Intelligent Tutoring Systems: A Tutorial Survey (original) (raw)
Related papers
Modeling of Tutoring Processes in Intelligent Tutoring Systems
Springer eBooks, 2004
The combination Computer Based Training systems with Artificial Intelligence and Cognitive Science has led to the development of Intelligent Tutoring Systems nearly 30 years ago. A common agreement has been reached about the constituents of an Intelligent Tutoring System (ITS). Nonetheless, the interpretation of the role of each component in the ITS is still heterogeneous. Together with the absence of formal methods in ITS, this leads to the situation, that the components of ITSs are strongly domain dependent and not reusable. The situation is analyzed for case-based ITS, i.e. ITS based on a narrative story line. A formal model of the tutoring process is introduced into the ITS architecture. The model is based on the idea to support the training of two cognitive processes, i.e. the process of diagnostic reasoning, and the process of general knowledge application. The integration of the tutoring process model as the central component in the ITS has led to a homogenization of the architecture. Based on the new architecture, the ITS Docs 'n Drugs has been realized.
Towards a methodology for the design of intelligent tutoring systems
2006
The present article proposes a methodology for the construction of intelligent tutoring systems that can be applied to any case that implies the design of a system intended for training advanced engineering students in the operation and maintenance of mechanisms. The article offers premises for the design of the modules of knowledge domain, student and tutor, and describes control strategies implemented as metarules .
Innovative modeling techniques on intelligent tutoring systems
2000
This chapter describes three modeling techniques that have recently started to attract the attention of researchers and developers in the domain of intelligent tutoring systems (ITSs). These techniques are: hierarchical modeling, interoperable and reusable software components, and ontologies. All three of them have been used in developing a model of ITSs called GET-BITS (GEneric Tools for Building ITSs). The GET-BITS model has been used throughout the chapter in order to illustrate the techniques. The major goal of the chapter is to show how these three techniques can be used to make the internal organization of ITSs more natural, more flexible, and more robust, to enhance their design, and to improve their performance. Important modules of any intelligent tutoring system, like domain knowledge, pedagogical knowledge, student model, and explanation strategies, are discussed extensively in the context of the three modeling techniques and the GET-BITS model. Experience with using GET-BITS as the basis for building practical applications shows how the processes of computer-based tutoring and learning based on the GET-BITS model are much closer to human-based instruction. From the design perspective, major advantages of using hierarchical modeling, software components, and ontologies in developing practical ITSs include enhanced modularity, easy extensions, and important steps towards knowledge sharing and reuse.
ii This book is the second in a planned series of books that examine key topics (e.g., learner modeling, instructional strategies, authoring, domain modeling, learning effect, and team tutoring) in intelligent tutoring system (ITS) design through the lens of the Generalized Intelligent Framework for Tutoring (GIFT;, a modular, service-oriented architecture created to develop standards for authoring, managing instruction, and analyzing the effect of ITS technologies.
146 Design Perspectives of Intelligent Tutoring
Intelligent Tutoring Systems (ITSs) have come a long way, since their inception decades ago. Its prospects have revolutionized e-Learning, curriculum instructions and workplace training. The field has witnessed significant developments towards many possible directions and as a result, numerous ITSs have been developed to date. Recent tutoring systems have moved from research labs to classrooms [1]. However, it is still a costly affair and lacks established standards. Human learning phenomena are very complex and itself is an ongoing research activity right through the history of mankind. This paper attempts to identify some key instructional/learning aspects that must be addressed while designing a successful tutoring system. In this regard, we have reviewed some of the well-known ITS design principles and report an analysis of their success in modelling the learning/instructional ingredients.
ENHANCING THE TUTOR MODEL OF INTELLIGENT TUTORING SYSTEMS
American Academic & Scholarly Research Journal ( …, 2012
Intelligent Tutoring Systems are systems that have general features that can communicate with a student, define the student knowledge and abilities, and can change the teaching strategy. Teaching strategies employed in intelligent tutoring systems, as usual, are not based on old and recent developments in pedagogical science and ignoring both general principles of teaching and learning theory and many classical teaching methods suggested by practicing teachers. This paper describes the use of traditional theories of teaching and learning, in terms of enhancing the tutor model of intelligent tutoring systems.
A Comparative Literature Review of Intelligent Tutoring Systems from 1992-2015
2017
A Comparative Literature Review of Intelligent Tutoring Systems from 1990-2015 Brice Robert Colby Department of Instructional Psychology and Technology, BYU Master of Science This paper sought to accomplish three goals. First, it provided a systematic, comparative review of several intelligent tutoring systems (ITS). Second, it summarized problems and solutions presented and solved by developers of ITS by consolidating the knowledge of the field into a single review. Third, it provided a unified language from which ITS can be reviewed and understood in the same context. The findings of this review centered on the 5-Component Framework. The first component, the domain model, showed that most ITS are focused on science, technology, and mathematics. Within these fields, ITS generally have mastery learning as the desired level of understanding. The second component, the tutor model, showed that constructivism is the theoretical strategy that informs most ITS. The tutoring tactics employ...
Survey of Intelligent Tutoring Systems Up To the End of 2016
2019
The main goals of Intelligent Tutoring Systems (ITS) are: providing highly developed instructional guidance on a one-toone foundation that is improved than what is attained with traditional computer aided instruction and is analogous to that of a decent human tutor; and developing and testing models of intelligent processes associated with instruction. ITS is a subfield of artificial intelligence. ITS consists of four interacting components: the student model which embodies the student's present knowledge state, the pedagogical module which comprises appropriate instructional measures which are depending on the content of the student model, the knowledge model which contains the domain knowledge, and the user interface model which permits an effective dialog among ITS and the user. Usually, the knowledge model is the central part in the instructional process but there is a diversity of approaches that also put the stress on the other components. In this paper we have surveyed 55...