PERSONALIZED LEARNING STREAMS IN A MODULAR LEARNING SYSTEM

1 . A computer-implemented method for dynamically generating a personalized learning stream in a modular learning system, the method comprising steps of:

maintaining an application services database including a plurality of application services, each application service associated with an available time;

maintaining a learning application database including a plurality of learning applications, each learning application associated with at least one application service in the plurality of application services;

receiving, from a user device operated by a learning user, a performance request specifying a time and one or more learning applications in the plurality of learning applications;

determining an availability of application services associated with the plurality of learning applications based on specified time and the available time associated with the application service;

adding the plurality of learning applications to a learning stream associated with the learning user, wherein the learning application in the learning stream is associated with the available time; and

displaying the learning stream on the user device.

2 . The method of claim 1 :

wherein adding the plurality of learning applications to the learning stream comprises of generating a performance cell associated with the learning application, the performance cell including information associated with the at least one application service associated with the learning application; and

wherein displaying the learning stream on the user device comprises displaying a series of performance cells.

3 . The method of claim 1 , further comprising:

receiving a rescheduling request specifying the learning application in the learning stream and a new time;

determining the availability of the at least one application service associated with the learning application specified by the rescheduling request based on the new time and the available time associated with the at least one application service; and

associating the learning application in the learning stream with the new time.

4 . The method of claim 3 ,

wherein the learning application is associated with sequence metadata describing the plurality of learning applications to be performed after the learning application; and

wherein the method further comprises:

determining an updated time for the plurality of learning applications to be performed after the learning application, wherein the updated time is after the new time of the learning application; and

associating the plurality of learning applications to be performed after the learning application in the learning stream with the updated time.

5 . A non-transitory computer-readable storage medium storing computer program instructions executable by a processor for performing a method for dynamically generating a personalized learning stream in a modular learning system, the method comprising steps of:

maintaining an application services database including a plurality of application services, each application service associated with an available time;

maintaining a learning application database including a plurality of learning applications, each learning application associated with at least one application service in the plurality of application services;

receiving, from a user device operated by a learning user, a performance request specifying a time and one or more learning applications in the plurality of learning applications;

determining an availability of application services associated with the plurality of learning applications based on specified time and the available time associated with the application service;

adding the plurality of learning applications to a learning stream associated with the learning user, wherein the learning application in the learning stream is associated with the available time; and

displaying the learning stream on the user device.

6 . The non-transitory computer-readable storage medium of claim 5 ,

wherein adding the plurality of learning applications to the learning stream comprises of generating a performance cell associated with the learning application, the performance cell including information associated with the at least one application service associated with the learning application; and

wherein displaying the learning stream on the user device comprises of displaying a series of performance cells.

7 . The non-transitory computer-readable storage medium of claim 5 , wherein the method further comprises:

receiving a rescheduling request specifying the learning application in the learning stream and a new time;

determining the availability of the at least one application service associated with the learning application specified by the rescheduling request based on the new time and the available time associated with the at least one application service; and

responsive to determining the new availability, associating the learning application in the learning stream with the new time.

8 . The non-transitory computer-readable storage medium of claim 7 ,

wherein each the learning application is associated with sequence metadata describing one or more learning applications to be performed after the learning application; and

wherein the method further comprises:

determining an updated time for the plurality of learning applications to be performed after the learning application, wherein the updated time is after the new time of the learning application; and

associating the plurality of learning applications to be performed after the learning application in the learning stream with the updated time.

9 . An apparatus comprising:

a processor configured to execute instructions stored on a non-transitory computer-readable storage medium;

a non-volatile memory including:

a plurality of instructions for execution on the processor, the instructions which are executable to perform steps of:

maintaining an application services database including a plurality of application services, each application service associated with an available time;

maintaining a learning application database including a plurality of learning applications, each learning application associated with at least one application service in the plurality of application services;

receiving, from a user device operated by a learning user, a performance request specifying a time and one or more learning applications in the plurality of learning applications;

determining an availability of application services associated with the one or more specified learning applications based on the specified time and the available time associated with each application service;

adding the plurality of learning applications to a learning stream associated with the learning user, wherein learning application in the learning stream is associated with the time; and

displaying the learning stream on the user device.

10 . The apparatus of claim 9 ,

wherein adding the plurality of learning applications to the learning stream comprises of generating a performance cell associated with the learning application, the performance cell including information associated with the at least one application service associated with the learning application; and

wherein displaying the learning stream on the user device comprises of displaying a series of performance cells.

11 . The apparatus of claim 9 , wherein the steps further comprising:

receiving a rescheduling request specifying the learning application in the learning stream and a new time;

determining the new availability of the at least one application service associated with the learning application specified by the rescheduling request based on the new time and the available time associated with the at least one application service; and

associating the learning application in the learning stream with the new time.

12 . The apparatus of claim 11 ,

wherein the learning application is associated with sequence metadata describing one or more learning applications to be performed after the learning application; and

wherein the method further comprises:

determining an updated time for the plurality of learning applications to be performed after the learning application, wherein the updated time is after the new time of the learning application; and

associating the plurality of learning applications to be performed after the learning application in the learning stream with the updated time.