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: 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 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: 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: 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: 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: 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 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: 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 distributed processing method is disclosed herein for evaluating student work product. 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 an analysis results from the one or several independent processing units, and can update the result based on a value scoring the machine learning of the independent processing unit.

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: 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 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: 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 distributed processing method is disclosed herein for evaluating student work product. 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 an analysis results from the one or several independent processing units, and can update the result based on a value scoring the machine learning of the independent processing unit.

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 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 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 distributed processing method is disclosed herein for evaluating student work product. 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 an analysis results from the one or several independent processing units, and can update the result based on a value scoring the machine learning of the independent processing unit.

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.