A system that coordinates pickups of entities to be picked up includes a number of monitor devices, a number of authorized pickup entity devices, at least one communications network, at least one time to arrival estimation server, at least one coordination server, and at least one administration server. Each of the time to arrival estimation server, coordination server, and administration server may have respective databases stored on respective nontransitory computer- or processor-readable media. The coordination server permits interaction between the monitor devices and authorized pickup entity devices while maintaining privacy of entities logically associated with such devices and while addressing a plurality of technical problems that one of ordinary skill in the art may face when implementing the system that coordinates pickups.

A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein are directed to a Course Ingestion Engine (hereinafter “C.I. Engine”) that extracts a least a portion of a word present in a course description of an online course. The C.I. Engine determines, based on the at least one extracted portion of the word, at least one skill defined in a social networking service that can be acquired from content of the online course. The C.I. Engine recommends the online course to a target member account of the social networking service.

A method for pushing a data within a template in an educational setting comprising: scanning, via a first user device, a first tag, said first user device having first a unique ID and said first tag being a master tag and comprising a first tag ID; scanning, via a second user device, a second tag, said second user device having a second unique ID and said second tag having a second tag ID and being controlled by said master tag; defining a template being loaded onto said second user device upon the scanning of the second tag; and wherein the template comprises data corresponding to said second tag ID, said second unique ID, and a time corresponding to the scanning of said second tag.

A childhood development system may capture audio and video in a home environment in which a child resides. The captured audio and the captured video may be filtered to remove audio and video corresponding to persons other than the child. Based upon information from the filtered video and the filtered audio, multiple scores can be calculated for the child using multiple trained machine-learning models. The scores can be compared with various stored activity score bundles. An indication of one or more compatible activities mapped to the activity score bundles that best match the child's scores is output.

Provided are techniques for automatically enhancing content items through identifying relationships. One or more content items and an associated transcript for each of the one or more content items are received. One or more terms are identified in the one or more content items. A content tree is built for each of the one or more content items using the one or more terms and corresponding contexts. A content graph is built using each content tree. One or more subgraphs of the content graph are identified. One or more paths through each of the one or more subgraphs are identified and one or more content expansion recommendations are provided. In response to selection of a content item, the one or more paths are used to provide an enhanced content item with one or more prerequisite content items and one or more subsequent content items.

A system that providing an interactive means for one or more team members to learn about and better-react to opponents in upcoming games is provided. The system operates by repeatedly running drill sessions having a dynamic difficulty, where the difficulty is automatically set, based on the success of the player performing the drill session, and other characteristic about the player.

A system and a method for connecting a tutor with a student in real time. Initially, the system receives a student profile. Further, the system receives a question from the student. Furthermore, the system synthesizes the question based on a set of predefined machine learning model. Subsequently, the system determines a cohort of the students from the set of the cohort of the students. The cohort of the students is determined based on the one or more parameters related to the question. Further, the system identifies a tutor assigned to the cohort of the students. Subsequently, the system notifies the tutor in real time. Further, the system receives an acknowledgement from the tutor within a predefined time. Finally, the system connects the tutor with the student in real time when the acknowledgement is the positive acknowledgement.

The present invention relates to software and a method of use for implementing workflows and managing engagements and staff. More particularly, the present invention relates to a software module tracking data of staff, engagements and workflows and a method of using such data in the management of staff and assignment of tasks. Information concerning employees is input into a database by the manager and the employees, and is tracked therein. The information concerning an employee includes an employee's availability, ability and experience. Workflow/Task information is input into the database when either a client makes a request for service of the business, or a workflow/task internal to the business is needed to be performed. Task information includes the nature of the work and deadlines. Task information is compared to the employee information. A list is automatically generated naming the employees best suited to the mandate of the task. The manager then chooses a name from the top of the list and assigns the task to that employee.

The methods, apparatus, and systems described herein facilitate decision-making by providing predictions of student outcomes and behaviors. The methods include receiving a communication posted by a student, identifying keywords in text of the communication associated with one or more student metrics, scoring the communication for at least one student metric, and predicting a likelihood of a student outcome based on the score.

A system for objective assessment of learning outcomes comprising a data repository comprising at least a hierarchical arrangement of a plurality of learning goals, a report generator coupled to the data repository, an analysis engine coupled to the data repository, a rules engine coupled to the data repository, and an application server adapted to receive application-specific requests from a plurality of client applications and coupled to the data repository. The application server is further adapted to provide an administrative interface for viewing, editing, or deleting a plurality of learning goals and relationships between them, learning assessment tools, learning outcome reports, and learning indexes, and the rules engine performs a plurality of consistency checks to ensure alignment between and among learning goals, learning assessment tools, learning outcomes, and learning indexes. The application server receives learning assessment data and the analysis engine performs analyses to generate a plurality of learning indexes.