SYSTEMS AND METHODS FOR MONITORING eLEARNING SYSTEM DATA AND GENERATING RECOMMENDATIONS
According to one aspect, an online learning system comprising a processor adapted to provide a monitoring module, a recommendation module and a communication module. The monitoring module is operable to monitor system data about one or more components of the online learning environment wherein the system data is indicative of behavior of one or more users of the learning environment. The recommendation module is operable to determine whether the system data for a given component meets one or more defined thresholds, each threshold being indicative of undesirable behavior associated with that component, and if one of the given thresholds is met, determine at least one remedial action associated with that threshold which may be employed to address the undesirable behavior. The communication module is operable to communicate information about the at least one remedial action to at least one user.
1 . A computer-implemented eLearning method comprising:
monitoring system data about one or more components of an online learning environment, the system data being indicative of behavior of one or more users of the learning environment;
determining whether the system data for a given component meets one or more defined thresholds, each threshold being indicative of undesirable behavior associated with that component;
if one of the given thresholds is met, determining at least one remedial action associated with that threshold which may be employed to address the undesirable behavior; and
communicating information about the at least one remedial action to at least one user.
2 . The method of claim 1 , wherein when more than one defined thresholds are met, the method further comprises:
determining a priority value indicative of importance of addressing the undesirable behavior associated with those thresholds;
selecting at least one of those thresholds to address based on the priority value; and
determining the remedial action associated with the selected threshold.
3 . The method of claim 2 , wherein the remedial actions and priority values associated with each threshold are determined based upon a predefined condition-action matrix.
4 . The method of claim 1 , wherein the at least one remedial action that may be employed when the threshold is met is determined based upon instructional design.
5 . The method of claim 1 , wherein the at least one remedial action that may be employed when the threshold is met is determined based upon at least one predefined workflow.
6 . The method of claim 1 , wherein the system data about one or more components includes utilization data for those components.
7 . The method of claim 6 , wherein the utilization data includes user-account information indicative of one or more users that have or have not utilized one of the components in a given period of time.
8 . The method of claim 7 , wherein the one or more components includes one or more learning tools, and the system data includes tool data indicative of utilization of one or more aspects of those tools
9 . The method of claim 8 , wherein one of the remedial actions includes sending a targeted notification message to the one or more users that have not utilized one of the components.
10 . The method of claim 1 , wherein one of the remedial actions includes sending a plurality of notification messages to a plurality of users associated with a system component.
11 . An online learning system comprising a processor adapted to provide:
a monitoring module, the monitoring module operable to monitor system data about one or more components of the online learning environment, the system data being indicative of behavior of one or more users of the learning environment;
a recommendation module, the recommendation module operable to
i. determine whether the system data for a given component meets one or more defined thresholds, each threshold being indicative of undesirable behavior associated with that component, and
ii. if one of the given thresholds is met, determine at least one remedial action associated with that threshold which may be employed to address the undesirable behavior; and
a communication module, the communication module operable to communicate information about the at least one remedial action to at least one user.
12 . The system of claim 11 , wherein when more than one defined thresholds are met the recommendation module is further operable to:
determine a priority value indicative of importance of addressing the undesirable behavior associated with those thresholds;
select at least one of those thresholds to address based on the priority value; and
determine the remedial action associated with the selected threshold.
13 . The system of claim 12 , wherein the remedial actions and priority values associated with each threshold are determined based upon a predefined condition-action matrix.
14 . The system of claim 11 , wherein the at least one remedial action that may be employed when the threshold is met is determined based upon instructional design.
15 . The system of claim 11 , wherein the at least one remedial action that may be employed when the threshold is met is determined based upon at least one predefined workflow.
16 . The system of claim 11 , wherein the system data about one or more components includes utilization data for those components.
17 . The system of claim 16 , wherein the one or more components includes one or more learning tools, and the system data include tool data indicative of utilization of one or more aspects of those tools
18 . The system of claim 16 , wherein the utilization data includes user-account information indicative of one or more users that have or have not utilized one of the components in a given period of time.
19 . The system of claim 18 , wherein one of the remedial actions includes sending a targeted notification message to the one or more users that have not utilized one of the components.
20 . The system of claim 11 , wherein one of the remedial actions includes sending a plurality of notification messages to a plurality of users associated with a system component.