[comp.edu] ITS KNOWLEDGE ACQUISITION INFO NEEDED

grassi@hpindda.HP.COM (Maurizio Grassi) (08/23/88)

My name is MAURIZIO GRASSI, I am a student at the Polytechnic of Milan in
Italy.
I am developing a thesis about a prototype of an ITS system.
My main interest is about your methodology in knowledge acquisition.
In the project I am involved, I have to explore this problem and try to create
an implemented model of an interactive knowledge acquisition tool.
I am working with two other students.
They solved the problem of guiding the student in learning and how to recover
from his errors, and implemented a prototype of ITS which teaches two 
topics:
	- English verbs,
	- semantic nets.
I have to generalize this work we design together and implement a tool which 
creates the knowledge base for the system.
I would really appreciate it if someone would send me some information about
projects or interesting references which can help me to design my work.

A report about the project follows.

                                               Greetings,


THE "EDUCATION EXPERT ENVIRONMENT"

This research analyzes models of knowledge handled to provide an intelligent
computer aided instructor.
The methodology we are developing tries to work out the principles of 
teaching/learning processes on which pedagogic tools need to be based.
These principles were formalized by Burton and Brown in: " An investigation
of computer coaching for informal learning activities " (see Sleemann and 
Brown, Intelligent Tutoring Systems, Academic Press 1982).
From this basis we want to build a shell-system which is a global environment
in instruction.
Teaching subjects can be divided in structured and non-structured, i.e. 
knowledge can be achieved by students in an incremental step-by-step way or in
an unstructured manner.
Our work designs a tool which solves the problem of structures learning.
The key points, that characterize the intelligent tutoring system we are 
modeling, are:
	- being able to answer a variety of user questions and explaining its
	  arguments using a model of the application domain;
	- giving advice in order to proceed with a task;
	- selecting and ordering material and choosing the most appropriate
	  teaching strategy;
	- having a student's model;
	- optimizing the learning process.
With the project, called Education Expert Environment, we want to monitor on 
the one hand the teacher in producing the subject and on the other the student
in using this material.
In order to create a flexible tool, we divide the problem into three parts:
	- the development of a course planning unit in which to acquire the
	  knowledge (IN DESIGN);
	- the project of an inference engine about student's move (DONE);
	- the study of a manager of student's learning modality (DONE);
The knowledge is recorded in a genetic graph (see Goldstein, " The genetic
graph: a representation for the evolution of procedural knowledge ", 
International Journal of Man-Machine Studies 1979) we organize in three levels
easy to handle:
	- the "island-network" in which the limits of the argument are defined;
	- the "island-model" in which the contents of the subjects are 
	  referenced;
	- the "concept-model" which is the specific learning unit.

- The DESIGN UNIT
The teacher, using a knowledge acquisition tool, plans the course and describes
the teaching process.
The "concept-model" of a particular argument is developed.
Each model, which plays the role of rule-based domain expert, is embedded in 
the "island-model", the brick of the "island-network" that defines the global
courseware.

- The TEACHING-LEARNING UNIT
The student, using the teaching/learning environment, is guided through the
"island-network", the learning contest, by an expert manager which adapts its
advice and explanation to the background knowledge and experience of the user.

- The INFERENCE MACHINE
Each concept is a framework to test student's knowledge.
An expert "teacher", in a differential way, debugs student's errors and builds
a model of his learning activity.
This model is used by an "orator" which defines the answers and examples to be
proposed to  increase the learner's knowledge.
An "evaluator" judges the quality of each move to investigate the student's
capability.