Abstract: Biometric keystroke measure data derived from a computer-implemented long form examination taken by an examinee is received. Features are the extracted from the biometric keystroke measure data for the examinee. A similarity value is then determined, using one or more of a direct distance approach or a machine learning approach, for the extracted features relative to features extracted from biometric keystroke measure data derived from each of a plurality of other examinees while taking the long form examination. At least one of the determined similarity values is then identified having a value above a pre-defined threshold. The pre-defined threshold indicates a likelihood of the examinee being the same as one of the other examinees. Data can then be provided that characterizes the identification. Related apparatus, systems, techniques and articles are also described.

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: 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: Exemplary data structures designed for log files of game/simulation-based educational assessments are described. An exemplary data structure may comprise at least one session element representing an assessee's participation in an educational assessment session; a session identification element identifying the educational assessment session represented by the session element; an assessee identification element identifying the assessee participating in the educational assessment session represented by the session element; an events element representing a collection of events occurring in the educational assessment session represented by the session element; an event element representing one event in the collection of events; an event time element indicting a time associated with the event; an event performer element indicating a performer of the event; an event target element indicating a target of the event; and an event result element representing a result of the event.