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Systems and methods for semantic knowledge assessment, instruction and acquisition

A technology of knowledge and corpus, applied in the field of semantic knowledge evaluation and teaching system, can solve the problem of not measuring and evaluating the relative importance of vocabulary knowledge depth and so on

Inactive Publication Date: 2008-06-18
AI LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For example, traditional systems typically do not measure and assess (a) the relative importance of each individual unrecognized lexical term, and (b) the depth of lexical knowledge for individuals, population segments, and / or regional populations
Furthermore, most traditional systems do not include processes in place to organize ability-appropriate reading material based on each individual learner's assessed vocabulary ability
Furthermore, most traditional methods do not include proper procedures to assess retention of newly learned lexical entries

Method used

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  • Systems and methods for semantic knowledge assessment, instruction and acquisition
  • Systems and methods for semantic knowledge assessment, instruction and acquisition
  • Systems and methods for semantic knowledge assessment, instruction and acquisition

Examples

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Embodiment Construction

[0059] FIG. 1 is a block diagram illustrating a language assessment and teaching system 100 configured in accordance with an embodiment of the present invention. System 100 may include testing component 124 , compiling components 122 , 126 , 128 , 130 , and 132 , evaluating components 122 , 124 , and 132 , and providing component 116 configured to provide competency-appropriate language instructional material to users.

[0060] System 100 may include one or more corpus and subdomain databases 110 (only one shown) for storing any desired number of corpora and corresponding subdomains. The system 100 also includes a corpus program or module 112 for compiling the significance of the term data. Specifically, there are a set number of terms within each corpus and subdomain. The aggregate of all terms in each corpus or subdomain is called a vocabulary. The term "lemma" as used herein refers to any symbol, multi-symbol unit, sound, sound, word, multi-word unit or idiomatic expressi...

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Abstract

Systems and methods for semantic knowledge assessment, instruction, and acquisition are disclosed. In one embodiment a computer-implemented method for language instruction includes determining a lexical recognition ability level of a user within a lexicon of a particular language. This method further includes, based on item recognizability, creating a target list of unknown lexical items. The target list can be sorted by ranking the importance of the unknown lexical items within the particular lexicon. The method also includes generating a personal language learning sequence for the user based, at least in part, on the target list.

Description

[0001] This application claims priority to US Provisional Application No. 60 / 668,764, filed April 5, 2005, the contents of which are incorporated herein by reference (Attorney Docket No. 581458001US). technical field [0002] The following disclosure generally relates to systems and methods for semantic knowledge assessment and teaching. Background technique [0003] The field of linguistics includes a variety of pedagogical theories and approaches to language acquisition. Many traditional theories and methods are oriented toward rule-based grammatical concepts or processes. For example, standard grammar translation methods emphasize learning the syntax and structure of sentences. This approach assumes that once students have learned enough grammatical rules for constructing sentences, they will be able to place the appropriate vocabulary as needed to produce meaningful language. For example, the (habit formation-based) listening and speaking approach focuses primarily on ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G09B7/00G09B19/06G06F40/00
CPCG09B19/06G09B7/00
Inventor 盖伊·齐查尔斯·布朗布伦特·库里根大野孝司西岛淳戴维·朔伊费勒
Owner AI LTD
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