Abstract: A neural network for assertion-based scoring can include a support vector classifier and a plurality of sequential layers. The sequential layers can include, for example, a word embedding layer, a conventional layer, a recurrent layer, a dense layer, and/or a dropout layer. The neural network can be configured to perform a word-frequency count and/or can be configured to collect candidate words of various Levenshtein distances from standard-spelling variations.

Abstract: A system, method, and related techniques are disclosed for scoring user responses to constructed response test items. The system includes a scoring engine for receiving a user response to a test question and evaluating the response against a scoring rubric. The scoring rubric may include a binding stage, an assertion stage, and a scoring stage. Furthermore, the system includes a database for referencing elements used by the scoring engine which may comprise objects, object sets, attributes of objects, and transformations of any elements.

Abstract: A system, method, and related techniques are disclosed for scoring user responses to constructed response test items. The system includes a scoring engine for receiving a user response to a test question and evaluating the response against a scoring rubric. The scoring rubric may include a binding stage, an assertion stage, and a scoring stage. Furthermore, the system includes a database for referencing elements used by the scoring engine which may comprise objects, object sets, attributes of objects, and transformations of any elements.

Abstract: A system and method for administering tests at a computer terminal in communication with a remote location is provided. The method includes: establishing an initial threshold amount of questions, the initial threshold amount being a positive integer greater than one; sending to the computer terminal a first batch of questions that exceeds the threshold amount, the batch of questions having a substantially equal difficulty level; receiving an answer to one of the batch of questions; selecting, based on the answer to the one of the number of questions, a new question having a difficultly level different than the one of the number of questions; and sending the new question to the computer terminal.

Abstract: A construction and display of speech commands system that allows a user to simply read what is on an application that involves visual elements with which the user interacts, and in doing so, gives the appropriate commands to the speech recognition system for the task at hand. The construction and display of speech commands system may include a speech recognition system, a grammar builder module, and a speech enablement module. The construction and display of speech commands system may automatically generate a speech enabled application from generated speech grammar.

Abstract: A method for creating a page template corresponding to a form for use in a mark recognition system includes identifying at least one path of traversal across a form, detecting edge transitions along each such path, and creating page template using the detected edge transitions.

Abstract: A system, method, and related techniques are disclosed for scoring user responses to constructed response test items. The system includes a scoring engine for receiving a user response to a test question and evaluating the response against a scoring rubric. The scoring rubric may include a binding stage, an assertion stage, and a scoring stage. Furthermore, the system includes a database for referencing elements used by the scoring engine which may comprise objects, object sets, attributes of objects, and transformations of any elements.

Abstract: A system, method, and related techniques are disclosed for scoring user responses to constructed response test items. The system includes a scoring engine for receiving a user response to a test question and evaluating the response against a scoring rubric. The scoring rubric may include a binding stage, an assertion stage, and a scoring stage. Furthermore, the system includes a database for referencing elements used by the scoring engine which may comprise objects, object sets, attributes of objects, and transformations of any elements.