An exemplary system may include an augmented reality device with a user interface, a processor and memory having a program communicatively connected to the processor. A transceiver may be communicatively connected to a practitioner device for real-time practitioner guidance. The system may include a plurality of sensors and a feedback device in communication with the processor. The system may display initial and updated guidance objects in a real-time environment of the user and in response to sensor outputs of the plurality of sensors. The feedback device may provide at least one of audio, visual, and tactile feedback in response to the sensors outputs. The system may condition the user to provide a desired reaction by guiding the real-time user reactions in the real-time environment using the feedback in response to the sensor outputs.

An exemplary system may include an augmented reality device with a user interface, a processor and memory having a program communicatively connected to the processor. A transceiver may be communicatively connected to a practitioner device for real-time practitioner guidance. The system may include a plurality of sensors and a feedback device in communication with the processor. The system may display initial and updated guidance objects in a real-time environment of the user and in response to sensor outputs of the plurality of sensors. The feedback device may provide at least one of audio, visual, and tactile feedback in response to the sensors outputs. The system may condition the user to provide a desired reaction by guiding the real-time user reactions in the real-time environment using the feedback in response to the sensor outputs.

The system set forth herein relates to a network formed between an instructor device and one or more student devices where the system monitors sensors in the student devices to determine whether the student is distracted. The instructor is able to identify operating parameters for the system in the form of rules. The student devices must follow the rules, and where the system detects a rule violation, a warning may be issued to the instructor, student, or both. This allows students to have their mobile devices (such as cell phones or tablets) in class, and even use the mobile devices to participate in class, but also allows the instructor to remotely control and monitor how those student devices are being used.

The system set forth herein relates to a network formed between an instructor device and one or more student devices where the system monitors sensors in the student devices to determine whether the student is distracted. The instructor is able to identify operating parameters for the system in the form of rules. The student devices must follow the rules, and where the system detects a rule violation, a warning may be issued to the instructor, student, or both. This allows students to have their mobile devices (such as cell phones or tablets) in class, and even use the mobile devices to participate in class, but also allows the instructor to remotely control and monitor how those student devices are being used.

A system and method for characterizing, selecting, ordering and rendering discrete elements of digitized video content to teach communications and pedagogic skills. Each of a plurality of observed or computer-generated instances of modeling of distinguishable teaching skills are recorded as digitized assets. Microskills are identified and deconstructed in the abstract from one or more of the visual and audible recordings of teaching skills modeling moments. Identifiers of microskills are associated by a human editor with recorded modeling instances and/or portions thereof. Modeling presentations are dynamically generated by a user asserting one or more microskill identifiers and a network-enabled selection, ordering and rendering of portions of modeling instances that are associated with the asserted microskill identifiers.

A system and method for characterizing, selecting, ordering and rendering discrete elements of digitized video content to teach communications and pedagogic skills. Each of a plurality of observed or computer-generated instances of modeling of distinguishable teaching skills are recorded as digitized assets. Microskills are identified and deconstructed in the abstract from one or more of the visual and audible recordings of teaching skills modeling moments. Identifiers of microskills are associated by a human editor with recorded modeling instances and/or portions thereof. Modeling presentations are dynamically generated by a user asserting one or more microskill identifiers and a network-enabled selection, ordering and rendering of portions of modeling instances that are associated with the asserted microskill identifiers.

An automated marketing and training regimen for certifying instructors and allowing same to create a microbusiness via a microsite and a technology software platform for implementing and supporting same.

An educational apparatus has a controller linked with student devices, and a teacher device. Each student device is in the form of a desk with a board, a touch sensor array in the board, a display physically separate from the array, and permanent indicia. The apparatus recognises touch by a student on the board, and this is mapped to content of an overlay sheet of paper placed on the board. Moreover, multiple devices may be juxtaposed, and events may be recognised based on all of the group of devices together. An example is a paper sheet covering four devices together and having a map printed on it, in which the software recognised a particular location of touch on a particular device as being a specific region on the map.

An educational apparatus has a controller linked with student devices, and a teacher device. Each student device is in the form of a desk with a board, a touch sensor array in the board, a display physically separate from the array, and permanent indicia. The apparatus recognises touch by a student on the board, and this is mapped to content of an overlay sheet of paper placed on the board. Moreover, multiple devices may be juxtaposed, and events may be recognised based on all of the group of devices together. An example is a paper sheet covering four devices together and having a map printed on it, in which the software recognised a particular location of touch on a particular device as being a specific region on the map.

A distance learning device for providing laboratory instruction via two-way interaction with a student at a remote location and system for using same.