Intelligent tutoring system

Abstract: Cognitive psychology, artificial intelligence, and computer technology have advanced to the point where it is feasible to build computer systems that are as effective as intelligent human tutors Computer tutors based on a set of pedagogical principles derived from the ACT theory of cognition have been developed for teaching students to do proofs in geometry and to write computer programs in the language LISP

Abstract: This paper consists of an in-depth summary and analysis of the research and development state of the art for intelligent tutoring system (ITS) authoring systems. A seven-part categorization of two dozen authoring systems is given, followed by a characterization of the authoring tools and the types of ITSs that are built for each category. An overview of the knowledge acquisition and authoring techniques used in these systems is given. A characterization of the design tradeoffs involved in building an ITS authoring system is given. Next the pragmatic questions of real use, productivity findings, and evaluation are discussed. Finally, I summarize the major unknowns and bottlenecks to having widespread use of ITS authoring tools. (http://aied.inf.ed.ac.uk/members99/archive/vol_10/murray/full.html)

Abstract: Contents: S.J. Derry, S.P. Lajoie, A Middle Camp for (Un)Intelligent Instructional Computing: An Introduction. Part I:Model Builders. K.R. Koedinger, J.R. Anderson, Reifying Implicit Planning in Geometry: Guidelines for Model-Based Intelligent Tutoring System Design. V.J. Shute, A Comparison of Learning Environments: All That Glitters... M.R. Lepper, M. Woolverton, D.L. Mumme, J-L. Gurtner, Motivational Techniques of Expert Human Tutors: Lessons for the Design of Computer-Based Tutors. S.J. Derry, L.W. Hawkes, Local Cognitive Modeling of Problem-Solving Behavior: An Application of Fuzzy Theory. Part II:Non-Modelers. K. Reusser, Tutoring Systems and Pedagogical Theory: Representational Tools for Understanding, Planning, and Reflection in Problem Solving. G. Salomon, On the Nature of Pedagogic Computer Tools: The Case of the Writing Partner. R. Lehrer, Authors of Knowledge: Patterns of Hypermedia Design. S.D. Teasley, J. Roschelle, Constructing a Joint Problem Space: The Computer as a Tool for Sharing Knowledge. Part III:Bridging Differences in Opposing Camps. S.P. Lajoie, Computer Environments as Cognitive Tools for Enhancing Learning. S. Katz, A. Lesgold, The Role of the Tutor in Computer-Based Collaborative Learning Situations. L. Schauble, K. Raghavan, R. Glaser, The Discovery and Reflection Notation: A Graphical Trace for Supporting Self-Regulation in Computer-Based Laboratories. Part IV:Discussants. S.F. Chipman, Gazing Once More Into the Silicon Chip: Who's Revolutionary Now? A. Lesgold, Information Technology and the Future of Education.

Abstract: Making ITS available on the World Wide Web (WWW) is a way to integrate the flexibility and intelligence of ITS with world-wide availability of WWW applications This paper discusses the problems of developing WWW-available ITS and, in particular, the problem of porting existing ITS to a WWW platform We present the system ELM-ART which is a WWW-based ITS to support learning programming in Lisp ELM-ART demonstrates how several known ITS technologies can be implemented in WWW context

Abstract: The Andes system demonstrates that student learning can be significantly increased by upgrading only their homework problem-solving support. Although Andes is called an intelligent tutoring system, it actually replaces only the students' pencil and paper as they do problem-solving homework. Students do the same problems as before, study the same textbook, and attend the same lectures, labs and recitations. Five years of experimentation at the United States Naval Academy indicates that Andes significantly improves student learning. Andes' key feature appears to be the grain-size of interaction. Whereas most tutoring systems have students enter only the answer to a problem, Andes has students enter a whole derivation, which may consist of many steps, such as drawing vectors, drawing coordinate systems, defining variables and writing equations. Andes gives feedback after each step. When the student asks for help in the middle of problem-solving, Andes gives hints on what's wrong with an incorrect step or on what kind of step to do next. Thus, the grain size of Andes' interaction is a single step in solving the problem, whereas the grain size of a typical tutoring system's interaction is the answer to the problem. This report is a comprehensive description of Andes. It describes Andes' pedagogical principles and features, the system design and implementation, the evaluations of pedagogical effectiveness, and our plans for dissemination.