Real time learning and self improvement educational system and method

Abstract

A computer-implemented method of generating learning exercises is provided. The method comprises receiving text, processing the text using linguistic parsers to generate linguistic characteristics of the text, storing the linguistic characteristics in a data file, retrieving user information comprising a user knowledge level and user goals, using the stored linguistic characteristics and the user information to generate the learning exercises based on a parametrical model, receiving responses to the learning exercises from the user, and updating the user information based on the responses to the learning exercises. The linguistic characteristics comprise words of the text and relationships between the words.

What is claimed is: 
     
         1 . A computer-implemented method of generating learning exercises, the method comprising:
 receiving text;   processing the text using linguistic parsers to generate linguistic characteristics of the text, the linguistic characteristics comprising words of the text and relationships between the words;   storing the linguistic characteristics in a data file;   retrieving user information comprising a user knowledge level and user goals;   using the stored linguistic characteristics and the user information to generate the learning exercises based on a parametrical model;   receiving responses to the learning exercises from the user; and   updating the user information based on the responses to the learning exercises.   
     
     
         2 . The computer-implemented method of  claim 1 , further comprising:
 using the stored linguistic characteristics and the updated user information to generate subsequent learning exercises based on the parametrical model;   receiving subsequent responses to the subsequent learning exercises; and   updating the updated user information based on the subsequent responses.   
     
     
         3 . The computer-implemented method of  claim 1 , wherein the relationships between the words comprise syntactic links, semantic schemes, grammar rules and/or keyword structures. 
     
     
         4 . The computer-implemented method of  claim 1 , wherein the user information further comprises user personal information and/or user learned information. 
     
     
         5 . The computer-implemented method of  claim 1 , wherein the linguistic parsers comprise a syntactic parser, a semantic parser, a grammar extractor and/or a marquee summarizer. 
     
     
         6 . The computer-implemented method of  claim 1 , wherein the processing further comprises extracting sentences from the text and processing the sentences using the linguistic parsers. 
     
     
         7 . The computer-implemented method of  claim 1 , wherein parameters of the parametrical model comprise subject, category, learning technology and/or educational mode. 
     
     
         8 . The computer-implemented method of  claim 1 , further comprising, prior to retrieving the user information, administering a user placement test to determine the user knowledge level. 
     
     
         9 . The computer-implemented method of  claim 6 , wherein the processing further comprises highlighting parts of speech, grammar patterns, and/or keywords in the sentences according to a color coding scheme. 
     
     
         10 . A non-transitory computer-readable medium having stored thereon instructions to generate learning exercises, the instructions, when executed by a processor, cause the processor to:
 receive text;   process the text using linguistic parsers to generate linguistic characteristics of the text, the linguistic characteristics comprising words of the text and relationships between the words;   store the linguistic characteristics in a data file;   retrieve user information comprising a user knowledge level and user goals;   use the stored linguistic characteristics and the user information to generate the learning exercises based on a parametrical model;   receive responses to the learning exercises from the user; and   update the user information based on the responses to the learning exercises.   
     
     
         11 . The non-transitory computer-readable medium of  claim 10 , wherein the instructions further cause the processor to:
 use the stored linguistic characteristics and the updated user information to generate subsequent learning exercises based on the parametrical model;   receive subsequent responses to the subsequent learning exercises; and   update the updated user information based on the subsequent responses.   
     
     
         12 . The non-transitory computer-readable medium of  claim 10 , wherein the relationships between the words comprise syntactic links, semantic schemes, grammar rules and/or keyword structures. 
     
     
         13 . The non-transitory computer-readable medium of  claim 10 , wherein the user information further comprises user personal information and/or user learned information. 
     
     
         14 . The non-transitory computer-readable medium of  claim 10 , wherein the linguistic parsers comprise a syntactic parser, a semantic parser, a grammar extractor and/or a marquee summarizer. 
     
     
         15 . The non-transitory computer-readable medium of  claim 10 , wherein process the text further comprises extract sentences from the text and process the sentences using the linguistic parsers. 
     
     
         16 . The non-transitory computer-readable medium of  claim 10 , wherein parameters of the parametrical model comprise subject, category, learning technology and/or educational mode. 
     
     
         17 . The non-transitory computer-readable medium of  claim 10 , wherein the instructions further cause the processor to, prior to retrieving the user information, administer a user placement test to determine the user knowledge level. 
     
     
         18 . The non-transitory computer-readable medium of  claim 15 , wherein process the text further comprises highlight parts of speech, grammar patterns, and/or keywords in the sentences according to a color coding scheme.