US 12,067,901 B2
Methods and systems for providing a learning path for an electronic learning system
Jugoslav Bilic, Kitchener (CA); Stephen John Michaud, Kitchener (CA); Martin David Goodenough Bayly, Kitchener (CA); and Ryan Clayton Ogg, Kitchener (CA)
Assigned to D2L Corporation, Kitchener (CA)
Filed by D2L Corporation, Kitchener (CA)
Filed on Jun. 3, 2015, as Appl. No. 14/729,526.
Prior Publication US 2016/0358494 A1, Dec. 8, 2016
Int. Cl. G09B 7/00 (2006.01); G09B 5/02 (2006.01)
CPC G09B 7/00 (2013.01) [G09B 5/02 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A computer-implemented method for providing a learning path for an electronic learning system, the electronic learning system including a computer server having a processor, a learning path component in electronic communication with the processor, an evaluation component in electronic communication with the processor, a resource mapping component in electronic communication with the processor and at least one data storage component in electronic communication with the learning path component, the evaluation component and the processor, the at least one data storage component storing one or more learning objectives, the method comprising:
retrieving, by the learning path component of the server, from the one or more learning objectives, a set of learning objectives assigned to the learning path;
for each learning objective of the set of learning objectives, selecting, by the learning path component of the server, from a plurality of resources accessible to the electronic learning system, one or more resources assigned a relevance score by the resource mapping component, the one or more resources including content with content data and one or more resource property fields that define at least one characteristic of the resource, the resource mapping component sectioning the content data of each resource into content portions based on the one or more resource property fields, the relevance score at least satisfying a relevance threshold for that learning objective, the relevance score representing an estimated degree of correlation between that learning objective and each content portion of the respective resource, and the relevance threshold indicating a minimum relevance score required for a resource to be selected for a learning objective;
generating, by the learning path component of the server, an initial learning path using the selected one or more resources;
identifying, by the processor, one or more evaluation type resources from the selected one or more resources, each evaluation type resource comprising an interaction for evaluating a proficiency of a user in relation to at least a subset of learning objectives of the set of learning objectives;
determining, by the evaluation component, a competence level of the user in respect of at least one of the learning objectives of the subset of learning objectives;
monitoring, by the processor, a feedback usage indicator stored in a learning path database of the data storage component for each evaluation type resource of the selected one or more resources, the feedback usage indicator representing an amount of user interactions with that evaluation type resource, the feedback usage indicator increasing in value with each subsequent use of each evaluation type resource; and
updating, by the learning path component of the server, the initial learning path to generate the learning path in real-time based on, at least, the feedback usage indicator of each evaluation type resource of the selected one or more resources, the updating of the initial learning path by the learning path component of the server comprising:
determining, by the learning path component of the server, a system learn value for a resource associated with the feedback usage indicator;
comparing the system learn value to a learn value threshold;
dynamically generating, by the evaluation component, at least one additional evaluation type resource based on the determined competence level of the user in respect of the at least one of the learning objectives of the subset of learning objectives, the dynamically generated additional evaluation type resource being customized for the user based on prior interactions of the user with the initial learning path; and
determining to update the initial learning path based on the comparison of the system learn value to the learn value threshold, wherein the system learn value is a numerical value corresponding to a probability that a corresponding resource will assist the user in achieving a corresponding learning objective.