Data processing: artificial intelligence – Knowledge processing system
Reexamination Certificate
1999-03-26
2001-09-18
Chaki, Kakali (Department: 2122)
Data processing: artificial intelligence
Knowledge processing system
Reexamination Certificate
active
06292792
ABSTRACT:
TECHNICAL FIELD OF THE INVENTION
The present invention relates generally to knowledge creation and distribution systems and methods, and more particularly, a system and method using software programming to create a knowledge base, organize the knowledge base or some subset thereof, and distribute the knowledge in various formats, including a tutorial.
BACKGROUND OF THE INVENTION
Organizations and companies can amass tremendous amounts of information. However, transmitting this information in a useable format, including the right subset of the information and in the proper manner, to employees or individuals in the organization is often very difficult. In order to aid in this process, numerous computer-based training, tutoring and information delivery systems have been propagated to attempt to transfer data or information to users with no external input from a human (other than the user).
These training systems generally fall under the category of “computer-based training” (CBT), which includes “intelligent computer-based training” (ICBT), “intelligent computer-aided training” (ICAT) and “intelligent tutoring” (ITS) systems. These types of training systems share the objective of presenting instructional material to a human recipient (called a “user”) using a computer program with little or no additional human intervention. These types of computer-based tutorial systems have been developed to reduce the cost associated with traditional classroom training (including travel costs, salaries for instructors, and excessive lost productivity during training).
In these computer-based training systems, the computer program must initially be provided with a database of the basic information from which it can compose the instructional material (e.g., text, graphics, charts, video clips, audio clips, etc.) that is provided or built by an “author.” There are two distinct concepts surrounding the delivery of information using these tutorial systems that can be categorized as follows: (1) the content detailing the concepts to be conveyed to the user and (2) the manner in which the content is to be conveyed. For purposes of this disclosure, these two concepts are termed the “content” and “pedagogy” respectively.
Traditional CBT approaches generally include “authoring tools” that allow authors to develop and deliver on-line instruction programs. These prior art CBT systems focus on integrating numerous media formats into seamless, highly scripted presentations. These CBT authoring systems require the author to completely create and specify the pedagogy. Also the content and the pedagogy are highly interconnected within the database. Furthermore, these CBT systems have only been used to deliver knowledge to a student in a tutorial paradigm.
An extension of the tutorial systems can be generally categorized as a user-model tutorial. These user-model prior art tutorial systems attempt to develop models of the user's state of knowledge prior to the tutorial. The emphasis of these approaches, including the overlay model, the bug library model, and the dynamic model computation, is on developing a student model and then using this model to determine choices in a predetermined pedagogy. However, these user-model approaches do not reduce any of the problems associated with creating the predetermined pedagogy by the author.
Another example of a computer aided training system is contained in U.S. Pat. No. 5,311,422, entitled “General Purpose Architecture for Intelligent Computer-Aided Training,” which discloses a tool for building on-line training programs, including templates for content, pedagogy, and user model (i.e., model of the user's knowledge) that apply to a wide variety of domains. The tool can execute training programs using these general templates and cooperating expert system (rule-based) programs. However, these rule-based programs must be individually written for each new training application and therefore require a person skilled in the art of rule-based programming; a rare expertise when compared to traditional programming skills for languages such as C++ and JAVA. Furthermore, this patent still requires the author to create a fully-specified pedagogy (i.e., the pedagogy cannot be created automatically). Additionally, this prior art patent only discloses the delivery of knowledge to users in a tutorial paradigm (i.e., not in a help system, customer service, what-if scenario, etc.)
Another prior art training approach is virtual classroom training (VCT) which attempts to combine elements of classroom training with elements of CBT using video conference and other technologies. Typically, students are linked with an instructor in a virtual classroom using telecommunications technology and computer applications. While VCT offers some of the advantages of interaction among students and an instructor, it still has the drawback of requiring a human instructor. Additionally, these prior art VCT do not automatically generate pedagogies for the simple reason that the instructor determines how the material will be delivered. Furthermore, the initial implementation costs for VCT are extremely high and the VCT courses are not self-paced.
In all of the above-described prior art systems, the author must create and/or input a pedagogy for delivering the knowledge to the user. Therefore, during the building of the database, the author must also create the pedagogy (i.e., the manner in which the user will be delivered information from the database). In other words, the author must specify pedagogical details such as when content is to be displayed, how often it is to be displayed, whether it is optional or must be mastered prior to moving forward, etc. Furthermore, more flexible pedagogies are more desirable as they can address a greater variety of user backgrounds and skill levels, and can provide a given user with a greater variety of delivery interactions. In fact, some of these prior art tutoring systems incorporate very elaborate pedagogical specifications, including branching logic that can be based upon student inputs. However, another limitation of the prior art tutoring systems is that the greater the flexibility in the pedagogy, the greater the burden on the author who must input all the pedagogical details. This places a higher burden on either the author, the programmer creating the program, or both.
SUMMARY OF THE INVENTION
The present invention provides a dynamic knowledge creation and delivery system and method that substantially eliminates or reduces disadvantages and problems associated with previously developed computer-based information delivery systems and methods.
More specifically, the present invention provides a system for that includes a knowledge delivery computer program stored in computer-readable form on a tangible storage medium for delivering concepts from a configuration data base to a user. An author can create the configuration data base using the knowledge delivery computer program so that the configuration includes a plurality of concepts and, optionally, a plurality of problems associated with the concepts. As the author creates the configuration, the knowledge delivery software allows the author to create a configuration taxonomy to define the relationships between the concepts. The knowledge delivery software can then automatically generate a pedagogy for the configuration based on the configuration taxonomy that defines how the concepts will be delivered to a user. The author may optionally create all or part of the pedagogy manually. The knowledge delivery software can also facilitate the delivery of the content within the configuration to a user according to the pedagogy. A user can access the configuration using the knowledge delivery software over the internet using a user interface stored on the client computer that allows the a user to send requests and receive responses over the internet.
The present invention provides an important technical advantage by separating the content to be delivered from the pedagogy or manner of delivery. Therefo
Baffes Paul T.
Nugent Shane V.
Subramanian Siddarth
Chaki Kakali
Gray Cary Ware and Freidenrich
Intelligent Learning Systems, Inc.
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