Abstract: A method comprising accessing a first data structure that is associated with a first product prepared by a student and that includes first process data associated with a process performed by the student in generating the first product, analyzing the first data structure to generate a first characterization score based on the first product and the first process data, accessing a second data structure that is associated with a second product prepared by the student and that includes second process data associated with a process performed by the student in generating the second product, analyzing the second data structure to generate a second characterization score based on the second product and the second process data, and calculating a skill level change metric based on the first characterization score and the second characterization score indicating a change in ability level of the student over a course of the scenario-based assessment.

Abstract: Systems and methods for defining and using an optimal burst boundary threshold to assess the reliability of a manual/automatic writing score are presented. Keystroke data, including inter-key interval data, such as inter-word interval data, may be gathered from writings. Clustering analyses may be performed on the inter-key interval data to determine an optimal number of bursts for the writings. An optimal burst boundary may be determined from the optimal number of bursts. Other burst-related measures and statistics, including the average and maximum burst lengths, may be determined from the writings based on the optimal burst boundary threshold. A score may be received for each of the writings. A validation indication metric may be generated for each of the writings based on the received score and the optimal burst boundary threshold. The resulting measures and statistics may be used or applied in different ways and provide personalized feedback as learning analytics.

Abstract: Systems and methods are provided for providing feedback on a user's writing behavior in generating a constructed response. An electronic process log for the constructed response is received. The electronic process log is processed to generate a vector having a predetermined number of elements. The vector comprises information related to the user's actions in generating the constructed response and includes (i) data indicating types of actions performed by the user in generating the constructed response, (ii) time points associated with the actions, and (iii) locations associated with the actions, each location indicating whether an associated action occurred within a word, between words, within a phrase, between phrases, within a sentence, between sentences, within a paragraph, or between paragraph. The vector is compared to one or more vectors associated with other constructed responses, and feedback is generated based on the comparison.

Abstract: A method and system for using a natural language generator for automatic assessment item generation is disclosed. The natural language generator includes a document structure generator that produces an abstract document specification defining a structure for an assessment item based on user input. The abstract document specification is input into a logical schema generator, which produces a logical schema specification that creates a more detailed specification for an assessment item. Finally, a sentence generator receives the logical schema specification and creates natural language for the assessment item based on the variables defined in the logical schema specification.

Abstract: Systems and methods are provided for scoring a constructed response generated by a user and providing information on the user's writing behavior. A constructed response and associated electronic process log are received. The constructed response is processed to generate first feature values representative of aspects of the constructed response. The electronic process log is processed to generate second feature values related to the user's actions in generating the constructed response. A score for the constructed response is generated using the processing system by applying a computer scoring model to the first and second feature values. A rule of a rule engine that is satisfied is identified, the rule being satisfied when one or more feature values of the second feature values meet a condition associated with the rule. Information on the user's actions in generating the constructed response is provided based on the satisfied rule.

Abstract: Systems and methods are provided for scoring a constructed response generated by a user and providing information on the user's writing behavior. A constructed response and associated electronic process log are received. The constructed response is processed to generate first feature values representative of aspects of the constructed response. The electronic process log is processed to generate second feature values related to the user's actions in generating the constructed response. A score for the constructed response is generated using the processing system by applying a computer scoring model to the first and second feature values. A rule of a rule engine that is satisfied is identified, the rule being satisfied when one or more feature values of the second feature values meet a condition associated with the rule. Information on the user's actions in generating the constructed response is provided based on the satisfied rule.

Abstract: Systems and methods are provided for non-monotonic recognition of phrasal terms. Phrasal terms are identified from a corpus of written materials and ranked based on, for example, a mutual rank ratio. The phrasal terms are sequentially selected and a determination is made as to whether to accept or reject the selected phrasal term based on at least one predetermined criteria. The ranking of the phrasal terms may also rely on linguistic support to reduce duplication of phrasal terms and to distinguish different confidence levels for identified and accepted phrasal terms.

Abstract: A dental charting system having a control device configured to be held by a user or which is mounted to another device held by a user and the control device including one or more movement sensors for sensing movement of the control device in space and generating representative movement signals. A gesture processing module is provided to receive and process the movement signals to detect the occurrence of a gesture event from a set of predetermined gesture events, and which generates representative gesture control signals. A dental charting application program is also provided and runs on a host device and which provides a graphic user interface on a display associated with the host device for interacting with the application program, the application program being configured to receive and process the gesture control signals to enable interaction with the graphic user interface by the user via hand gesture movements of the control device.

Abstract: Systems and methods are provided for non-monotonic recognition of phrasal terms. Phrasal terms are identified from a corpus of written materials and ranked based on, for example, a mutual rank ratio. The phrasal terms are sequentially selected and a determination is made as to whether to accept or reject the selected phrasal term based on at least one predetermined criteria. The ranking of the phrasal terms may also rely on linguistic support to reduce duplication of phrasal terms and to distinguish different confidence levels for identified and accepted phrasal terms.

Abstract: A method and system for performing automatic text analysis is described. A local ranking for one or more contexts with respect to a word and a global ranking for one or more contexts are generated. The rankings are based on the frequency with which the contexts appear in a corpus. A statistic may be generated using the local and global rankings, such as a log ratio rank statistic equal to the logarithm of the global rank divided by local rank, to measure the similarity of contexts with respect to words with which they combine. A source matrix of word to context values is then created. Singular value decomposition is used to create sub-matrices from the source matrix. Vectors from the sub-matrices corresponding to context(s) and/or word(s) are then selected to determine term-term or context-context similarity or term-context correspondence.

Abstract: A method and system for determining a lexical association of phrasal terms are described. A corpus having a plurality of words is received, and a plurality of contexts including one or more context words proximate to a word in the corpus is determined. An occurrence count for each context is determined, and a global rank is assigned based on the occurrence count. Similarly, a number of occurrences of a word being used in a context is determined, and a local rank is assigned to the word-context pair based on the number of occurrences. A rank ratio is then determined for each word-context pair. A rank ratio is equal to the global rank divided by the local rank for a word-context pair. A mutual rank ratio is determined by multiplying the rank ratios corresponding to a phrase. The mutual rank ratio is used to identify phrasal terms in the corpus.

Abstract: A method and system for determining a lexical association of phrasal terms are described. A corpus having a plurality of words is received, and a plurality of contexts including one or more context words proximate to a word in the corpus is determined. An occurrence count for each context is determined, and a global rank is assigned based on the occurrence count. Similarly, a number of occurrences of a word being used in a context is determined, and a local rank is assigned to the word-context pair based on the number of occurrences. A rank ratio is then determined for each word-context pair. A rank ratio is equal to the global rank divided by the local rank for a word-context pair. A mutual rank ratio is determined by multiplying the rank ratios corresponding to a phrase. The mutual rank ratio is used to identify phrasal terms in the corpus.

Abstract: A method and system for determining a lexical association of phrasal terms are described. A corpus having a plurality of words is received, and a plurality of contexts including one or more context words proximate to a word in the corpus is determined. An occurrence count for each context is determined, and a global rank is assigned based on the occurrence count. Similarly, a number of occurrences of a word being used in a context is determined, and a local rank is assigned to the word-context pair based on the number of occurrences. A rank ratio is then determined for each word-context pair. A rank ratio is equal to the global rank divided by the local rank for a word-context pair. A mutual rank ratio is determined by multiplying the rank ratios corresponding to a phrase. The mutual rank ratio is used to identify phrasal terms in the corpus.

Abstract: A method and system for performing automatic text analysis is described. A local ranking for one or more contexts with respect to a word and a global ranking for one or more contexts are generated. The rankings are based on the frequency with which the contexts appear in a corpus. A statistic may be generated using the local and global rankings, such as a log ratio rank statistic equal to the logarithm of the global rank divided by local rank, to measure the similarity of contexts with respect to words with which they combine. A source matrix of word to context values is then created. Singular value decomposition is used to create sub-matrices from the source matrix. Vectors from the sub-matrices corresponding to context(s) and/or word(s) are then selected to determine term-term or context-context similarity or term-context correspondence.

Abstract: A method and system for performing automatic text analysis is described. A local ranking for one or more contexts with respect to a word and a global ranking for one or more contexts are generated. The rankings are based on the frequency with which the contexts appear in a corpus. A statistic may be generated using the local and global rankings, such as a log ratio rank statistic equal to the logarithm of the global rank divided by local rank, to measure the similarity of contexts with respect to words with which they combine. A source matrix of word to context values is then created. Singular value decomposition is used to create sub-matrices from the source matrix. Vectors from the sub-matrices corresponding to context(s) and/or word(s) are then selected to determine term-term or context-context similarity or term-context correspondence.

Abstract: A natural language system searching system develops concept and string indexes of a textual database, such as a group of litigation documents, by breaking the text to be indexed into sentences, words, dates, names and places in a reader, identifying phrases in a phrase parser, recovering word stems in a morphology module and determining the sense of potentially ambiguous words in a sense selector, all in accordance with words and concepts (word senses) stored in lexicon database 9-32. A query may then be processed by the reader, phrase parser, morphology module, and sense selector to provide a text meaning output which can be compared with the concept and string indexes to identify, retrieve and display documents and/or portions of documents related to the query. A lexicon enhancer adds vocabulary semi-automatically.

Abstract: This invention relates to a drinks dispenser, and in particular to a drinks dispenser suitable for use at commercial premises such as a bar or public house for serving beer and the like. According to the invention there is provided a drinks dispenser comprising a frame (14) carrying at least one tap (20), the frame being connected to a column (12) within which can be located a conduit (52) for delivering liquid to the tap, the frame having connectors (30) by which separate and additional frame(s) (16) may be connected thereto, a separate cover (76) being provided which can be mounted upon the frame means. The drinks dispenser is therefore modular in construction, with the frame(s) providing the structural strength of the dispenser and the cover(s) fulfilling the aesthetic requirements.

Abstract: A method and system for determining a lexical association of phrasal terms are described. A corpus having a plurality of words is received, and a plurality of contexts including one or more context words proximate to a word in the corpus is determined. An occurrence count for each context is determined, and a global rank is assigned based on the occurrence count. Similarly, a number of occurrences of a word being used in a context is determined, and a local rank is assigned to the word-context pair based on the number of occurrences. A rank ratio is then determined for each word-context pair. A rank ratio is equal to the global rank divided by the local rank for a word-context pair. A mutual rank ratio is determined by multiplying the rank ratios corresponding to a phrase. The mutual rank ratio is used to identify phrasal terms in the corpus.

Abstract: A method and system for performing automatic text analysis is described. A local ranking for one or more contexts with respect to a word and a global ranking for one or more contexts are generated. The rankings are based on the frequency with which the contexts appear in a corpus. A statistic may be generated using the local and global rankings, such as a log ratio rank statistic equal to the logarithm of the global rank divided by local rank, to measure the similarity of contexts with respect to words with which they combine. A source matrix of word to context values is then created. Singular value decomposition is used to create sub-matrices from the source matrix. Vectors from the sub-matrices corresponding to context(s) and/or word(s) are then selected to determine term-term or context-context similarity or term-context correspondence.

Abstract: A method and system for using a natural language generator for automatic assessment item generation is disclosed. The natural language generator includes a document structure generator that produces an abstract document specification defining a structure for an assessment item based on user input. The abstract document specification is input into a logical schema generator, which produces a logical schema specification that creates a more detailed specification for an assessment item. Finally, a sentence generator receives the logical schema specification and creates natural language for the assessment item based on the variables defined in the logical schema specification.