Predictive artificial intelligence and pedagogical agent modeling in the cognitive imprinting of knowledge and skill domains

• US 20060166174A1
• Filed: 01/21/2005
• Published: 07/27/2006
• Est. Priority Date: 01/21/2005
• Status: Abandoned Application

• Current Assignee: Dean Gordon Arrasmith, Deme Michael Clainos, Rowe T. Peter
• Original Assignee: Dean Gordon Arrasmith, Deme Michael Clainos, Rowe T. Peter
• Inventors: Rowe, T. Peter, Clainos, Deme Michael, Arrasmith, Dean Gordon
• Application Number:
  US11/040,632
• Publication Number:
  US 20060166174A1
• Time in Patent Office: Days
• US Class Current: 434/236
• CPC Class Codes: G09B 5/06 with both visual and audible presentation of the material to be studied

Abstract

System and methods for predicting and dynamically adapting the most appropriate content and teaching strategies that aid individual student learning. System and methods are based on a cognitive model that integrates new information with what the student already knows. A program of study is predicted by the unique cognitive needs of the individual student correlated with aggregated student data history using an Artificial Intelligence Engine (AI Engine). Said system and methods then dynamically adapt the initial cognitive model to the student'"'"'s ongoing progress using personalized software Agents. Said system and methods include a computer network that incorporates a server-side AI Engine and a collection of client-side software Agents embodied as animated characters. The program connects new information to prior knowledge and then strengthens these connections through dedicated learning Activities, customized to the student, to ensure that effective, and real, learning occurs.

Claims

1. A method of ensuring that students learn from instruction, comprising the steps of:

acquiring cognitive student data into a computer;

storing cognitive student data models in a computer;

automatically creating a customized program of content activities based on a student cognitive model; and

automatically adjusting a customized program of activities based on a changing student cognitive model as said student progresses through the program

2. The method of claim 1, wherein acquiring cognitive student data step is the input of prior knowledge from familiar sources and directly from student

3. The method of claim 1, wherein the computer has an Artificial Intelligence Engine to automatically create a customized program of activities step

4. The method of claim 1, wherein the automatic adjustment of the customized program of activities step is implemented by software agents

5. The method of claim 1, wherein a customized program of activities is managed by a helper agent and a plurality of content agents

6. The method of claim 3, wherein the automatic creating of a customized program step further comprises the step of pattern matching the target students individual cognitive model with the historically stored cognitive model of all previous students using an Artificial Intelligence Engine

7. The method of claim 5, wherein the agent further comprises a helper agent to guide and encourage the student, and multiple content agents to present instructional material.

8. The method of claim 5, wherein automatic adjusting of the student cognitive model is implemented by the helper agent and the content agents monitoring student responses to customized program of activities.

9. The method of claim 8 wherein the helper agent and the multitude of contents agents communicate with the student via computer response, voice recognition and speech.

10. A computer-implemented learning system, comprising:

a server computer and a plurality of client computers on a network

means for displaying a prior knowledge questionnaire and test to a parent/guardian/teacher and student on a client computer, and storing said results in a student cognitive model dataset

means for storing a student cognitive model in a server computer

means for comparing a multitude of stored student cognitive models with a new student cognitive model using an Artificial Intelligence Engine for the purpose of identifying pattern matches of past successful activity programs

means for downloading and implementing software helper and content agents on a client computer

means for downloaded and visually presenting content activities to a student on a client computer

means for student to interact with content activities and to have said interactions stored

means for communications between a server AI Engine and client software agents

11. The apparatus of claim 10, further comprising a means to modify a student cognitive model according to the student'"'"'s results

12. The apparatus of claim 10, further comprising a means to hear student directions and questions using voice recognition and a means to instruct the student using speech.

13. The apparatus of claim 10, further comprising means of providing parents/guardians/teachers with reports based on student interactions with content activities.

14. The apparatus of claim 10, further comprising a mechanism to allow students to accumulate rewards in the form of points based on their results of mastering content activities.