Abstract: Techniques described herein relate to analyzing executions of content resources within networks of execution client devices, and selecting sets of interactive content resources for execution on particular execution devices based on such analyses. Content resource execution data may be received from various execution client devices on which content resources have been executed and provided to end users. Such data may be analyzed to determine correlations between a first content executor and additional content executors based on the their respective content resource execution data, and the content resource execution data of correlated content executors may be aggregated and analyzed to select particular interactive content resources for the first content executor. Such selections may be provided to first content executor during a content execution session following an authenticated login by the first content executor.

Abstract: Systems and methods for content selection with first and second recommendation engines are disclosed herein. The system can include a memory include a content library database and a model database. The system can include a user device having a first network interface and a first I/O subsystem. The system can include one or more servers that can include a packet selection system and a presentation system. These one or more servers can: receive response data from the user device; provide received response data to a first recommendation engine; alert a second recommendation engine when a selected next node is a placeholder node; retrieve at least one statistical model relevant to selection of next node content; and select next node content based on an output of the at least one statistical model.

Abstract: Systems and methods for automated aggregated content commenting are disclosed herein. Such a system can include a memory including a content database; an evaluation criteria database; and a comment database. The system can include at least one server. The at least one server can: receive a content identifier; receive a user identifier; provide a representation of the piece of content to the user; receive a comment from the user identifying a portion of the piece of content; generate a portion of the comment database linked to the user and the content; generate an entry in the portion of the comment database linked to the user and the content; and store the comment in the entry in the portion of the comment database.

Abstract: A system includes one or more server hardware computing devices includes one or more processors and memory storing instructions that, when executed by the one or more processors, cause the system to receive a request to verify an identity of a user attempting to complete an examination provided by an online proctored examination platform to a candidate user authorized to complete the examination and repeatedly, at a predefined interval during the examination, determine, based at least in part on user data collected by the online proctored examination platform during the examination, the user data identifying the user at a time that the interval elapses, whether the user is the candidate user, and, responsive to a determination that the user is not the candidate user, perform one or more of a plurality of actions associated with a failed identity verification, the plurality of actions including stopping the examination.

Abstract: A file receiver receives an electronic structure file that includes structure-file data associated with a spatial arrangement and detects a content object for processing that includes content-object data. A file transformation engine transforms the structure-file data from the structure file into an electronic record. A rendering engine renders an image of the transformed structure-file data arranged in the spatial arrangement. An interface engine detects an input corresponding to specification of a position of a data segment. A parsing engine defines a segment-position specification indicative of the position. A template engine generates an electronic template that associates an identifier of the data segment with the segment-position specification and associates the electronic template with a template identifier. A record classifier determines that the content object corresponds to the template identifier.

Abstract: Systems and methods for accelerated stabilization of data packet metadata are disclosed herein. The system can include a memory having a content database and a user profile database. The system can include a user device having a first network interface and a first I/O subsystem. The system can include one or more servers. The one or more servers can: retrieve data packet metadata for a data packet; determine that the data packet metadata is unstable; identify a set of potential recipients of the data packet; select one of the set of potential recipients as the recipient of the data packet; provide the data packet to the recipient of the data packet; receive a response from the recipient to the provided data packet; and automatically update the data packet metadata based on the response received from the recipient.

Abstract: Techniques described herein relate to requesting and receiving adaptive content resources from content management servers and other content repositories, executing the adaptive content resources on one or more user devices, and performing caching determinations and caching behaviors based on the execution of the adaptive content resources. In some embodiments, content resources may be executed on user devices in a content distribution network. User inputs may be received in connection with the execution of the adaptive content resources, and a user context may be determined based on user interactions and feedback during execution of the adaptive content resources. Additional content resources may be requested and received from content repositories for caching within user devices based on the determined user context.

Abstract: An improved machine learning system is provided. For example, a content management server may provide real-time analysis of a user's handwriting to assess the user's knowledge of a language, including using a convolution neural network method. The convolution neural network method may be executed to normalize at least some identified strokes in the user's handwritten user input. Normalization may be performed by translating a window comprising a subset of pixels in a digital representation of the handwritten user input amongst a plurality of pixels in the digital representation.

Abstract: Systems and methods for content provisioning are disclosed herein. The system can include memory having a content database, a task database, and a user profile database. The system can include a user device having a first network interface and a first I/O subsystem. The system can include a server that can: receive a user identifier from the user device; retrieve user information from the user profile database, which user information identifies one or several attributes of the user; retrieve user task data from the task database, which user task data identifies a plurality of tasks for completion by the user; automatically generate prioritization data for the plurality of tasks identified by the user task data; select a task based on the prioritization data; and send content relating to the selected task to the user device.

Abstract: A distributed processing system is disclosed herein. The distributed processing system includes a server, a database server, and an application server that are interconnected via a network, and connected via the network to a plurality of independent processing units. The independent processing units can include an analysis engine that is machine-learning-capable, and thus uniquely completes its processing tasks. The server can provide one or several pieces of data to one or several of the independent processing units, can receive analysis results from these one or several independent processing units, and can update the result based on a value characterizing the machine learning of the independent processing unit.

Abstract: Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.

Abstract: A system includes a candidate device including a processor configured to implement a candidate evaluation software application and a server computer configured to communicate with the candidate device using a network. The server computer is configured to receive, from the candidate device, a request to access an evaluation service. The request includes a candidate identifier. The server computer is configured to access historical candidate data in a memory accessible by the server computer to determine a trust score for a candidate associated with the candidate identifier, and when the trust score exceeds a threshold, transmit a credential to the candidate device enabling an evaluation of the candidate to be performed on the candidate device via a secured local area network.

Abstract: Techniques are disclosed for detecting, tracking, and recording data associated with physical manipulatives in a physical environment, and a corresponding set of virtual manipulatives in a virtual environment. Physical manipulative sensor devices may be configured to detect the position and/or movements of physical manipulatives within a physical environment, including simple or multi-step user interactions with physical manipulatives. The sensor devices and/or associated user computing devices may use the sensor data to determine updated positions, orientations, and configurations for one or more physical manipulatives within the physical environment, as well as defining relationships between sets of the physical manipulatives.

Abstract: Systems and methods are provided by which information such as text may be extracted from a captured digital image, and displayed as an editable overlay over the captured digital image in a digital user interface. One or more boundaries defining a region or regions of the captured digital image from which information is extracted may be displayed over the captured digital image, and may be selectively added, edited, or deleted, resulting in corresponding information in the editable overlay being added, edited, or deleted. Additionally, information in the editable overlay may be added, edited, or deleted directly. The extracted information may correspond to responses to a homework assignment or test depicted in the captured digital image. The extracted information may be arranged in ordered steps, with the order of the steps being editable, and individual steps being removable, addable, or otherwise editable via interaction with the user interface.

Abstract: A method/apparatus/system for generating a request for improvement of a data object in a neural network is described herein. The neural network contains a plurality of data objects each made of an aggregation of content. The data objects of the neural network are interconnected based on one or several skill levels embodied in the content of the data objects via a plurality of connecting vectors. These connecting vectors can be generated and/or modified based on data collected from the iterative transversal of the connecting vectors by one or several users of the neural network.

Abstract: Systems, device configurations, and processes for a server to receive, from a user interface (UI) on a client, a request to generate a list from a selection of: an objective, vocabulary item, and/or grammar point mapped to a range of competency scores, and an audience. The server then selects data records storing data for the objective, vocabulary item or grammar point. The server then renders, for transmission and display on the client, a user interface control including a list of data for the objective, grammar point, and/or vocabulary item.

Abstract: Techniques relate to managing digital credentials. An operation evaluation system monitors, using sensors configured to detect physical attributes of a user in a physical environment, physical attributes of the user while the user performs a user action in a testing environment. Data corresponding to the physical attributes of the user is transmitted to one or more digital credential generators. A digital credential template associated with at least one of the physical attributes of the user is determined. For the digital credential template, a criteria associated with the digital credential template is retrieved and compared to the physical attributes. Based on the comparison, whether or not the user is eligible to receive a digital credential is determined based on the digital credential template, and, in response to determining that the user is eligible to receive a digital credential based on the digital credential template, a digital credential is generated.

Abstract: Systems and methods of the present invention provide for: receiving a digital image data; modifying the digital image data to reduce a width of a feature within the digital image data; executing a dimension reduction process on the feature; storing a feature vector comprising: at least one feature for each of the received digital image data, and a correct or incorrect label associated with each feature vector; selecting the feature vector from a data store; training a classification software engine to classify each feature vector according to the label; classifying the image data as correct or incorrect according to a classification software engine; and generating an output labeling a second digital image data as correct or incorrect.

Abstract: Systems and methods for automated objective identification are disclosed herein. The system can include a user device and a memory. The memory can include a filed database including field data associated with previously identified objectives. The memory can include a scoring database containing a machine-learning scoring algorithm. The system can include at least one server that can receive an identifier of a content portion, extract field information identifying at least one attribute of the identified content portion from the content portion, input extracted field information into the machine-learning scoring algorithm; receive identification of objectives forming a set of objectives from the machine-learning scoring algorithm; sort the objectives forming the set of objectives according to scores generated for each of the objectives in the set of objectives; and output the sorted objectives to the user device.