Abstract: A system and method is provided for monitoring and aggregating, via a network, performance information that indicates scholastic achievement and electronic communications of students participating in an online group learning course, conducted electronically via the network during a course term, in which the students are initially grouped into groups and then regrouped during the course term based on the aggregated performance information, according to an implementation of the invention. The performance information may indicate a performance of a student in the course. The system may provide electronic tools to users. The system may monitor the tools to determine communication and social activity, as well as academic achievement of the students. The communication activity, social activity, and the academic achievement may be used to dynamically regroup students during a course term.

Abstract: A knowledge acquisition system and artificial cognitive declarative memory model to store and retrieve massive student learning datasets. A Deep Academic Learning Intelligence system for machine learning-based student services provides monitoring and aggregating performance information and student communications data in an online group learning course. The system uses communication activity, social activity, and the academic achievement data to present a set of recommendations and uses responses and post-recommendation data as feedback to further train the machine learning-based system.

Abstract: A system and method provide continuous workforce optimization based on observations of users in an online learning management system integrated with physical learning nodes that can be interconnected with other physical learning nodes for multi-site workforce optimizations. The system provides online group learning courses to users via a network. The system may integrate with conventional physical classrooms, which may be physically located at different institutions, allowing for cross-site (e.g., cross-university, cross-military unit, cross-corporation, etc.) collaborative learning. The system may monitor user interactions during the online group learning courses and generate user profiles based on the user interactions. For example, for students (e.g., military personnel) training in cyber warfare using the online group learning courses, the system may track their performance via the monitored interactions, and place them into workforces to address cyber warfare needs.

Abstract: A system and method is provided for monitoring and aggregating, via a network, performance information that indicates scholastic achievement and electronic communications of students participating in an online group learning course, conducted electronically via the network during a course term, in which the students are initially grouped into groups and then regrouped during the course term based on the aggregated performance information, according to an implementation of the invention. The performance information may indicate a performance of a student in the course. The system may provide electronic tools to users. The system may monitor the tools to determine communication and social activity, as well as academic achievement of the students. The communication activity, social activity, and the academic achievement may be used to dynamically regroup students during a course term.

Abstract: In certain implementations, group learning may be provided via computerized student group assignments. In an implementation, student information about students registered to take a course may be obtained. The student information may comprise attributes of the students that correspond to student variables. Group criteria information associated with the course may be obtained. The group criteria information may comprise first criteria indicating that a student group is to be diverse with respect to a first variable, and second criteria indicating that a student group is to be similar with respect to a second variable. The students may be assigned to student groups associated with the course based on the attributes, the first criteria, and the second criteria such that a student group associated with the course comprises a set of students that, as a whole, is diverse with respect to the first variable and similar with respect to the second variable.

Abstract: In certain implementations, group learning may be provided via computerized student group assignments. In an implementation, student information about students registered to take a course may be obtained. The student information may comprise attributes of the students that correspond to student variables. Group criteria information associated with the course may be obtained. The group criteria information may comprise first criteria indicating that a student group is to be diverse with respect to a first variable, and second criteria indicating that a student group is to be similar with respect to a second variable. The students may be assigned to student groups associated with the course based on the attributes, the first criteria, and the second criteria such that a student group associated with the course comprises a set of students that, as a whole, is diverse with respect to the first variable and similar with respect to the second variable.