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.

A web-based bayesian intelligent tutoring system for computer programming

Abstract: In this paper, we present a Web-based intelligent tutoring system, called BITS. The decision making process conducted in our intelligent system is guided by a Bayesian network approach to support students in learning computer programming. Our system takes full advantage of Bayesian networks, which are a formal framework for uncertainty management in Artificial Intelligence based on probability theory. We discuss how to employ Bayesian networks as an inference engine to guide the students' learning processes. In addition, we describe the architecture of BITS and the role of each module in the system. Whereas many tutoring systems are static HTML Web pages of a class textbook or lecture notes, our intelligent system can help a student navigate through the online course materials, recommend learning goals, and generate appropriate reading sequences.

Chapter 37 – Intelligent Tutoring Systems

Abstract: Publisher Summary The goal of intelligent tutoring systems (ITSs) would be to engage the students in sustained reasoning activity and to interact with the student based on a deep understanding of the students' behavior. This chapter begins by providing an overview of intelligent tutoring systems. The chapter comments on competing research goals in the field, followed by descriptions of two successful systems: (1) the Pittsburgh urban math project algebra tutor project and (2) the SHERLOCK project. These two systems are being deployed in real-world educational environments with substantial success. This chapter briefly describes the underlying theory and implementation of each system, to motivate later discussions. A description of the standard components in an intelligent tutoring system is also presented along with a discussion of human-computer interaction assessment issues unique to educational software. This chapter also provides a prescription for ITS design and development methods. Several issues concerning ITS design principles are also addressed in the chapter.

Student modeling and assessment in intelligent tutoring of software patterns

Abstract: This paper presents the design, implementation, and evaluation of a student model in DEPTHS (Design Pattern Teaching Help System), an intelligent tutoring system for learning software design patterns. There are many approaches and technologies for student modeling, but choosing the right one depends on intended functionalities of an intelligent system that the student model is going to be used in. Those functionalities often determine the kinds of information that the student model should contain. The student model used in DEPTHS is a result of combining two widely known modeling approaches, namely, stereotype and overlay modeling. The model is domain independent and can be easily applied in other learning domains as well. To keep student model update during the learning process, DEPTHS makes use of a knowledge assessment method based on fuzzy rules (i.e., a combination of production rules and fuzzy logics). The evaluation of DEPTHS performed with the aim of assessing the system's overall effectiveness and the accuracy of its student model, indicated several advantages of the DEPTHS system over the traditional approach to learning design patterns, and encouraged us to move on further with this research.

Large-scale randomized controlled trial with 4th graders using intelligent tutoring of the structure strategy to improve nonfiction reading comprehension

Abstract: Reading comprehension is a challenge for K-12 learners and adults. Nonfiction texts, such as expository texts that inform and explain, are particularly challenging and vital for students’ understanding because of their frequent use in formal schooling (e.g., textbooks) as well as everyday life (e.g., newspapers, magazines, and medical information). The structure strategy is explicit instruction about how to strategically use knowledge about text structures for encoding and retrieval of information from nonfiction and has consistently shown significant improvements in reading comprehension. We present the delivery of the structure strategy using a web-based intelligent tutoring system (ITSS) that has the potential to offer consistent modeling, practice tasks, assessment, and feedback to the learner. Finally, we report on statistically significant findings from a large scale randomized controlled efficacy trial with rural and suburban 4th-grade students using ITSS.

ZOSMAT: Web-based intelligent tutoring system for teaching-learning process

Abstract: In recent years, there is a growing need for computer technology to be used in a real school environment and/or higher education classrooms. However, educational software has often been criticized as it has not been specifically designed to meet the needs of real classrooms. In this study, we have tried to develop the system, what we have called as ''ZOSMAT'' that will respond almost every needs of a real classroom. ZOSMAT can be used for the purpose of either individual learning or real classroom environment with the guidance of a human tutor during a formal education process. This characteristic of ZOSMAT distinguishes itself from other intelligent tutoring systems. ZOSMAT follows a student in each stage of the learning process and guides him/her about what he/she will need to do. ZOSMAT with a web-based feature presents an equal opportunity of education for both the student in the classroom and the student in the far end of the world. This system is a student-centered one and the progress in student's learning process depends on his/her effort.