Recommending competitive learning objects

Abstract

A method and apparatus for competitive learning objects in a learning environment is provided. Based on the success that a student has with a particular learning item, a learning recommendation is generated for another student.

1 . A method, comprising:
 maintaining, at an online learning system, a hierarchy of learning objects, wherein each learning object of a plurality of learning objects in the hierarchy is associated with a corresponding skill and one or more content items associated with the corresponding skill;   wherein a particular node in the hierarchy of learning objects is associated with a first skill and corresponds to both a first learning object and a second learning object, wherein:
 the first learning object is associated with a first content item that is associated with the first skill; and 
 the second learning object is associated with a second content item that is associated with the first skill; 
   receiving, from a first user of a plurality of users, a first learning recommendation request for a learning object associated with the first skill;   generating, for the first user, a first learning recommendation, wherein the first learning recommendation identifies the first learning object;   receiving, from a second user of the plurality of users, a second learning recommendation request for a learning object associated with the first skill;   generating, for the second user, a second learning recommendation, wherein the second learning recommendation identifies the second learning object;   wherein the method is performed by one or more computing devices.   
     
     
         2 . The method of  claim 1 , further comprising:
 maintaining for a plurality of users of an online education system, profiles, wherein the profile maintained for each of the plurality of users describes one or more education-related attributes associated with the corresponding user of the plurality of users;   determining that the first learning object is associated with a greater level of success than the second learning object for users with a first value for a particular education-related attribute;   determining that the second learning object is associated with a greater level of success than the first learning object for users with a second value for the particular education-related attribute.   
     
     
         3 . The method of  claim 2 , wherein the particular education-related attribute identifies a course of study undertaken by the student. 
     
     
         4 . The method of  claim 2 , wherein the particular education-related attribute identifies a class that the student is enrolled in. 
     
     
         5 . The method of  claim 1 , further comprising:
 determining that the first learning object is associated with a better overall success rate than the second learning object based at least in part on the success of the second user with respect to the second learning object;   removing the second learning object from consideration as a learning object to be recommended to users.   
     
     
         6 . The method of  claim 1 , wherein generating the first learning recommendation comprises:
 in response to determining that the first user has previously interacted with the second learning object, selecting the first learning object as the learning object to recommend to the first user for the first skill.   
     
     
         7 . The method of  claim 1 , further comprising:
 selecting each learning object associated with the particular node for a learning recommendation at least once;   based at least in part on a determination that the first learning object is associated with a better success rate than the second learning object, selecting the first learning object more frequently than the second learning object for learning recommendations.   
     
     
         8 . The method of  claim 1 , wherein:
 the second learning object is a potential learning object of a set of potential learning objects selected for consideration to be associated with the particular node;   the method further comprises, in response to determining that the first learning object is associated with a greater level of success than the second learning object:
 associating the third learning object with the particular node; and 
 removing the association between the second learning object and the particular node. 
   
     
     
         9 . The method of  claim 8 , wherein:
 in response to determining that the third learning object is associated with a greater level of success than the first learning object:
 associating a fourth learning object with the particular node; and 
 removing the association between the first learning object and the particular node. 
   
     
     
         10 . The method of  claim 1 , wherein the first learning recommendation further identifies the second learning object. 
     
     
         11 . A method, comprising:
 maintaining, at an online learning system, a plurality of learning objects, wherein each learning object of the plurality of learning objects is associated with a corresponding skill and one or more corresponding assessment items, wherein the one or more assessment items measure the level of success that users attain with respect to the skill associated with the corresponding learning object;   in response to a first user attaining a first level of success with respect to the first skill associated with a first learning object, selecting a second learning object to recommend to the first user, wherein the second learning object is associated with a second skill and is located at a second position;   in response to determining that a second user has attained the first level of success with respect to the first learning object, and based at least in part on determining that the first user has attained a second level of success with respect to the second learning object, selecting a third learning object to recommend to the second user, wherein the third learning object is associated with a third skill;   wherein the method is performed by one or more computing devices.   
     
     
         12 . The method of  claim 11 , wherein:
 the plurality of objects are arranged in a hierarchy;   the second learning object is a child of the first learning object and the third learning object is a child of the second learning object.   
     
     
         13 . The method of  claim 11 , wherein:
 the plurality of objects are arranged in a hierarchy;   the second learning object is a parent of the first learning object and the third learning object is a parent of the second learning object.   
     
     
         14 . The method of  claim 11 , wherein:
 the plurality of objects are arranged in a hierarchy;   the second learning object is a first child of the first learning object and the third learning object is a second child of the first learning object.   
     
     
         15 . The method of  claim 11 , wherein:
 the plurality of objects are arranged in a hierarchy;   the second learning object is a first parent of the first learning object and the third learning object is a second parent of the first learning object.   
     
     
         16 . The method of  claim 11 , further comprising:
 maintaining for the first and second users, profiles, wherein the profile maintained for each of the first and second users describes one or more education-related attributes associated with the corresponding user;   wherein the third learning object is selected based at least in part on a determination that one or more education-related attributes of the second user is similar to one or more education-related attributes of the first user.   
     
     
         17 . The method of  claim 11 , further comprising:
 in response to detecting that the second user has achieved a second level of success with respect to the third learning object, selecting the first learning object to recommend to the second user.   
     
     
         18 . The method of  claim 11 , further comprising:
 in response determining that the first user has attained a second level of success with respect to the second learning object, storing a first remediation metric for the second learning object, wherein the first remediation metric provides a measurement of how successful the second learning object has been as a remediator.   
     
     
         19 . The method of  claim 18 , further comprising:
 maintaining for the first and second users, profiles, wherein the profile maintained for each of the first and second users describes one or more education-related attributes associated with the corresponding user;   in response determining that the first user has attained a second level of success with respect to the second learning object, storing a second remediation metric for the second learning object, wherein the second remediation metric provides a measurement of how successful the second learning object has been as a remediator;   wherein the first remediation metric is associated with a first education-related attribute and the second remediation metric is associated with a second education-related attribute.   
     
     
         20 . The method of  claim 11 , further comprising:
 in response to determining that the first user has previously interacted with a learning object that is associated with a first skill that is associated with the first learning object, performing one or more of the following:
 restricting the type of device that the user may use to interact with the third learning object; 
 selecting a first tool for delivering content items to the user, wherein the first tool was not previously used for delivering content items to the user; or 
 selecting a first content item to be delivered to the user, wherein the first content item was not previously delivered to the user. 
   
     
     
         21 . The method of  claim 11 , further comprising:
 in response to determining that a second user has attained the first level of success with respect to the first learning object, and based at least in part on determining that the first user has attained a second level of success with respect to the second learning object, selecting a fourth learning object to recommend to the second user, wherein the third learning object is associated with a fourth skill;   wherein the third skill and the fourth skill are prerequisites to a first skill that is associated with the first learning object.   
     
     
         22 . A computer-readable non-transitory storage medium storing instructions which, when executed by one or more processors, cause the one or more processors to perform:
 maintaining, at an online learning system, a hierarchy of learning objects, wherein each learning object of a plurality of learning objects in the hierarchy is associated with a corresponding skill and one or more content items associated with the corresponding skill;   wherein a particular node in the hierarchy of learning objects is associated with a first skill and corresponds to both a first learning object and a second learning object, wherein:
 the first learning object is associated with a first content item that is associated with the first skill; and 
 the second learning object is associated with a second content item that is associated with the first skill; 
   receiving, from a first user of a plurality of users, a first learning recommendation request for a learning object associated with the first skill;   generating, for the first user, a first learning recommendation, wherein the first learning recommendation identifies the first learning object;   receiving, from a second user of the plurality of users, a second learning recommendation request for a learning object associated with the first skill;   generating, for the second user, a second learning recommendation, wherein the second learning recommendation identifies the second learning object.   
     
     
         23 . The computer-readable non-transitory storage medium of  claim 22 , wherein the instructions further include instructions for:
 maintaining for a plurality of users of an online education system, profiles, wherein the profile maintained for each of the plurality of users describes one or more education-related attributes associated with the corresponding user of the plurality of users;   determining that the first learning object is associated with a greater level of success than the second learning object for users with a first value for a particular education-related attribute;   determining that the second learning object is associated with a greater level of success than the first learning object for users with a second value for the particular education-related attribute.   
     
     
         24 . The computer-readable non-transitory storage medium of  claim 23 , wherein the particular education-related attribute identifies a course of study undertaken by the student. 
     
     
         25 . The computer-readable non-transitory storage medium of  claim 23 , wherein the particular education-related attribute identifies a class that the student is enrolled in. 
     
     
         26 . The method of  claim 22 , wherein the instructions further include instructions for:
 determining that the first learning object is associated with a better overall success rate than the second learning object based at least in part on the success of the second user with respect to the second learning object;   removing the second learning object from consideration as a learning object to be recommended to users.   
     
     
         27 . The computer-readable non-transitory storage medium of  claim 22 , wherein generating the first learning recommendation comprises:
 in response to determining that the first user has previously interacted with the second learning object, selecting the first learning object as the learning object to recommend to the first user for the first skill.   
     
     
         28 . The computer-readable non-transitory storage medium of  claim 22 , wherein the instructions further include instructions for:
 selecting each learning object associated with the particular node for a learning recommendation at least once;   based at least in part on a determination that the first learning object is associated with a better success rate than the second learning object, selecting the first learning object more frequently than the second learning object for learning recommendations.   
     
     
         29 . The computer-readable non-transitory storage medium of  claim 22 , wherein:
 the second learning object is a potential learning object of a set of potential learning objects selected for consideration to be associated with the particular node;   the instructions further include instructions for, in response to determining that the first learning object is associated with a greater level of success than the second learning object:
 associating the third learning object with the particular node; and 
 removing the association between the second learning object and the particular node. 
   
     
     
         30 . The computer-readable non-transitory storage medium of  claim 29 , wherein:
 in response to determining that the third learning object is associated with a greater level of success than the first learning object:
 associating a fourth learning object with the particular node; and 
 removing the association between the first learning object and the particular node. 
   
     
     
         31 . The computer-readable non-transitory storage medium of  claim 22 , wherein the first learning recommendation further identifies the second learning object. 
     
     
         32 . A computer-readable non-transitory storage medium storing instructions which, when executed by one or more processors, cause the one or more processors to perform:
 maintaining, at an online learning system, a plurality of learning objects, wherein each learning object of the plurality of learning objects is associated with a corresponding skill and one or more corresponding assessment items, wherein the one or more assessment items measure the level of success that users attain with respect to the skill associated with the corresponding learning object;   in response to a first user attaining a first level of success with respect to the first skill associated with a first learning object, selecting a second learning object to recommend to the first user, wherein the second learning object is associated with a second skill and is located at a second position;   in response to determining that a second user has attained the first level of success with respect to the first learning object, and based at least in part on determining that the first user has attained a second level of success with respect to the second learning object, selecting a third learning object to recommend to the second user, wherein the third learning object is associated with a third skill.   
     
     
         33 . The computer-readable non-transitory storage medium of  claim 32 , wherein:
 the plurality of objects are arranged in a hierarchy;   the second learning object is a child of the first learning object and the third learning object is a child of the second learning object.   
     
     
         34 . The computer-readable non-transitory storage medium of  claim 32 , wherein:
 the plurality of objects are arranged in a hierarchy;   the second learning object is a parent of the first learning object and the third learning object is a parent of the second learning object.   
     
     
         35 . The computer-readable non-transitory storage medium of  claim 32 , wherein:
 the plurality of objects are arranged in a hierarchy;   the second learning object is a first child of the first learning object and the third learning object is a second child of the first learning object.   
     
     
         36 . The computer-readable non-transitory storage medium of  claim 32 , wherein:
 the plurality of objects are arranged in a hierarchy;   the second learning object is a first parent of the first learning object and the third learning object is a second parent of the first learning object.   
     
     
         37 . The computer-readable non-transitory storage medium of  claim 32 , wherein the instructions further include instructions for:
 maintaining for the first and second users, profiles, wherein the profile maintained for each of the first and second users describes one or more education-related attributes associated with the corresponding user;   wherein the third learning object is selected based at least in part on a determination that one or more education-related attributes of the second user is similar to one or more education-related attributes of the first user.   
     
     
         38 . The computer-readable non-transitory storage medium of  claim 32 , wherein the instructions further include instructions for:
 in response to detecting that the second user has achieved a second level of success with respect to the third learning object, selecting the first learning object to recommend to the second user.   
     
     
         39 . The computer-readable non-transitory storage medium of  claim 32 , wherein the instructions further include instructions for:
 in response determining that the first user has attained a second level of success with respect to the second learning object, storing a first remediation metric for the second learning object, wherein the first remediation metric provides a measurement of how successful the second learning object has been as a remediator.   
     
     
         40 . The computer-readable non-transitory storage medium of  claim 39 , wherein the instructions further include instructions for:
 maintaining for the first and second users, profiles, wherein the profile maintained for each of the first and second users describes one or more education-related attributes associated with the corresponding user;   in response determining that the first user has attained a second level of success with respect to the second learning object, storing a second remediation metric for the second learning object, wherein the second remediation metric provides a measurement of how successful the second learning object has been as a remediator;   wherein the first remediation metric is associated with a first education-related attribute and the second remediation metric is associated with a second education-related attribute.   
     
     
         41 . The computer-readable non-transitory storage medium of  claim 32 , wherein the instructions further include instructions for:
 in response to determining that the first user has previously interacted with a learning object that is associated with a first skill that is associated with the first learning object, performing one or more of the following:
 restricting the type of device that the user may use to interact with the third learning object; 
 selecting a first tool for delivering content items to the user, wherein the first tool was not previously used for delivering content items to the user; or 
 selecting a first content item to be delivered to the user, wherein the first content item was not previously delivered to the user. 
   
     
     
         42 . The computer-readable non-transitory storage medium of  claim 32 , wherein the instructions further include instructions for:
 in response to determining that a second user has attained the first level of success with respect to the first learning object, and based at least in part on determining that the first user has attained a second level of success with respect to the second learning object, selecting a fourth learning object to recommend to the second user, wherein the third learning object is associated with a fourth skill;   wherein the third skill and the fourth skill are prerequisites to a first skill that is associated with the first learning object.