Methods and systems for representing usage of an electronic learning system

• US 10,339,616 B2
• Filed: 05/01/2014
• Issued: 07/02/2019
• Est. Priority Date: 05/01/2014
• Status: Active Grant

• Current Assignee: D2L Corporation
• Original Assignee: D2L Corporation
• Inventors: Mihai, Sebastian, Grabka, Dariusz
• Primary Examiner(s): Hillery, Nathan
• Application Number:
  US14/267,023
• Publication Number:
  US 20150317757A1
• Time in Patent Office: 1,888 Days
• CPC Class Codes: G06Q 50/20 Education
• CPC Class Codes: G06Q 50/205 Education administration or guidance
• CPC Class Codes: G09B 5/00 Electrically-operated educational appliances working with questions and answers G09B7/00; simulators G09B9/00; advertising or displaying in general G09F
• CPC Class Codes: G09B 7/02 of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student

Abstract

A method and system for representing usage of an electronic learning system. The method and system involve receiving an input indicative of a selection of a property of the electronic learning system to be represented, the property including a course content provided by the electronic learning system and an activity available for that course content; receiving representation parameters that define a scope of the usage to be represented; determining an event count for the property during the period of interest; and generating a usage indicator for the property based at least on the event count. The usage indicator is generally reflective of at least a usage amount of the property during the period of interest.

Claims

1. A computer-implemented method for representing usage of an electronic learning system, the method comprising:

receiving an input indicative of a selection of an interaction with a course content provided by the electronic learning system;

receiving representation parameters that define a scope of the usage to be represented, the representation parameters including at least a period of interest;

determining an event count for the interaction during the period of interest, the event count being a number of events stored at one or more storage components of the electronic learning system for the interaction with the course content;

generating a usage indicator that is reflective of a usage amount of the course content during the period of interest, the usage indicator being generated by adjusting the event count with at least one of a count parameter and a weight factor, the count parameter providing at least one limitation to a value of the event count and the weight factor indicating an amount of influence that the interaction has on the usage of the electronic learning system, wherein the usage indicator is generated based at least in part on one or more of an amount of time the course content was viewed, a number of revisions made to the course content, a number of keystrokes input in relation to the course content, a rating input for the course content, a user review for the course content, and a comment for the course content, an author of the course content, and an indication of whether the course content is bookmarked within the electronic learning system;

determining one or more groups of users based at least in part on a respective level of achievement of the user with respect to a course associated with the course content; and

determining a correlation between the interaction and a level of achievement with respect to the course based at least in part on the one or more groups of users; and

providing an indication of the correlation between the interaction and the level of achievement with respect to the course.

2. The method of claim 1, wherein:

the representation parameters further comprise a time interval that is shorter than the period of interest; and

determining the event count for the interaction during the period of interest comprises;

separating the period of interest into a set of sub-periods according to the time interval, a length of at least one sub-period corresponds to the time interval; and

determining a plurality of counts for the period of interest, each count being the number of events corresponding to the interaction with the course content during a sub-period and the event count being a sum of the plurality of counts.

3. The method of claim 1, wherein:

the count parameter comprises at least one of an upper count limit and a lower count limit; and

adjusting the event count with the count parameter comprises;

when the count parameter is the upper count limit;

determining whether the event count exceeds the upper count limit; and

in response to determining the event count exceeds the upper count limit, reducing the event count to the upper count limit; and

when the count parameter is the lower count limit;

generating an intermediary event count by subtracting the lower count limit from the event count; and

if the intermediary event count is less than zero, setting the event count to zero, otherwise using the intermediary event count as the event count.

20. The method of claim 1, wherein, the correlation is based at least in part on one or more of (i) a manner by which a user of the electronic system interacts with one or more content resources provided by the electronic system, and (ii) an extent to which the user of the electronic system interacts with the one or more content resources provided by the electronics system.

4. A computer-implemented method for representing usage of an electronic learning system, the method comprising:

receiving an input indicative of a selection of a property of the electronic learning system to be represented, the property including a course content provided by the electronic learning system and an activity available for that course content;

receiving representation parameters that define a scope of the usage to be represented, the representation parameters including at least a period of interest;

determining an event count for the property during the period of interest, the event count corresponding to a number of events stored at one or more storage components of the electronic learning system in association with the property for the period of interest;

generating a usage indicator for the property based at least on the event count, the usage indicator being reflective of at least a usage amount of the property during the period of interest, wherein the usage indicator is generated based at least in part on one or more of an amount of time the course content was viewed, a number of revisions made to the course content, a number of keystrokes input in relation to the course content, a rating input for the course content, a user review for the course content, and a comment for the course content, an author of the course content, and an indication of whether the course content is bookmarked within the electronic learning system;

determining one or more groups of users based at least in part on a respective level of achievement of the user with respect to a course associated with the course content; and

determining a correlation between the interaction and a level of achievement with respect to the course based at least in part on the one or more groups of users; and

providing an indication of the correlation between the interaction and the level of achievement with respect to the course.

5. The method of claim 4, wherein:

the representation parameters comprise a time interval, the time interval being shorter than the period of interest; and

determining the event count for the property during the period of interest comprises;

separating the period of interest into a set of sub-periods according to the time interval, a length of at least one sub-period corresponds to the time interval; and

determining a plurality of counts for the period of interest, each count being the number of events corresponding to the property for a sub-period and the event count being a sum of the plurality of counts.

6. The method of claim 5, wherein generating the usage indicator for the property based at least on the event count comprises:

determining a top count from the two or more counts, the top count being the count from the two or more counts with a greatest value; and

normalizing each count with the top count.

7. The method of claim 6 further comprises:

receiving a transformation mode indicator for the event count, the transformation mode indicator providing a type of adjustment to be applied to the event count; and

varying each count in accordance with the transformation mode indicator.

8. The method of claim 7, wherein:

the transformation mode indicator corresponds to a peak mode; and

varying each count in accordance with the transformation mode indicator comprises;

identifying the sub-period associated with the top count; and

for each sub-period subsequent to the identified sub-period, replacing the corresponding normalized count with the normalized top count.

9. The method of claim 7, wherein:

the transformation mode indicator corresponds to a cumulative average mode; and

varying each count in accordance with the transformation mode indicator comprises, for each sub-period,

retrieving the count associated with each prior sub-period; and

generating an adjusted count by determining an average of the count for each prior sub-period and the count for that sub-period; and

replacing the count for that sub-period with the adjusted count.

10. The method of claim 4, wherein determining the event count for the property during the period of interest further comprises:

setting the event count to zero;

retrieving, from the one or more storage components, events that satisfy the representation parameters; and

for each retrieved event, determining whether that event is associated with the property and if so, incrementing the event count.

11. The method of claim 4, wherein generating the usage indicator for the property based at least on the event count comprises:

receiving a weight factor for the activity, the weight factor indicating an amount of influence the activity has on the usage of the electronic learning system; and

adjusting the event count with the weight factor.

12. The method of claim 4, wherein determining the event count for the property during the period of interest further comprises:

receiving a count parameter for the event count, the count parameter providing at least one limitation to a value of the event count; and

adjusting the event count based on the count parameter.

13. The method of claim 12, wherein:

the count parameter comprises an upper count limit;

adjusting the event count based on the count parameter comprises;

determining whether the event count exceeds the upper count limit; and

in response to determining the event, count exceeds the upper count limit, reducing the event count to the upper count limit.

14. The method of claim 12, wherein:

the count parameter comprises a lower count limit;

adjusting the event count based on the count parameter comprises;

generating an intermediary event count by subtracting the lower count limit from the event count; and

if the intermediary event count is less than zero, setting the event count to zero, otherwise using the intermediary event count as the event count.

15. The method of claim 4, wherein:

the activity is associated with a first course content and a second course content that is different from the first course content;

the usage indicator comprises a first usage indicator for the activity at the first course content and a second usage indicator for the activity at the second course content;

determining the event count for the property during the period of interest comprises;

generating a first event count for the first course content, the first event count corresponding to the usage amount of the activity at the first course content during the period of interest; and

generating a second event count for the second course content, the second event count corresponding to the usage amount of the activity at the second course content during the period of interest; and

generating each of the first usage indicator and the second usage indicator based at least on the first event count and the second event count.

16. The method of claim 15 further comprises:

determining whether the first event count is greater than the second event count; and

if the first event count is greater than the second event count, normalizing each of the first event count and the second event count with the first event count, otherwise normalizing each of the first event count and the second event count with the second event count.

17. The method of claim 4, wherein generating the usage indicator for the property comprises providing a visual representation of the usage indicator.

18. The method of claim 17, wherein the visual representation comprises a heat map.

19. An electronic learning system comprising:

a processing component configured to operate one or more components of the electronic learning system to represent usage of the electronic learning system;

one or more storage components for storing, at least, events associated with the electronic learning system, the one or more storage components being in communication with the processing component; and

a representation component operated by the processing component to;

receive an input indicative of a selection of a user interaction type with a course content provided by the electronic learning system;

receive representation parameters that define a scope of the usage to be represented, the representation parameters including at least a period of interest;

determine an event count for the user interaction type during the period of interest, the event count being a number of events stored at the one or more storage components of the electronic learning system for the user interaction type with the course content;

generate a usage indicator that is reflective of a usage amount of the course content during the period of interest, the usage indicator being generated by adjusting the event count with at least one of a count parameter and a weight factor, the count parameter providing at least one limitation to a value of the event count and the weight factor indicating an amount of influence that the user interaction type has on the usage of the electronic learning system, wherein the usage indicator is generated based at least in part on one or more of an amount of time the course content was viewed, a number of revisions made to the course content, a number of keystrokes input in relation to the course content, a rating input for the course content, a user review for the course content, and a comment for the course content, an author of the course content, and an indication of whether the course content is bookmarked within the electronic learning system;

determine one or more groups of users based at least in part on a respective level of achievement of the user with respect to a course associated with the course content; and

determine a correlation between the interaction and a level of achievement with respect to the course based at least in part on the one or more groups of users; and

provide an indication of the correlation between the interaction and the level of achievement with respect to the course.