Intelligent tutoring System ITS

1
Intelligent tutoring System ITS

• Nadia Khursan
• Dima Shaheen

2
outlines

• History
• Components

3
History
CAI
ICAI
ITS
4
Drawbacks of CAI (compared with human tutor)

• Inability to conduct dialogues with the student
  in natural language
• Inability to understand the subject being taught
• The program cannot accept unanticipated
  responses
• Inability to understand the nature of the
  students mistakes or misconceptions
• Inability to profit from experience with students
  or to experiment with the teaching strategy.

5
Intelligent Computer Assisted Instruction (ICAI)

• concerned with developing computer systems which
  interact knowledgeably with learners.(Self, 1989)
• The users are able to conduct flexible and
  adaptive dialogue with the computer through words
  or graphic interfaces
• They should be allowed to access information in
  varying forms and from varying viewpoints as they
  wish

.



6
What is ITS

• Computer-based system that can
• simulate the human tutor by putting their
  knowledge and inference mechanisms into computer
  systems.
• communicate with the users intelligently
• make inferences about students knowledge based
  on what they have entered
• deduce the learners knowledge from his
  interactions with the system as he tries to
  handle the educational tasks posed to him (Mandl
  Lesgold, 1989)

7
Intelligent Tutoring System (ITS)

• A step beyond ICAI
• leading to new classes of problems and approaches
  and where learning is at least as important as
  teaching.
• Involves artificial intelligence concepts
  including
• Knowledge representation and communication
• problem-solving approaches
• dynamic student modeling
• human cognition
• intelligent user interfaces
• intelligent help systems
• use of strategies

8

• capture the knowledge that allows experts to
  compose an instructional interaction
• knowledge is explicitly represented and can be
  used in the system
• the program is responsible to compose
  instructional interactions dynamically, making
  decisions by reference to the knowledge provided.

9
(No Transcript)
10
(No Transcript)
11
ITS components
Domain Expert
Instructional Expert
Intelligent Interface
Student Model
user
12
Components of an ITS

• The expertise module which contains the expert's
  knowledge on the domain (subject knowledge).
  knowledge representation
• The student module
• profile
• Cognitive state
• Affective state
• The tutorial module which contains the tutorial
  knowledge (knowledge about how to teach).
• The interface module which is responsible for the
  communication between the computer system and the
  student,containing Communication knowledge --
  knowledge about how to communicate with the
  learner through the computer.

13
1. Domain Knowledge

• ontology

14
2. Student model

• It includes the following four kinds of
  information
• Personal data it is used for the identification
  of the user (e.g. name, email).
• Users characteristics it mainly includes
  cognitive abilities, learning styles, learning
  goals and teaching strategies preferences.
• Knowledge level for example, novice, beginner,
  intermediate, advanced, etc. of the sub-domains
  and the whole domain.
• Interaction records they record the interaction
  of a user agent with a system.

15
3. Pedagogical model
16
Authoring module

• A course can have as many
• chapters,
• lessons,
• and topics as required

17
..topics

• Each topic consists of two major components
• Learning Strategies
• Learning Contents

18
..topics Learning Strategies

• consists of three pedagogy elements, which are
  integrated in every lesson to provide complete
  and effective instructional knowledge
• Learning Objective,
• Introduction,
• Summary

19
topics Learning Content

• Content page
• Activity page
• Assessment page
• which are the learning objects used by the
  learners to achieve the learning objectives.

20
4. Intelligent interface
21
(No Transcript)
22
Managing student emotions
23
Emilie-2
24
Intelligent agents

• Personal assistants? student assistant
• MIMIC (Multiple Intelligent Mentors Instructing
  Collaboratively),

25
Student Information Manager (SIM)

• electronic mail filtering
• class and meeting scheduling
• assignment information searching
• appropriate information presentation
• book and article recommendation and
• management of information student resources,
  including indexing, cross-referencing and
  updating for consistency.

26
SIM knowbots (knowledge robots)

• Maes

27
MIMIC (Multiple Intelligent Mentors Instructing
Collaboratively)

• The aim is to provide agents which provide
  content appropriate for individual lessons and
  can perform other tasks automatically, such as
  opening web pages, reading text, running other
  programs, answering questions and providing
  instructions.
• Botknowledge

28
Versions of MIMIC

• Instructivist Agent and Constructivist Agent
• Chatterbots
• Recognizing students emotion
• Recognizing student cognitive style
• Presenting and organizing the learning content in
  a way that fits the student style.
• Tracking student emotional state during the
  learning session and providing the needed
  feedback

29
Cognitive styles and interface design

• How does the structure of the material to be
  learned interact with style?
• Does the mode of presentation of the material
  affect learning?
• What effect does the type of content have on
  style and learning?

30
Dimensions of Cognitive Style

• Verbal-Imagery - an individuals position on this
  dimension determines whether that person tends to
  use images or verbal representation to represent
  information when thinking.
• Wholist-Analytic - an individuals position on
  this dimension determines whether that person
  processes information in parts or as a whole.
  (Riding and Rayner, 1998)
• Cognitive Styles Analysis (Riding, 1991) software
  package

31
Effects of cognitive style

• can affect learning related elements such as
• preferred format of instructional material
  (Pillay, 1998)
• learning in a vocational training environment
  (Russell, 1997)
• preferred mode of working (Riding Read, 1996)
  and
• the effectiveness of book or hypertext
  (Wilkinson, Crerar Falchikov, 1997).

32
Example of intelligent agents

• Cosmo is a pedagogical agent particularly keen
  on space deixis and on emotional behavior.
• Smiley is an animated agent used in a simple
  courseware to provide feedback to the students
  based on their progress in training.
• Steve (Johnson, 2000) is designed to interact
  with students in networked immersive virtual
  environments
• Aini (MBR, 2004) is another 3D animated
  intelligent agent which has been employed and has
  the ability to improve services by reducing
  reliance on live agents to provide the answers
  and information to service inquiries in
  e-commerce (Sing Fung, 2003) and e-medicine
  (Sing, Fung, Ph'ng, 2005) applications.