Virtual coaching platform

Abstract

Some embodiments of a virtual coaching platform can analyze user and coach characteristics to determine suggested coaching partnerships. Some virtual coaching platform embodiments can implement whole-person dimensionalities used to track progress and provide coaching resources and guidance. In some implementations, the virtual coaching platform can provide six whole-person dimensions including: centered, aware, agile, includes, elevates, and drives. Some virtual coaching platform embodiments can select a subset of the dimensionalities to update using determined associations between a user and the dimensionalities. Some virtual coaching platform embodiments can implement a motivational matrix to assess a user in a readiness versus clarity domain and provide coaching suggestions based on a corresponding type.

I/We claim: 
     
         1 . A system implementing a virtual coaching platform, the system comprising:
 one or more processors;   an interface that obtains dimensionality metrics in relation to a user, wherein each dimensionality metric has an association to at least one dimensionality of at least part of a user skills model, wherein the user skills model comprises dimensionalities made up of multiple dimensions; and   a memory storing virtual coaching platform items, the virtual platform items including videos, exercises, recordings, and reading materials, the memory further storing measures of user interaction with virtual platform items, and the memory further storing instructions that, when executed by the one or more processors, cause the system to perform operations comprising:
 for each selected dimension, of two or more dimensions of the at least part of the user skills model:
 generating a user score for the selected dimension; and 
 computing a comparison value for the selected dimension by comparing the user score for the selected dimension with a base score for the selected dimension; 
 
 automatically computing a type of the user based on comparison values for dimensions; and 
 selecting one or more coaching suggestions customized to the user based on the computed type of the user. 
   
     
     
         2 . The system of  claim 1 , wherein the base score for a particular dimension, of the two or more dimensions, is an average of user scores for the particular dimension for a group of users within the same geographical region as the user. 
     
     
         3 . The system of  claim 1 , wherein at least some of the obtained metrics are values corresponding to responses, by the user, to a set of self-reporting questions. 
     
     
         4 . The system of  claim 1 , wherein at least some of the obtained dimensionality metrics are values corresponding to responses to a set of peer review questions. 
     
     
         5 . The system of  claim 1 , wherein the multiple dimensions in the user skills model are equivalent to:
 centered, aware, agile, including, elevates, and drives.   
     
     
         6 . The system of  claim 1 , wherein one dimension includes sub-dimensions equivalent to:
 purpose, engagement, energy, and calm.   
     
     
         7 . The system of  claim 1 , wherein the at least part of a user skills model comprises less than all of the dimensionalities of the user skills model. 
     
     
         8 . The system of  claim 1 ,
 wherein the at least part of a user skills model comprises less than all of the dimensionalities of the user skills model;   wherein the dimensionalities that are included in the at least part of a user skills model are chosen by:
 obtaining pulse metrics indicating amounts of interaction the user has had with content tagged with at least one dimensionality of the user skills model; and 
 determining that a total of the pulse metrics corresponding to each of the dimensionalities, that are included in the at least part of a user skills model, exceeds a threshold. 
   
     
     
         9 . The system of  claim 1 ,
 wherein the at least part of a user skills model comprises less than all of the dimensionalities of the user skills model; and   wherein at least a first of the dimensionalities that are included in the at least part of a user skills model is chosen by:
 obtaining pulse metrics indicating amounts of interaction the user has had with content tagged with at least one dimensionality of the user skills model; 
 augmenting the pulse metrics with an additional pulse metric in the first dimensionality by applying a mapping, between a second dimensionality to the first dimensionality, that has a weighting factor, wherein applying the mapping comprises multiplying one of the obtained pulse metrics corresponding to the second dimensionality by the weighting factor; 
 computing a total pulse metric for the first dimensionality by combining at least one of the obtained pulse metrics corresponding to the first dimensionality and the additional pulse metric; and 
 determining that the total pulse metric for the dimensionality exceeds a threshold. 
   
     
     
         10 . A non-transitory computer-readable storage medium storing instructions that, when executed by a computing system having one or more processors, cause the computing system to perform operations comprising:
 storing, in a memory, dimensionality metrics in relation to a user, wherein each   dimensionality metric has an association to at least one dimensionality of at least part of a user skills model, wherein the user skills model comprises dimensionalities made up of multiple dimensions;   storing virtual coaching platform items, the virtual platform items including videos, exercises, recordings, and reading materials;   generating a user score for a selected dimension;   computing a comparison value for the selected dimension by comparing the user score for the selected dimension with a base score for the selected dimension;   automatically computing a type of the user based on comparison values for dimensions; and   selecting one or more coaching suggestions customized to the user based on the computed type of the user.   
     
     
         11 . The non-transitory computer readable medium of  claim 10 , wherein the base score for a particular dimension, of the two or more dimensions, is an average of user scores for the particular dimension for a group of users within the same geographical region as the user. 
     
     
         12 . The non-transitory computer readable medium of  claim 10 , wherein at least some of the obtained metrics are values corresponding to responses, by the user, to a set of self-reporting questions. 
     
     
         13 . The non-transitory computer readable medium of  claim 10 , wherein at least some of the obtained dimensionality metrics are values corresponding to responses to a set of peer review questions. 
     
     
         14 . The non-transitory computer readable medium of  claim 10 , wherein the multiple dimensions in the user skills model are equivalent to:
 centered, aware, agile, including, elevates, and drives.   
     
     
         15 . The non-transitory computer readable medium of  claim 10 , wherein one dimension includes sub-dimensions equivalent to:
 purpose, engagement, energy, and calm.   
     
     
         16 . The non-transitory computer readable medium of  claim 10 , wherein the at least part of a user skills model comprises less than all of the dimensionalities of the user skills model. 
     
     
         17 . The non-transitory computer readable medium of  claim 10 ,
 wherein the at least part of a user skills model comprises less than all of the dimensionalities of the user skills model;   wherein the dimensionalities that are included in the at least part of a user skills model are chosen by:
 obtaining pulse metrics indicating amounts of interaction the user has had with content tagged with at least one dimensionality of the user skills model; and 
 determining that a total of the pulse metrics corresponding to each of the dimensionalities, that are included in the at least part of a user skills model, exceeds a threshold. 
   
     
     
         18 . The system of  claim 1 ,
 wherein the at least part of a user skills model comprises less than all of the dimensionalities of the user skills model; and   wherein at least a first of the dimensionalities that are included in the at least part of a user skills model is chosen by:
 obtaining pulse metrics indicating amounts of interaction the user has had with content tagged with at least one dimensionality of the user skills model; 
 augmenting the pulse metrics with an additional pulse metric in the first dimensionality by applying a mapping, between a second dimensionality to the first dimensionality, that has a weighting factor, wherein applying the mapping comprises multiplying one of the obtained pulse metrics corresponding to the second dimensionality by the weighting factor; 
 computing a total pulse metric for the first dimensionality by combining at least one of the obtained pulse metrics corresponding to the first dimensionality and the additional pulse metric; and 
 determining that the total pulse metric for the dimensionality exceeds a threshold. 
   
     
     
         18 . A method comprising:
 storing, in a memory, dimensionality metrics in relation to a user, wherein each   dimensionality metric has an association to at least one dimensionality of at least part of a user skills model, wherein the user skills model comprises dimensionalities made up of multiple dimensions;   storing virtual coaching platform items, the virtual platform items including videos, exercises, recordings, and reading materials;   generating a user score for a selected dimension;   computing a comparison value for the selected dimension by comparing the user score for the selected dimension with a base score for the selected dimension;   automatically computing a type of the user based on comparison values for dimensions; and   selecting one or more coaching suggestions customized to the user based on the computed type of the user.   
     
     
         20 . The method of  claim 18 , wherein the base score for a particular dimension, of the two or more dimensions, is an average of user scores for the particular dimension for a group of users within the same geographical region as the user.