Topic
Intelligent tutoring system
About: Intelligent tutoring system is a research topic. Over the lifetime, 3472 publications have been published within this topic receiving 58217 citations. The topic is also known as: ITS.
Papers published on a yearly basis
Papers
More filters
Book•
01 Jan 1987
TL;DR: The progression of the research, how theories from these fields are combined in a computational model are described, and some questions coming out of the work might suggest possible collaboration with other fields of research are presented.
Abstract: Over the past 6 years we have been developing a computer program to teach medical diagnosis. Our research synthesizes and extends results in artlficlal intelligence (Al), medicine, and cognitive psychology. This paper describes the progression of the research, and explalns how theories from these fields are combined in a computational model. The general problem has been to develop an "intelligent tutoring system" by adapting the MYCIN "expert system." Thls conversion requires a deeper understanding of the nature of expertise and explanatlon than origlnally requlred for developlng MYCIN, and a concomitant shift in perspective from slmple performance goals to attaining psychologlcal validity in the program''s reasoning process. Others have written extensively about the relatlon of artificlal intelligence to cognltive sclence (e.g., [Pylyshyn, 1978] [Boden, 1977]). Our purpose here is not to repeat those arguments, but to present a case study which will provide a common point for further dlscusslon. To this end, to help evaluate the state of cognitive science, we will outline our methodology and survey what resources and viewpoints have helped our research. We will also discuss pitfalls that other Al-oriented cognitive scientists may encounter. Finally, we will present some questions coming out of our work whlch might suggest possible collaboration with other fields of research.
139 citations
TL;DR: This study has recommended the development and evaluation of mobile-based ITSs, which have rarely been applied in experimental courses including problem-solving, decision-making in physics, chemistry, and clinical fields.
Abstract: With the rapid growth of technology, computer learning has become increasingly integrated with artificial intelligence techniques in order to develop more personalized educational systems. ...
136 citations
TL;DR: This paper presents the results of three evaluation studies performed during 1998 and 1999 on SQL-Tutor, an intelligent tutoring system for the SQL database language, and extended CBM to support long-term modeling of student knowledge, and used this extension to develop an adaptive problem-selection strategy.
Abstract: This paper presents the results of three evaluation studies performed during 1998 and 1999 on SQL-Tutor, an intelligent tutoring system for the SQL database language. We have evaluated the system in the context of genuine courses, and used the results to further refine the system. The main goal of our research has been the exploration and extension of Constraint-Based Modeling (CBM), a student modeling approach proposed by Ohlsson (1994). SQL-Tutor provided us with experiences of using CBM, and we used it to extend the approach in several important ways. The main goal of all three evaluation studies was to determine how well CBM supported student learning. We have obtained positive results. The students who learnt with SQL-Tutor in the first study performed significantly better than those who did not when assessed by a subsequent classroom examination. Furthermore, the analysis of students' learning shows that CBM has a sound psychological foundation.
Besides the evaluation of CBM, we also evaluated the improvements in terms of student assessments of the usefulness of the system and evaluated various techniques used in SQL-Tutor. In the second study, we evaluated the effectiveness of feedback provided to the students. This study showed that high-level advice is most beneficial to students' learning. The focus of the third study was different. We extended CBM to support long-term modeling of student knowledge, and used this extension to develop an adaptive problem-selection strategy. The study revealed the benefits of this strategy in comparison with a simple heuristic strategy. We also reflect on our experiences in evaluating SQL-Tutor.
136 citations
TL;DR: A conceptual for combining ITS and AH into Adaptive Intelligent Tutoring System (AITS) for e-learning systems that allows knowledge to be stored in such a way that is not only independent of the knowledge domain, but also supports the storage of transfer knowledge relationships and prerequisite knowledge relationships is described.
135 citations
05 Sep 2007
TL;DR: The architecture, interface and support for collaboration in the new, multi-user system described is described, which is the first system to also represent a higher-level skill such as collaboration using the same formalism.
Abstract: We present COLLECT-UML, a constraint-based intelligent tutoring system (ITS) that teaches object-oriented analysis and design using Unified Modelling Language (UML). UML is easily the most popular object-oriented modelling technology in current practice. While teaching how to design UML class diagrams, COLLECT-UML also provides feedback on collaboration. Being one of constraint-based tutors, COLLECT-UML represents the domain knowledge as a set of constraints. However, it is the first system to also represent a higher-level skill such as collaboration using the same formalism. We started by developing a single-user ITS that supported students in learning UML class diagrams. The system was evaluated in a real classroom, and the results showed that students’ performance increased significantly. In this paper, we present our experiences in extending the system to provide support for collaboration as well as domain-level support. We describe the architecture, interface and support for collaboration in the new, multi-user system. The effectiveness of the system has been evaluated in two studies. In addition to improved problem-solving skills, the participants both acquired declarative knowledge about effective collaboration and did collaborate more effectively. The participants have enjoyed working with the system and found it a valuable asset to their learning.
134 citations