Automated individualized learning program creation system and associated methods

• US 6,996,366 B2
• Filed: 11/02/2001
• Issued: 02/07/2006
• Est. Priority Date: 11/02/2000
• Status: Expired due to Term

• Current Assignee: Skillsoft Ireland Limited (SkillSoft Limited)
• Original Assignee: National Education Training Group, Inc.
• Inventors: Pezzuti, Albert, L'Allier, James J., Henrie, Stephen P.
• Primary Examiner(s): ADAMS, CHANDA L
• Application Number:
  US10/001,902
• Publication Number:
  US 20030118978A1
• Time in Patent Office: 1,558 Days
• Field of Search: 434/362, 434/219, 434/350, 434/322, 434/323, 434/118
• US Class Current: 434/362
• CPC Class Codes: G09B 7/02 of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student

Abstract

A computer-based method is provided that determines a “gap” between the skill(s) possessed by a user and those desired to be possessed and then creates a training regimen to fill that gap. The method maps the skill gap with at least one course from a database and automatically creates a set of training interventions that contains the at least one course, the set modifiable by an administrator. Then the user is automatically presented with the training regimen.

Claims

1. A computer-based method for implementing a system for automatically producing an individualized learning sequence in a subject area to a user for addressing a skill gap between a skill level of the user and a skill level desired to be possessed, the method comprising the steps of:

entering into a first electronic database a natural language description of a skill level currently possessed by a user in at least one skill in a predetermined subject area;

comparing the possessed skill level with a skill level desired to be possessed by the user in the at least one skill;

determining from the comparing step a skill gap between the possessed skill level and the desired skill level;

mapping the skill gap with at least one course having an entry in a second electronic database to fill the skill gap, each course entry comprising a natural language description of the course, the mapping step comprising;

matching words in the natural language descriptions of the mapped course in the second database and of the at least one skill in the predetermined subject area; and

ranking each course having at least one matching word with the description of the at least one skill in the predetermined subject area for probable relevancy, wherein the ranking step comprises;

multiplying a count of each matching word by a predetermined weighting value to calculate a weighted value for each matching word;

summing the weighted values for all the matching words to obtain a score;

ordering the at least one course according to the scores thereof; and

imposing a predetermined limit for the score above which a course is mapped for possible inclusion in a training intervention set;

automatically creating a set of training interventions the training intervention set to be recommended to the user, the set containing the at least one mapped course;

permitting an administrator to review the at least one mapped course and, if desired, to manually select the at least one mapped course for including in the set of training interventions to be recommended to the user; and

presenting the user with a training regimen comprising the set of training interventions.

2. The method recited in claim 1, further comprising the steps, prior to the matching step, of:

tabulating each word in the natural language description of the mapped course;

tabulating a number of occurrences of each word in the natural language description of the mapped course;

comparing each word in the natural language description of the mapped course with a list of words that should be skipped;

assigning a null weighting value to each word that should be skipped as determined by the each word comparing step;

assigning a weighting value to each nonskipped word; and

the ranking step comprises using each matching word and the weighting value of each matching word to determine a score indicative of the probable relevancy.

3. The method recited in claim 2, wherein tabulating steps further comprise:

tabulating each word phrase in the natural language description of the mapped course; and

tabulating a number of occurrences of each word phrase in the natural language description of the mapped course; and

wherein;

the word matching step comprises matching word phrases in the natural language descriptions of the mapped course in the second database and of the at least one skill in the predetermined subject area;

the weighting value assigning step further comprises assigning a weighting value to each word phrase; and

the ranking step further comprises using each matching word phrase and the weighting value of each matching word phrase to supplement the score indicative of the probable relevancy.

4. The method recited in claim 1, further comprising the step, prior to the mapping step, of permitting the administrator to set mapping criteria.

5. The method recited in claim 4, wherein each course entry in the second database comprises a plurality of metadata elements, at least one of which comprises the natural language description of the course, and wherein the permitting step comprises receiving from the administrator a selection from among the metadata elements for consideration in the mapping step.

6. A computer-based method for implementing a system for automatically producing an individualized learning sequence in a subject area to a user for addressing a skill gap between a skill level of the user and a skill level desired to be possessed, the method comprising the steps of:

comparing a skill level possessed by a user with a skill level desired to be possessed by the user in the skill;

determining from the comparing step a skill gap between the possessed skill level and the desired skill level;

mapping the skill gap with at least one course to fill the skill gap, each course associated with a natural language description of the course, the mapping step comprising;

matching words in the natural language descriptions of the mapped course and of the skill;

ranking each course having at least one matching word with the description of the skill for probable relevancy, wherein the ranking step comprises;

multiplying a count of each matching word by a predetermined weighting value to calculate a weighted value for each matching word;

summing the weighted values for all the matching words to obtain a score;

ordering the at least one course according to the scores thereof; and

imposing a predetermined limit for the score above which a course is mapped for possible inclusion in a set of training interventions; and

automatically creating the training intervention set to be recommended to the user, the set containing the at least one mapped course.

7. The method recited in claim 6, further comprising the steps, prior to the matching step, of:

tabulating each word in the natural language description of the mapped course;

tabulating a number of occurrences of each word in the natural language description of the mapped course;

comparing each word in the natural language description of the mapped course with a list of words that should be skipped;

assigning a null weighting value to each word that should be skipped as determined by the each word comparing step;

assigning a weighting value to each nonskipped word; and

the ranking step comprises using each matching word and the weighting value of each matching word to determine a score indicative of the probable relevancy.

8. The method recited in claim 7, wherein tabulating steps further comprise:

tabulating each word phrase in the natural language description of the mapped course; and

tabulating a number of occurrences of each word phrase in the natural language description of the mapped course; and

wherein;

the word matching step comprises matching word phrases in the natural language descriptions of the mapped course and of the skill;

the weighting value assigning step further comprises assigning a weighting value to each word phrase; and

the ranking step further comprises using each matching word phrase and the weighting value of each matching word phrase to supplement the score indicative of the probable relevancy.