In one example embodiment of the invention, a simulation based training system is provided having a sensor that unobtrusively collects objective data for individuals and teams experiencing training content to determine the cognitive states of individuals and teams; time-synchronizes the various data streams; automatically determines granular and objective measures for individual cognitive load (CL) of individuals and teams; and automatically determines a cognitive load balance (CLB) and a relative cognitive load (RCL) measure in real or near-real time. Data is unobtrusively gathered through physiological or other activity sensors such as electroencephalogram (EEG) and electrocardiogram (ECG) sensors. Some embodiments are further configured to also include sociometric data in the determining cognitive load. Sociometric data may be obtained through the use of sociometric badges. Some embodiments further automatically customize the simulation content by automatically selecting content based on the CL of the individuals and teams.

In one example embodiment of the invention, a simulation based training system is provided having a sensor that unobtrusively collects objective data for individuals and teams experiencing training content to determine the cognitive states of individuals and teams; time-synchronizes the various data streams; automatically determines granular and objective measures for individual cognitive load (CL) of individuals and teams; and automatically determines a cognitive load balance (CLB) and a relative cognitive load (RCL) measure in real or near-real time. Data is unobtrusively gathered through physiological or other activity sensors such as electroencephalogram (EEG) and electrocardiogram (ECG) sensors. Some embodiments are further configured to also include sociometric data in the determining cognitive load. Sociometric data may be obtained through the use of sociometric badges. Some embodiments further automatically customize the simulation content by automatically selecting content based on the CL of the individuals and teams.

Systems and methods are provided for compensating contributors, comprising writers, editors, and reviewers, of assessment items, comprising questions, answers, and answer explanations. The systems and methods presented comprise hardware architecture, computer-implemented processes, and instructions configured to carry out the processes for compensating contributors. A user may use the systems and methods to contribute assessment items, to take assessment items in an assessment, to select or have selected assessment items for an assessment, and/or to provide information related to assessment items. The present invention solves problems with the currently available systems and methods of compensating contributors of assessment items.

Methods, apparatuses, and systems for more efficiently assessing the performance of a person on a test or at completing a task. The disclosure is directed to systems, apparatuses, and methods for training a model to jointly predict (a) test item annotations (e.g., a domain or subject-matter expert's assessment of the difficulty level of a test item) and (b) test-taker responses. The disclosed approach may be used to estimate item parameters used in tests for evaluating the proficiency of a test taker, and more specifically, as part of a language proficiency test or examination.

Methods, apparatuses, and systems for more efficiently assessing the performance of a person on a test or at completing a task. The disclosure is directed to systems, apparatuses, and methods for training a model to jointly predict (a) test item annotations (e.g., a domain or subject-matter expert's assessment of the difficulty level of a test item) and (b) test-taker responses. The disclosed approach may be used to estimate item parameters used in tests for evaluating the proficiency of a test taker, and more specifically, as part of a language proficiency test or examination.

An automated method of assembling computerized adaptive test (CAT) pools of test items is provided. A plurality of item bins is created. Each item bin is associated with a different content domain, and each item bin includes only items associated with its respective content domain. The items in each item bin are grouped into a plurality of individual cells, wherein each item is placed in only one of the individual cells, and each cell includes a plurality of items which span a range of difficulty levels. The grouping is performed by linear programming at the individual cell level. One or more pools of items are assembled from a random selection of cells across the item bins, wherein there is only one cell for each item bin. The CAT is administered by randomly assigning each test taker to one of the pools of items.

An automated method of assembling computerized adaptive test (CAT) pools of test items is provided. A plurality of item bins is created. Each item bin is associated with a different content domain, and each item bin includes only items associated with its respective content domain. The items in each item bin are grouped into a plurality of individual cells, wherein each item is placed in only one of the individual cells, and each cell includes a plurality of items which span a range of difficulty levels. The grouping is performed by linear programming at the individual cell level. One or more pools of items are assembled from a random selection of cells across the item bins, wherein there is only one cell for each item bin. The CAT is administered by randomly assigning each test taker to one of the pools of items.

A computer access control system includes a client electronic device configured to administer an alertness test to a user. A computer access controller is coupled to and configured to be actuated by the client electronic device.

A method of operating a motor vehicle includes detecting at least one motor vehicle driver response, producing a perception model based on the detected motor vehicle driver response, and analyzing the perception model to at avoid least one motor vehicle driver response by adjusting a parameter of the motor vehicle. Analysis of the perception model can also be carried out to predict a motor vehicle driver response, in particular during the generation of new control software for the vehicle.

A method of operating a motor vehicle includes detecting at least one motor vehicle driver response, producing a perception model based on the detected motor vehicle driver response, and analyzing the perception model to at avoid least one motor vehicle driver response by adjusting a parameter of the motor vehicle. Analysis of the perception model can also be carried out to predict a motor vehicle driver response, in particular during the generation of new control software for the vehicle.