to interact with a tutor.

An intelligent tutoring system (ITS) is a software application that tries to replicate the performance of a human tutor by supporting the theory of “learning by doing” and providing customized instruction to a student while performing a task within a problem domain such as mathematics, medical diagnosis, or even game play. ITSs have been shown to improve the performance of a student in wide range of domains. Despite their benefits, ITSs have not seen widespread use due to the complexity involved in their development. Developing an ITS from scratch requires expertise in several fields including computer science, cognitive psychology and artificial intelligence. In order to decrease the skill threshold required to build ITSs, several authoring tools have been developed. In this thesis, I document several contributions to the field of intelligent tutoring in the form of extensions to an existing ITS authoring tool, research studies on authoring tool paradigms and the design of authoring tools for non-programmers in two complex domains – natural language processing and 3D game environments. The Extensible Problem Specific Tutor (xPST) is an authoring tool that helps rapidly develop model-tracing like tutors on existing interfaces such as webpages. xPST‟s language was made more expressive with the introduction of new checktypes required for answer checking in problems belonging to domains such as geometry and statistics. A web-based authoring (WAT) tool was developed for the purpose of tutor management and deployment and to promote non-programmer authoring of ITSs. The WAT was used in a comparison study between two authoring tool paradigms – GUI based and text based, in two different problem domains – statistics and geometry.

We describe a domain-independent authoring tool, ConceptGrid, that helps non-programmers develop intelligent tutoring systems (ITSs) that perform natural language processing. The approach involves the use of a lattice-style table-driven interface to build templates that describe a set of required concepts that are meant to be a part of a student’s response to a question, and a set of incorrect concepts that reflect incorrect understanding by the student. The tool also helps provide customized just-in-time feedback based on the concepts present or absent in the student’s response. This tool has been integrated and tested with a browser-based ITS authoring tool called xPST.

We describe the design of an authoring tool that is intended to help non-programmers develop game-based intelligent tutoring systems. The tutorbuilding approach involves the creation of states, both atomic and complex, that help model physical and cognitive states respectively. The tutor-author specifies the parameters associated with each entity in the scenario for each state. The resulting tutor dynamically updates the learner model and automatically assesses the performance of the learner and provides customized feedback.

Authoring tools enable the more rapid creation of intelligent tutoring systems. Such tools are essential for tutors to become more widespread. In this study we evaluate WebxPST, a browser-based authoring system that enables non-programmers to create model-tracing-like intelligent tutors. Five authors, two course instructors and three undergraduates, created 74 problems suitable for use in an undergraduate statistics curriculum. A subset of these problems was deployed in a classroom. These authors quickly mastered the authoring interface showing the feasibility of the tool.

We describe how the Extensible Problem Specific Tutor (xPST), an open source engine for intelligent tutoring systems, has been adapted to provide training within game-engine based synthetic environments. We have designed a web-based tutor-authoring tool and have conducted a study that shows that xPST can be used by authors with minimal programming experience to create tutors for 3D game environments. As a proof of concept, we also describe how xPST has been extended to provide support to tutor based on real-time physiological data. We suggest that xPST could be a key component of the future of real-time personalized and adaptive live, virtual, and constructive training.