Abstract: Systems and methods of the present invention provide for: selecting a word pair and a category, concept, or sample response from a data store; performing a data extraction on a first knowledge base, including an article or content associated with a word in the word pair or a list of articles linking to the category, concept, or sample response; inserting words generated from the data extraction into a data store; defining a difficulty level for each of the words according to a crawl of difficulty data in a second knowledge base; and rendering a GUI displaying the words and the difficulty level for each of the words.

Abstract: Techniques described herein relate to performing diagnostic analyses including execution and evaluations of visual-spatial diagnostic content resources. A store of visual-spatial diagnostic content resources may be analyzed to determine the presence or absence of predetermined visual features, and mathematical modeling and/or machine-learning techniques may be used to calculate item parameter metrics for each visual-spatial diagnostic content resource. Thereafter, diagnostic sessions may proceed by selecting and presenting sequences of visual-spatial diagnostic content resources within an appropriate range of difficulty metrics, depending on the content recipient and performance on the previously-transmitted visual-spatial diagnostic content resources.

Abstract: Systems and methods of the present invention provide for: selecting a word pair and a category, concept, or sample response from a data store; performing a data extraction on a first knowledge base, including an article or content associated with a word in the word pair or a list of articles linking to the category, concept, or sample response; inserting words generated from the data extraction into a data store; defining a difficulty level for each of the words according to a crawl of difficulty data in a second knowledge base; and rendering a GUI displaying the words and the difficulty level for each of the words.

Abstract: Systems and methods of the present invention provide for: selecting a word pair and a category, concept, or sample response from a data store; performing a data extraction on a first knowledge base, including an article or content associated with a word in the word pair or a list of articles linking to the category, concept, or sample response; inserting words generated from the data extraction into a data store; defining a difficulty level for each of the words according to a crawl of difficulty data in a second knowledge base; and rendering a GUI displaying the words and the difficulty level for each of the words.

Abstract: Techniques described herein relate to performing diagnostic analyses including execution and evaluations of visual-spatial diagnostic content resources. A store of visual-spatial diagnostic content resources may be analyzed to determine the presence or absence of predetermined visual features, and mathematical modeling and/or machine-learning techniques may be used to calculate item parameter metrics for each visual-spatial diagnostic content resource. Thereafter, diagnostic sessions may proceed by selecting and presenting sequences of visual-spatial diagnostic content resources within an appropriate range of difficulty metrics, depending on the content recipient and performance on the previously-transmitted visual-spatial diagnostic content resources.

Abstract: Systems and methods of the present invention provide for: selecting a word pair and a category, concept, or sample response from a data store; performing a data extraction on a first knowledge base, including an article or content associated with a word in the word pair or a list of articles linking to the category, concept, or sample response; inserting words generated from the data extraction into a data store; defining a difficulty level for each of the words according to a crawl of difficulty data in a second knowledge base; and rendering a GUI displaying the words and the difficulty level for each of the words.