Use of common words, and common word bound prefixes, infixes, and suffixes for natural language and genre determination; for serving as a student study aid of textbook material; for generating automated indexes, automated keywords of documents, and automated queries; for data-base reduction (compaction); and for sorting documents in heterogenous databases

Studying and learning textbook material involves constructing mental images and/or mental lexicons that enable the user to regurgitate, recite, and/or implement the knowledge representation in a manner that denotes understanding. The process involves the ability to associate and/or configure distinct conceptual and/or tangible objects as represented to the user by word objects of the text. The words come in two forms, MCW/iconic and uncommon/non-iconic. MCW iconic words comprise primarily of the irregular verbs, pronouns and reflexive pronouns, intransitive and modal verbs that in totality represent the body of syncategorematic words that construct the relationships between the uncommon word objects that, in turn, represents the relationship or configuration of the conceptual and/or tangible objects to be learned. Understanding and learning is achieved once the user can ascertain the proper configuration and/or relationship between objects without the “crutch” of having to rely on the syncategorematic body segment of words that originally instructed the user. In the prior State of the Art, exercises used to measure or promote learning fail to recognize the importance of the above principle and, as such, fail to obviate syncategorematic cues. To the extent syncategorematic cues are not obviated, learning becomes less efficient and measurements of learning become less accurate. Claimed herein as an invention is a new method for promoting and measuring learning that excludes syncategorematic cues relying on a automated extraction of syncategorematic word objects or MCW's. A description of the method is as follows:

• After the user studies a chapter from a textbook, the user scans the chapter on a scanner that creates a text file in memory linked to a processor. Then, in a automated fashion, without user interaction, all syncategorematic words, MCW's, are extracted from the text file, (the 300 most commonly used words representing roughly 65% of the words used are extracted with the exception of the negative words, “no” and “don't”). Punctuation is also extracted except end of sentence punctuation. A forward slash might be substituted for a end of sentence period and a backward slash substituted for a question mark. The user is then provided the post extracted text and, also, provided the list of MCW's used as the template of extraction. At this point the user has the option to answer the homework problems at the end of the chapter using both the textbook and post extracted text as a reference or may proceed to do the following. A second post extracted text is made available to the user that has white space areas representing where the original text was extracted. Using the extraction template as a reference, the user is then asked to fill the white space with syncategorematic words (MCW's) in a manner that represents the proper relationship of the non-syncategorematic non extracted words that are spaced apart. If the user is able to complete this exercise in a manner that corresponds fairly well with the original non-extracted text, the user can be considered as having learned the material. The user is then encouraged to use the post extracted text, (the one devoid of white space gaps) as a study guide in preparation of quizzes or exams or for completing related exercises or projects.
• It should be pointed out, the method described above for which claim of invention is made, is completely automated, involving no human interaction that could bias the learning or testing process. The theoretical concept upon which it is based is not part of the prior State of the Art. The method relies on a small set of MCW's, syncategorematic words, serving as the nuts, bolts, and cement that establish the configuration of objects to be learned (understanding), the objects represented by the non-syncategorematic word object segment of the text.
• The methodology as described above could be modified as called for based upon the preferences of the user and experience with the system. For instance, different exercises could be implemented that were based upon the same learning principle. The user might be given an exercise of writing a list in order of frequency or importance of as many of the important uncommon words in the text that might be represented as keywords. The user would only have a MCW extraction template to refer to during the exercise which would indicate words automatically eliminated from the list. After completing the exercise, the user would be provided a list of the uncommon words in the text sorted on the basis of frequency with which he would compare his responses. The objective of the user would not be to completely match the list, but rather, recall several keywords of the text, perhaps as many of 5 to 10, that would be confirmed by their presence on the uncommon word list. In doing this exercise, the user might want to raise the level of extraction from 300 MCW's to a substantially higher level depending on the nature of the text.