1 Intelligent Tutoring Systems: Architecture and Characteristics Indira Padayachee University of Natal, Durban, Information Systems & Technology, School of Accounting & Finance padayacheei@nu.ac.za Abstract This paper provides a close examination of specific intelligent tutoring system (ITS) architectures spanning the period 1988-1999. ITSs are classified into three categories, namely traditional three-model, classical four-model and new-generation architectures for the purposes of this study. Similarities and differences between architectures of the same category, and between different category architectures are discussed. The study depicts the influence of application domains, learning and instruction trends, as well as software development advances on ITS architecture and behaviour. This research aims to examine various ITS architectures and its actual behaviour to establish a set of generic characteristics and behaviour. These characteristics are useful for comparing and evaluating existing ITSs, and can guide the design of new ITSs. Key Words: Intelligent tutoring system, Artificial intelligence, Intelligent Tutoring System architectures, Intelligent tutoring system characteristics. Computing Review Categories: K.3.1, K.3.2 1. Introduction Intelligent Tutoring Systems (ITSs) are instructional systems that use artificial intelligence (AI) techniques in computer programs to facilitate learning. These systems are based on cognitive psychology as an underlying theory of learning, which deals mainly with issues such as knowledge representation and organisation within the human memory as well as the nature of human errors [Shute & Psotka, 1996]. The intelligent tutoring systems adopt a mixed-initiative teaching dialogue, which allows the system to initiate interactions with the learner, as well as interpret and respond meaningfully to learner-initiated interactions [Garito, 1991; Beverly Park Woolf, University of Massachusetts, 1998]. There exists a number of research papers that provide detailed descriptions of intelligent tutoring system architectures developed for specific application domains. These papers are useful in that they assist in understanding the functionality and operability mechanics of ITSs, and stimulate further development. However, there has been limited effort in examining both system architecture and behaviour, to ascertain common characteristics of ITSs. This research aims to examine various ITS architectures and its actual behaviour to establish a set of generic characteristics and behaviour. These characteristics are useful for comparing and evaluating existing ITSs, and can guide the development of new systems. The study also considers factors that have influenced ITS architectures, and discusses the similarities and differences between ITS architectures. 2. Intelligent Tutoring System architectures This section examines selected intelligent tutoring systems spanning the period 1988-1999, and classifies them into three categories, namely three-model, four-model and new-generation architectures. The ITS architectures have in the main been named after their respective designers for easy referencing. 2.1 Three-model architectures for ITSs A three-model architecture typically comprises three major building blocks or components, namely the systems domain expertise, student knowledge and skill, and tutoring expertise. Two examples representing the three-model architecture are discussed below.