Intelligent tutoring systems for systems engineering methodologies

The general goal is to provide the technology required to build systems that can provide intelligent tutoring in IDEF (Integrated Computer Aided Manufacturing Definition Method) modeling. The following subject areas are covered: intelligent tutoring systems for systems analysis methodologies; IDEF tutor architecture and components; developing cognitive skills for IDEF modeling; experimental software; and PC based prototype

Developing Computer-Based Training using the Requirements Engineering Techniques

There are several Requirements Engineering (RE) techniques have been developed to assist large projects within the RE process. However, it is still not clear if these frameworks will adequately to be useful in developing e-Learning software. The purpose of this paper is to show that the RE techniques can also fit for developing e-Learning software such as Computer-Based Training (CBT). In this context, a case study at the Food and Beverages (F&B) Division, Radisson SAS Hotel in Hamburg was taken in order to apply some of the RE techniques. The need to have a CBT for new staff at the division, led the research to focus on identifying the problem and user needs. Using the RE techniques such as Documentation Study, Interviewing, Requirements Workshop, Observation, and Prototyping is becoming a solution that helps developer in developing the CBT as needed by user afterward. This paper presents the result of using the RE methods in developing the CBT. The programming skills in developing the CBT will not be discussed in this paper. Keywords: Computer-Based Training, e-Learning software, Requirements Engineerin

Optimising ITS behaviour with Bayesian networks and decision theory

We propose and demonstrate a methodology for building tractable normative intelligent tutoring systems (ITSs). A normative ITS uses a Bayesian network for long-term student modelling and decision theory to select the next tutorial action. Because normative theories are a general framework for rational behaviour, they can be used to both define and apply learning theories in a rational, and therefore optimal, way. This contrasts to the more traditional approach of using an ad-hoc scheme to implement the learning theory. A key step of the methodology is the induction and the continual adaptation of the Bayesian network student model from student performance data, a step that is distinct from other recent Bayesian net approaches in which the network structure and probabilities are either chosen beforehand by an expert, or by efficiency considerations. The methodology is demonstrated by a description and evaluation of CAPIT, a normative constraint-based tutor for English capitalisation and punctuation. Our evaluation results show that a class using the full normative version of CAPIT learned the domain rules at a faster rate than the class that used a non-normative version of the same system

OFMTutor: An operator function model intelligent tutoring system

The design, implementation, and evaluation of an Operator Function Model intelligent tutoring system (OFMTutor) is presented. OFMTutor is intended to provide intelligent tutoring in the context of complex dynamic systems for which an operator function model (OFM) can be constructed. The human operator's role in such complex, dynamic, and highly automated systems is that of a supervisory controller whose primary responsibilities are routine monitoring and fine-tuning of system parameters and occasional compensation for system abnormalities. The automated systems must support the human operator. One potentially useful form of support is the use of intelligent tutoring systems to teach the operator about the system and how to function within that system. Previous research on intelligent tutoring systems (ITS) is considered. The proposed design for OFMTutor is presented, and an experimental evaluation is described

Generating socially appropriate tutorial dialog

Analysis of student-tutor coaching dialogs suggest that good human tutors attend to and attempt to influence the motivational state of learners. Moreover, they are sensitive to the social face of the learner, and seek to mitigate the potential face threat of their comments. This paper describes a dialog generator for pedagogical agents that takes motivation and face threat factors into account. This enables the agent to interact with learners in a socially appropriate fashion, and foster intrinsic motivation on the part of the learner, which in turn may lead to more positive learner affective states

Multimodal Interaction in a Haptic Environment

In this paper we investigate the introduction of haptics in a multimodal tutoring environment. In this environment a haptic device is used to control a virtual piece of sterile cotton and a virtual injection needle. Speech input and output is provided to interact with a virtual tutor, available as a talking head, and a virtual patient. We introduce the haptic tasks and how different agents in the multi-agent system are made responsible for them. Notes are provided about the way we introduce an affective model in the tutor agent