1. UNIT V: INTELLIGENT TUTORING SYSTEM AND ITS APPLICATION Dr. Bo Liu South China Normal University School of Information Technology in Education Email: liubli@scnu.edu.cn

2. 2 Outline Intelligent tutoring system (ITS) The central frame of intelligent tutoring system (ITS) Techniques of intelligent tutoring system (ITS) One applying case of ITS

3. 3 Intelligent tutoring system (ITS) Artificial intelligence (AI) Intelligent tutoring system (ITS) Representative models-- MYCIN;WEST;GUIDON

4. 4 Artificial intelligence (AI) The only way not to succeed is not to try. ----------Edward Teller(1908-2003) Artificial Intelligence (shorted as AI) is the study of man- made computational devices and systems which can be made to act in a manner which we would be inclined to call intelligent.

5. 5 History of AI The 'Dark Ages', or the birth of artificial intelligence (1943-56) The rise of artificial intelligence, or the era of great expectations (1956-late 1960s) Unfulfilled promises, or the impact of reality (late 1960s-early 1970s) The technology of expert systems, or the key to success (early 1970s-mid-1980s) How to make a machine learn, or the rebirth of neural networks (mid-1980s-onwards)

6. 6 A summary of the main events in the history of AI

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12. 12 Intelligent tutoring system (ITS) In 1982, Sleeman and Brown reviewed the state of the art in computer aided instruction and first coined the term Intelligent Tutoring Systems (ITS) -- Sleeman, D., & Brown, J. S. (1982). Introduction: Intelligent Tutoring Systems. In D. Sleeman & J. S. Brown (Eds.), Intelligent Tutoring Systems (pp. 1-11). New York: Academic Press.

13. 13 Goal of ITS To modularize the curriculum To engage the students in sustained reasoning activity To interact with the student based on a deep understanding of the students behavior Collect data which instructors could use to tutor and remediate students If ITS could realize even half the impact of human tutors, the payoff for society promised to be substantial.

14. 14 Learning Activity I Group discussion What do you think about the current status of ICAI and ITS? Giving your reasons. Can we use ICAI and ITS in educational field? Describing yours perspectives. –Time limitation: 20 Minutes

15. 15 Representative models MYCIN WEST GUIDON

16. 16 MYCIN It was an early expert system developed over five or six years in the early 1970s at Stanford Universityexpert system It was written in Lisp as the doctoral dissertation of Edward Shortliffe This expert system was designed to identify bacteria causing severe infections, such as bacteremia and meningitis, and to recommend antibiotics, with the dosage adjusted for patient's body weight — the name derived from the antibiotics themselves, as many antibiotics have the suffix "-mycin".

17. 17 WEST WEST is an example of a coach system. It is built on top of the game "How the West was Won". It is a child's game, a variation of a game also called "Shoots and Ladders" (Figure showing). The game was originally available on the PLATO system. PLATO is the tutoring environment that was developed by Computer Development Corporation, CDC, in the 1960s.

18. 18 GUIDON ( Clancey W.J., 1987), GUIDON is an intelligent computer-aided instructional program for teaching diagnosis, such as medical diagnosis. The program is general. Without reprogramming, the program can discuss with a student any diagnostic problem that it can solve on its own. In instructional programs, knowledge is represented as linguistic schemas (rules) such as: I F the site of the culture is normally sterile and the gram-stain of the organism is negative, THEN there is strongly suggestive evidence that there is significant disease associated with this occurrence of the organism.

19. 19 The central frame of intelligent tutoring system (ITS)  The basic constitutes of ITS  The central frame of ITS

20. 20 The basic constitutes of ITS (1)a task environment (2) a domain knowledge module (3) a student model (4) a pedagogical module

21. 21 The Problem-Solving Environment. This component of the tutor defines the problem solving activities in which the student is engaged. At minimum it consists of an editor that accepts and represents student actions. (1) The ITS problem solving environment should approximate the real world problem solving environment. (2) The ITS problem solving environment should facilitate the learning process.

22. 22 The Domain Expert. As its name suggests, the domain expert module represents the content knowledge that the student is acquiring. This module is at the heart of an intelligent tutoring system and provides the basis for interpreting student actions. Classically, the domain module

23. 23 The Student Model. The student model is a record of the student’s knowledge state. There are classically two components in a student model: an overlay of the domain expert knowledge and a bug catalog.

24. 24 The Pedagogical Module. The pedagogical module is responsible for structuring the instructional interventions. This module may operate at two levels (Pirolli and Greeno, 1998). At the curriculum level it can sequence topics to ensure an appropriate prerequisite structure is observed (Capell and Dannenberg, 1993) individualize the amount of practice at each level to ensure the students master the material (Corbett and Anderson, 1995b).

25. 25 Central frame of ITS Modeler Expert SimulatorKnowledge BaseStudent Model Tutor Problem Student TUTORING SYSTEM Problem Information Data Request Problem Data Explanation Data Problem Solving Situation Predicted and Preferred behavior Relations and Student Prototypes Advice &Explanation Update Model Students Current state

26. 26 Intelligent tutoring system (ITS) techniques Knowledge expression Logic reasoning Expert system

27. 27 Knowledge expression production rules: MYCIN, PROSPECTION mathematical logics; frames; scripts; semantic net; relational database

28. 28 Logic reasoning We begin our exploration of the use of mathematical logic in computer deduction by illustrating several simple approaches that use the propositional calculus, Then we turn to the more powerful predicate calculus and examine some heuristics and strategies for trying to prove proposed conclusions.

29. 29 Expert system structure

30. 30 One applying case of ITS Process of developing ITS Studying case posting

31. 31 Figure right displays the major activities in tutor development: (I) needs assessment, (2) cognitive task analysis, (3) tutor implementation and (4) evaluation. The first step is common to all software design. In the case of ITS design, this involves specifying educational goals and curriculum. The second stage is common to expert systems programming, although the target is defined more narrowly here: a cognitively valid model of problem solving performance. The third phase consists of initial tutor implementation, which is followed by a series of evaluation activities: (1) pilot studies to confirm basic usability and educational impact; (2) formative evaluations of the system under development, including (3) parametric studies that examine the effectiveness of system features and finally, (4) summative evaluations of the final tutor’s effect: learning rate and asymptotic achievement levels.

32. 32 Studying case posting Math learning system Whale Watcher system

33. 33 Assignment Describing the mechanism of an ICAI or ITS system. You can freely find out any one ICAI or ITS system by yourself. Explaining yours perspectives on ICAI and ITS.