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Building Intelligent Interactive Tutors

Book Description

Building Intelligent Interactive Tutors discusses educational systems that assess a student's knowledge and are adaptive to a student's learning needs.

The impact of computers has not been generally felt in education due to lack of hardware, teacher training, and sophisticated software. and because current instructional software is neither truly responsive to student needs nor flexible enough to emulate teaching. Dr. Woolf taps into 20 years of research on intelligent tutors to bring designers and developers a broad range of issues and methods that produce the best intelligent learning environments possible, whether for classroom or life-long learning.

The book describes multidisciplinary approaches to using computers for teaching, reports on research, development, and real-world experiences, and discusses intelligent tutors, web-based learning systems, adaptive learning systems, intelligent agents and intelligent multimedia.

It is recommended for professionals, graduate students, and others in computer science and educational technology who are developing online tutoring systems to support e-learning, and who want to build intelligence into the system.

  • Combines both theory and practice to offer most in-depth and up-to-date treatment of intelligent tutoring systems available
  • Presents powerful drivers of virtual teaching systems, including cognitive science, artificial intelligence, and the Internet
  • Features algorithmic material that enables programmers and researchers to design building components and intelligent systems

Table of Contents

  1. Brief Table of Contents
  2. Table of Contents
  3. Copyright Page
  4. Preface
  5. Part I. Introduction To Artificial Intelligence And Education
    1. Chapter 1. Introduction
      1. 1.1. An inflection point in education
      2. 1.2. Issues addressed by this book
      3. 1.3. State of the Art in Artificial Intelligence and Education
      4. 1.4. Overview of the Book
      5. Summary
    2. Chapter 2. Issues and Features
      1. 2.1. Examples of Intelligent Tutors
      2. 2.2. Distinguishing Features
      3. 2.3. Learning Theories
      4. 2.4. Brief theoretical framework
      5. 2.5. Computer science, psychology, and education
      6. 2.6. Building intelligent tutors
      7. Summary
  6. Part II. Representation, Reasoning And Assessment
    1. Chapter 3. Student Knowledge
      1. 3.1. Rationale for building a student model
      2. 3.2. Basic concepts of student models
      3. 3.3. Issues in building student models
      4. 3.4. Examples of student models
      5. 3.5. Techniques to Update Student Models
      6. 3.6. Future research issues
      7. Summary
    2. Chapter 4. Teaching Knowledge
      1. 4.1. Features of teaching knowledge
      2. 4.2. Teaching models based on human teaching
      3. 4.3. Teaching models informed by learning theory
      4. 4.4. Teaching models facilitated by technology
      5. 4.5. Industrial and military training
      6. 4.6. Encoding multiple teaching strategies
      7. Summary
    3. Chapter 5. Communication Knowledge
      1. 5.1. Communication and Teaching
      2. 5.2. Graphic Communication
      3. 5.3. Social Intelligence
      4. 5.4. Component Interfaces
      5. 5.5. Natural Language Communication
      6. 5.6. Linguistic issues in Natural Language Processing
      7. Summary
    4. Chapter 6. Evaluation
      1. 6.1. Principles of intelligent tutor evaluation
      2. 6.2. Example of Intelligent Tutor Evaluations
      3. Summary
  7. Part III. Technologies And Environments
    1. Chapter 7. Machine Learning
      1. 7.1. Motivation for machine learning
      2. 7.2. Building machine learning techniques into intelligent tutors
      3. 7.3. Features learned by intelligent tutors using machine learning techniques
      4. 7.4. Machine learning techniques
      5. 7.5. Examples of intelligent tutors that employ machine learning techniques
      6. Summary
    2. Chapter 8. Collaborative Inquiry Tutors
      1. 8.1. Motivation and research issues
      2. 8.2. Inquiry Learning
      3. 8.3. Collaborative Learning
      4. 8.4. Summary and Discussion
    3. Chapter 9. Web-Based Learning Environments
      1. 9.1. Educational inflection point
      2. 9.2. Conceptual framework for Web-based learning
      3. 9.3. Limitation of Web-based instruction
      4. 9.4. Variety of Web-based resources
      5. 9.5. Building the Internet
      6. 9.6. Standards for Web-based resources
      7. 9.7. Education Space
      8. 9.8. Challenges and Technical Issues
      9. 9.9. Vision of the Internet
      10. Summary
    4. Chapter 10. Future View
      1. 10.1. Perspectives on Educational Futures
      2. 10.2. Computational Vision for Education
      3. 10.3. Where are all the Intelligent Tutors?
      4. 10.4. Where are we Going?
  8. Bibliography
    1. References
  9. Index
    1. SYMBOL
    2. A
    3. B
    4. C
    5. D
    6. E
    7. F
    8. G
    9. H
    10. I
    11. J
    12. K
    13. L
    14. M
    15. N
    16. O
    17. P
    18. Q
    19. R
    20. S
    21. T
    22. U
    23. V
    24. W
    25. X