U.S. patent application number 12/492588 was filed with the patent office on 2010-12-30 for using game elements to motivate learning.
This patent application is currently assigned to MICROSOFT CORPORATION. Invention is credited to MARK R. ALEXIEFF, MARINA DUKHON, JONAS HELIN, JENNIFER P. MICHELSTEIN, NINA F. SHIH.
Application Number | 20100331075 12/492588 |
Document ID | / |
Family ID | 43381336 |
Filed Date | 2010-12-30 |
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United States Patent
Application |
20100331075 |
Kind Code |
A1 |
MICHELSTEIN; JENNIFER P. ;
et al. |
December 30, 2010 |
USING GAME ELEMENTS TO MOTIVATE LEARNING
Abstract
Elements of game play are incorporated into a productivity
application to assist in motivating users to learn features of the
productivity application. For example, the elements of game play
that are incorporated into learning features of the productivity
application may include items such as usage statistics, scores,
levels, challenges, achievements, competition, and the like. A
recommendation system assists users in determining what features to
learn next. For instance, the recommendations may be based on what
features the user has already learned and/or based on what features
the user's peers are using. Help content that is associated with
the productivity application is also tied to the features that are
currently being used by the user.
Inventors: |
MICHELSTEIN; JENNIFER P.;
(KIRKLAND, WA) ; DUKHON; MARINA; (KIRKLAND,
WA) ; HELIN; JONAS; (KIRKLAND, WA) ; ALEXIEFF;
MARK R.; (CLYDE HILL, WA) ; SHIH; NINA F.;
(REDMOND, WA) |
Correspondence
Address: |
MERCHANT & GOULD (MICROSOFT)
P.O. BOX 2903
MINNEAPOLIS
MN
55402-0903
US
|
Assignee: |
MICROSOFT CORPORATION
Redmond
WA
|
Family ID: |
43381336 |
Appl. No.: |
12/492588 |
Filed: |
June 26, 2009 |
Current U.S.
Class: |
463/23 ; 463/42;
463/43 |
Current CPC
Class: |
A63F 13/46 20140902;
A63F 13/533 20140902; A63F 13/5375 20140902; A63F 2300/558
20130101; A63F 13/798 20140902; A63F 13/47 20140902; G06Q 10/10
20130101; A63F 2300/8064 20130101; G06Q 50/20 20130101; G09B 7/02
20130101 |
Class at
Publication: |
463/23 ; 463/43;
463/42 |
International
Class: |
A63F 9/24 20060101
A63F009/24 |
Claims
1. A method for utilizing game elements within a productivity
application, the method executing on a processor of a computer,
comprising: tracking features being utilized by a user within the
application; wherein the application is a productivity application;
calculating a score as the user utilizes the tracked features;
determining recommendations to provide to the user based on the
tracked features utilized by the user; wherein the recommendations
include new features of the application to learn; providing the
recommendations to the user; displaying the score; receiving a
selection of one of the provided recommendations; and providing a
training challenge to allow a user to practice the recommended
feature that is selected.
2. The method of claim 1, wherein displaying the score comprises
displaying a component score for each of the components that
determine the score.
3. The method of claim 2, further comprising comparing the score to
a group of users using the application; wherein the group of users
is selected by a user of the application.
4. The method of claim 2, further comprising in response to
receiving a selection of one of the provided recommendations
displaying a picture of where functionality relating to the feature
is provided within a menu of the application.
5. The method of claim 2, wherein providing the recommendations to
the user is based on features being used by a group of users using
the application.
6. The method of claim 2, wherein providing the recommendations
comprises incorporating the recommendations into a social
networking site display that is associated with the user.
7. The method of claim 2, further comprising linking help content
that is natively supplied by the application to the training
challenge, such that the linked help content is viewable without
searching for the linked help content.
8. The method of claim 2, wherein the group of users is determined
based on other users having a similar usage pattern to the
user.
9. A computer-readable storage medium having computer-executable
instructions for utilizing game elements within a productivity
application, the instructions executing on a processor of a
computer, comprising: tracking features being utilized by a user
within the application; wherein the application is a productivity
application; calculating a score as the user utilizes the tracked
features; determining recommendations to provide to the user based
on the tracked features utilized by the user; wherein the
recommendations include new features of the application to learn;
directly linking help content that is natively supplied by the
application to each of the recommendations, such that the linked
help content for one of the recommended features is provided to a
user without performing a search for the linked help content;
providing the recommendations within a display; displaying the
score; receiving a selection of one of the provided
recommendations;
10. The computer-readable storage medium of claim 9, further
comprising providing a training challenge to allow a user to
practice the recommended feature that is selected; wherein the
training challenge is provided within a third-party supplied
expansion that is integrated into the application after deployment
of the application.
11. The computer-readable storage medium of claim 10, wherein
displaying the score comprises displaying a component score for
each of the components that determine the score and displaying an
indicator that shows how the score for each component compares to a
group score for the component.
12. The computer-readable storage medium of claim 10, wherein the
group of users for which the score is compared is selected by a
user of the application.
13. The computer-readable storage medium of claim 10, further
comprising in response to receiving a selection of one of the
provided recommendations displaying a graphic of where
functionality relating to the feature is provided within a menu of
the application and a graphic of the feature before the feature is
applied and a graphic of the feature after the feature is
applied.
14. The computer-readable storage medium of claim 10, wherein
providing the recommendations to the user is based on features
being used by a group of users using the application that is
selected by the user.
15. The computer-readable storage medium of claim 10, wherein
providing the recommendations comprises sending the recommendations
to the user through an electronic message.
16. The computer-readable storage medium of claim 10, wherein the
group of users is determined based on other users having a usage
pattern that is approximately equal to the user.
17. A system for utilizing game elements within a productivity
application, comprising: a processor and a computer-readable
medium; an operating environment stored on the computer-readable
medium and executing on the processor; a network connection; a
productivity application and a feature manager operating on the
processor; and configured to perform tasks, comprising: tracking
features being utilized by a user within the application; wherein
the application is a productivity application; calculating a score
as the user utilizes the tracked features; determining
recommendations to provide to the user based on the tracked
features utilized by the user; wherein the recommendations include
new features of the application to learn; directly linking help
content that is natively supplied by the application to each of the
recommendations, such that the linked help content for one of the
recommended features is provided to a user without performing a
search for the linked help content; providing the recommendations
within a display; displaying the score for the user along with a
display showing a component score for each of the components that
determine the score and displaying an indicator that shows how the
score for each component compares to a group score for the
component; receiving a selection of one of the provided
recommendations; and providing a training challenge to allow a user
to practice the recommended feature that is selected.
18. The system of claim 17, wherein providing the training
challenge is provided to at least one other user to create a
head-to-head competition between at least two users.
19. The system of claim 17, wherein providing the recommendations
to the user is based on features being used by a group of users
using the application that is selected by the user.
20. The system of claim 17, wherein providing the recommendations
comprises sending the recommendations to the user through an
electronic message and to a social networking site.
Description
BACKGROUND
[0001] Many individuals spend a lot of time trying to become
proficient at software games. For example, in order to maximize
their points and complete all of the objectives of a game, users
attempt to learn in detail how each level and other aspects of the
game works. Some individuals even play the game to the point where
the game stops being fun and starts being a chore in order to
become proficient.
SUMMARY
[0002] This Summary is provided to introduce a selection of
concepts in a simplified form that are further described below in
the Detailed Description. This Summary is not intended to identify
key features or essential features of the claimed subject matter,
nor is it intended to be used as an aid in determining the scope of
the claimed subject matter.
[0003] Elements of game play are incorporated into a productivity
application to assist in motivating users to learn features of the
productivity application. For example, the elements of game play
that are incorporated into learning features of the productivity
application may include items such as usage statistics, scores,
levels, challenges, achievements, competition, and the like. A
recommendation system is utilized to assist users in determining
what features of the application to learn next. For instance, the
recommendations may be based on what features the user has already
learned and/or based on what features the user's peers or some
other group of users are using. Help content that is associated
with the productivity application can also be tied to the features
that are currently being learned and used by the user such that the
linked help content is readily available.
BRIEF DESCRIPTION OF THE DRAWINGS
[0004] FIG. 1 illustrates a computer architecture for a
computer;
[0005] FIG. 2 shows an example learning system using game elements
for motivating learning within a productivity application;
[0006] FIGS. 3 and 4 show exemplary user interfaces for viewing
performance information and presenting challenges;
[0007] FIG. 5 illustrates an exemplary training challenge that is
utilized in learning a feature;
[0008] FIG. 6 illustrates a process for employing gaming elements
within a application to motivate learning; and
[0009] FIG. 7 shows a process for learning a new feature using game
play elements.
DETAILED DESCRIPTION
[0010] Referring now to the drawings, in which like numerals
represent like elements, various embodiments will be described. In
particular, FIG. 1 and the corresponding discussion are intended to
provide a brief, general description of a suitable computing
environment in which embodiments may be implemented.
[0011] Generally, program modules include routines, programs,
components, data structures, and other types of structures that
perform particular tasks or implement particular abstract data
types. Other computer system configurations may also be used,
including multiprocessor systems, microprocessor-based or
programmable consumer electronics, minicomputers, mainframe
computers, and the like. Distributed computing environments may
also be used where tasks are performed by remote processing devices
that are linked through a communications network. In a distributed
computing environment, program modules may be located in both local
and remote memory storage devices.
[0012] Referring now to FIG. 1, an illustrative computer
architecture for a computer 100 utilized in the various embodiments
will be described. The computer architecture shown in FIG. 1 may be
configured as a desktop, a server, or mobile computer and includes
a central processing unit 5 ("CPU"), a system memory 7, including a
random access memory 9 ("RAM") and a read-only memory ("ROM") 10,
and a system bus 12 that couples the memory to the CPU 5. A basic
input/output system containing the basic routines that help to
transfer information between elements within the computer, such as
during startup, is stored in the ROM 10. The computer 100 further
includes a mass storage device 14 for storing an operating system
16, application programs, and other program modules, which will be
described in greater detail below.
[0013] The mass storage device 14 is connected to the CPU 5 through
a mass storage controller (not shown) connected to the bus 12. The
mass storage device 14 and its associated computer-readable media
provide non-volatile storage for the computer 100. Although the
description of computer-readable media contained herein refers to a
mass storage device, such as a hard disk or CD-ROM drive, the
computer-readable media can be any available media that can be
accessed by the computer 100.
[0014] By way of example, and not limitation, computer-readable
media may comprise computer storage mediums and communication
media. Computer storage mediums includes volatile and non-volatile,
removable and non-removable media implemented in any method or
technology for storage of information such as computer-readable
instructions, data structures, program modules or other data.
Computer storage media includes, but is not limited to, RAM, ROM,
EPROM, EEPROM, flash memory or other solid state memory technology,
CD-ROM, digital versatile disks ("DVD"), or other optical storage,
magnetic cassettes, magnetic tape, magnetic disk storage or other
magnetic storage devices, or any other medium which can be used to
store the desired information and which can be accessed by the
computer 100.
[0015] According to various embodiments, computer 100 operates in a
networked environment using logical connections to remote computers
through a network 18, such as the Internet. The computer 100 may
connect to the network 18 through a network interface unit 20
connected to the bus 12. The network connection may be wireless
and/or wired. The network interface unit 20 may also be utilized to
connect to other types of networks and remote computer systems. The
computer 100 may also include an input/output controller 22 for
receiving and processing input from a number of other devices,
including a keyboard, mouse, or electronic stylus (not shown in
FIG. 1). Similarly, an input/output controller 22 may provide
output to a display screen that includes a user interface 28, a
printer, or other type of output device. User interface (UI) 28 is
designed to provide a user with a visual way to interact with
application 24 that incorporates game play elements for learning
features of the application, as well as to interact with other
functionality that is included on computing device 100.
[0016] As mentioned briefly above, a number of program modules and
data files may be stored in the mass storage device 14 and RAM 9 of
the computer 100, including an operating system 16 suitable for
controlling the operation of a networked computer, such as the
WINDOWS 7.RTM. operating system from MICROSOFT CORPORATION of
Redmond, Wash. The mass storage device 14 and RAM 9 may also store
one or more program modules. In particular, the mass storage device
14 and the RAM 9 may store one or more application programs. One of
the application programs is a productivity application 24, such as
one of the MICROSOFT OFFICE.RTM. programs.
[0017] Generally, productivity application 24 is an application
that a user utilizes in order to complete a task, such as authoring
a document in a word-processing program, programming a feature,
authoring a spreadsheet, and the like. Productivity application 24
is an application such as a word-processing program, a presentation
program, a spreadsheet program, a database program, a programming
environment, and the like. Feature manager 26 is configured to
incorporate elements of game play into productivity application 24
to assist in motivating users to learn how to use features of the
application. For example, the elements of game play that may be
incorporated into the application may include items such as usage
statistics, scores, levels, challenges, achievements, competition,
and the like. Feature manager 26 is configured to track the usage
of the features within the application by a user and provide the
user with feedback relating to the usage of the features as well as
to provide recommendations on what features to learn next. The
recommendations may be based on what features the user has already
learned and/or based on what features the user's peers are using.
Feature manager 26 is also configured to link help content that is
associated with the productivity application with the features that
are currently being used by the user such that the help content for
the feature that is currently being used is available to the user
with a single selection.
[0018] FIG. 2 shows an example learning system using game elements
for motivating learning within a productivity application. As
illustrated, system 200 includes display 28, input 205, and
productivity application 24. Feature manager 26 may be implemented
within presentation application 10 as shown in FIG. 2 or may be
implemented externally from application 24 as shown in FIG. 1.
[0019] In order to facilitate communication with the feature
manager 26, one or more callback routines, illustrated in FIG. 2 as
callback code 210, may be implemented. Through the use of the
callback code 210, the feature manager 26 may query for additional
information used in incorporating the elements of game play within
productivity application 24. For example, feature manager 26 may
request to be informed when a user transitions to another feature
within the application. Other information may also be provided that
relate to the features of the application. As discussed above,
feature manager 26 is configured to incorporate game play elements
into productivity application 24.
[0020] Feature manager 26 utilizes a tracking system 225 that
provides statistics and usage reporting based on what features the
user is utilizing in the application. The features that are tracked
may be any features included within the application. For example,
the features may be a base set of features that broadly covers the
functionality of the application or some other set of features
within the application. Feature manager 26 may store this tracked
information for the user as well as a group of other users. The
features used by the user and tracked by tracking system 225 are
also used to determine a score for the user as determined by score
tracker 220 as well as provide recommendations to the user as to
what features should be learned next.
[0021] Score tracker 220 is configured to map the usage information
for a feature(s) into a quantifiable value that may be converted
into points, badges, levels, scores, and the like. Feature manager
26 is also configured to provide different challenges to a user
that allows them to accumulate additional points, badges, and the
like while learning a new feature of application 24.
[0022] According to an embodiment, a leaderboard is provided that
allows the user to see how they are performing both individually as
well as how they are performing relative to other users. For
example, the group may be a work group, a set of designated
friends, friends from one or more social networking sites, users
who have a same work title, users in the same profession, and the
like. In this way, a user may compare their scores and learning
experience to other similarly situated users. Score tracker 220 is
configured to determine when a user reaches a predetermined score
such that the user is provided with a reward. For example, the
reward may be unlocking videos, pictures, games, customization of
the application, and the like. Score tracker 220 may also be
configured to provide performance information relating to
head-to-head competition between two or more users. For example a
user could challenge one or more other users to play the same
challenge. Feature manager 26 may also be configured to initiate
head-to-head competitions. According to one embodiment, points are
provided to the user in the head-to-head competition who completes
the challenge fastest and/or most efficiently uses the features of
the application to complete the challenge.
[0023] Recommended features 215 is configured to provide
recommendations to the user for what to learn next, based on what
the user has done or not done within the application, and based on
the social element of what features within the productivity
application other users are using and/or have already learned. The
recommended features that are suggested may be based on features
that enhance the features the user is currently using. For example,
if the user uses three features out of a group of five related
features, the other two features that are not used by the user may
be suggested.
[0024] Feature manager 26 is coupled to help system 225 such that
help content that is supplied by the productivity application is
provided to the user based on what features/actions the user is or
is not doing relating to the application. According to an
embodiment, the help system 225 is the help content that is
natively provided by productivity application 24. For example, when
a user is learning feature one as determined by tracking system
225, the help content relating to feature one may be automatically
linked to the feature such that the user may directly select help
for the feature without having to search for the desired help
content. Feature manager 26 tracks what the user is doing and then
proactively surfaces the best help topics for that user.
[0025] Feature manager 26 is also configured to be expandable
through one or more expansions 217. Expansions 217 may add
functionality to feature manager 26 before or after the deployment
of productivity application 24. For example, one or more
"challenge" expansions that add new game/learning elements may be
created by the developer of productivity application 24 and/or
third party developers and then integrated and utilized by feature
manager 26 to present the challenge. The expansions may be
integrated with feature manager 26 using many different methods.
For example, the expansion may be a patch to the productivity
application, a plug-in, and the like.
[0026] Display 28 is configured to provide the user with a visual
display of their score, as well as provide recommendations to the
user and present the user with challenges (See FIGS. 3-5 for
exemplary user interfaces).
[0027] Feature manager 26 is also coupled to other applications 230
such that information relating to the scores and recommendations
may be provided to the other application as well as receiving
information from the other applications. For example, feature
manager 26 may be coupled to a social networking site such that
when a user accesses the social networking site they are able to
see how they are performing using application 24 as well as see how
their linked associates are performing. Feature manager 26 may also
post this performance and recommendation information to other
locations, such as including the information within a news feed of
a social networking site and/or some other location that is
available by users. Another example application that may be linked
is a messaging application such that the performance
information/recommendations can be delivered to one or more users.
Feature manager 26 may also be coupled to a backend data store 240
that is used to store the performance and recommendation
information. This information may be used to compare users with
each other.
[0028] FIG. 3 shows an exemplary user interface for viewing
performance information and presenting challenges. As illustrated,
user interface 300 includes user score 310, graph area 320,
recommendations 325-327, display 330, a before preview picture 335,
an after preview picture 340, and challenge, video, and help
buttons.
[0029] As illustrated, user score 310 shows a score of 1350 that is
based on the features that a user has utilized within the
application. In order to increase the score, a user can accumulate
points by using more features or groups of features that are
associated with the productivity application. In the present
example, the productivity application is a word-processing
application. Other applications may also be utilized. For example,
the performance information may relate to another application
within a suite of programs and/or the entire suite of applications.
According to one embodiment, the more difficult the feature or set
of features utilized, the higher the value that is associated with
the score.
[0030] Graph area 320 displays how the points making up user score
310 are distributed. In this way, a user can see what parts of the
application they are using and how proficient they are at using the
features. Graph area 320 also provides score comparisons based on
other groups of users. As discussed above, these other user groups
may be determined from the user's profession, people who work for
the same company, all users, people at the user's similar level in
the productivity application, people who utilize the application
similarly to the user, people in the user's zip code, age group,
gender, social networking groups, and the like. A group from which
to compare may be selected by utilizing button 321.
[0031] Exemplary user interface 300 provides recommendations (e.g.
325-327) based on the top features the selected group is using that
the user is not currently using and/or based on the features used
by the user. In the present example, three recommendations
(325-327) have been provided to the user. In order to learn these
unused features, a training challenge may be associated with each
suggestion. In the present example, text wrapping 326 around a
picture is recommended for a user. When the user selects one of the
recommendations (i.e. clicking on text wrapping 326), the user is
presented with a display 330 that shows where the feature exists in
the productivity application, a before picture 335 and after
picture 340 that illustrates the benefits of using the feature, and
different types of training such as a short video demo, a challenge
which is like a small game or puzzle where the user is challenged
to use the feature inside the application, and a tie-in to existing
help content.
[0032] FIG. 4 shows another exemplary user interface for viewing
performance information and presenting challenges. As illustrated,
user interface 400 is similar to user interface 300. Achievement
breakdown area 410 provides a user with a view of feature areas
included within an application and how they are performing within
these features areas. As illustrated, most of the score bars are
empty (The Basics, Great Looking Docs, Professional Docs)
indicating that the user has just begun using game play elements
and has many different features to learn.
[0033] Selection area 420 allows a user to select a group from
which the recommendations provided to the user are based as well as
the groups' average achievement score. For example, when one group
is selected a first set of recommendations is provided whereas when
another group is selected, a second set of recommendations is
provided. In this example, the recommendations are based on how the
selected group uses the application and the user is not using the
application. For instance, when the user compares himself to Group
A and Group A uses feature X (that the user does not), a
recommendation provided to the user is to learn feature X. If the
user then compares himself to Group B and Group B does not use
feature X, but instead uses feature Y, feature Y is recommended to
the user.
[0034] FIG. 5 illustrates an exemplary training challenge that is
utilized in learning a feature. In response to a user selecting a
challenge, a challenge is presented to a user that allows them to
learn a feature. In the present example, the challenge is
reformatting table 510 to make it appear as table 520. Many
different challenges may be created for a feature. Area 530
provides the user with information on their progress within the
challenge as well as allowing them to receive a hint using button
531 when they become stuck in the challenge. The user may practice
in the challenge area until they are comfortable with the feature.
Points are also be awarded for completing a challenge. The points
awarded may be determined using many different criteria. For
example, the difficulty of the challenge, the time it took to
complete the challenge, the navigation of the application
functionality, and the like.
[0035] Referring now to FIGS. 6-7, illustrative processes for
employing game elements to motivate learning within a productivity
application is described.
[0036] When reading the discussion of the routines presented
herein, it should be appreciated that the logical operations of
various embodiments are implemented (1) as a sequence of computer
implemented acts or program modules running on a computing system
and/or (2) as interconnected machine logic circuits or circuit
modules within the computing system. The implementation is a matter
of choice dependent on the performance requirements of the
computing system implementing the invention. Accordingly, the
logical operations illustrated and making up the embodiments
described herein are referred to variously as operations,
structural devices, acts or modules. These operations, structural
devices, acts and modules may be implemented in software, in
firmware, in special purpose digital logic, and any combination
thereof.
[0037] FIG. 6 illustrates a process for employing gaming elements
within a application to motivate learning.
[0038] After a start operation, the process flows to operation 610,
where the features within an application that are utilized by a
user are tracked. The features tracked relate to features within
one or more areas of the application. For example, the features may
be divided according to functions performed within the application
(i.e. formatting text, pictures, and the like).
[0039] Moving to operation 620, a score is calculated for each
feature that is utilized. When a user utilizes a new feature, a
score is attached to that action. The score may be dependent upon
many factors, such as feature utilized, time the feature is
utilized, difficulty level, and the like.
[0040] Flowing to operation 630, recommendations are determined for
a user. The recommendations on what feature to learn next may be
based on different items, including what the user has done or not
done within the application and what features other users are
using.
[0041] Transitioning to operation 640, the recommendations are
provided to the user. The recommendations may be provided many
different ways. For example, the recommendations may be provided
within a user interface, the recommendations may be provided within
a social networking site, and/or an electronic message may be sent
to the user that includes the recommendations.
[0042] Moving to operation 650, the score is displayed to the user.
As previously discussed, the score displayed may include an
individual score, as well as scoring information as it relates to
one or more groups of users.
[0043] The process then flows to an end operation and returns to
processing other actions.
[0044] FIG. 7 shows a process for learning a new feature using game
play elements.
[0045] After a start operation, the process flows to operation 710,
where a recommended feature is selected. According to one
embodiment, the feature is selected from a group of recommended
features that are selected for the user.
[0046] Moving to operation 720, the help content that relates to
the selected feature within the application is linked to a training
challenge for the feature. The linked help content is readily
available for the user without the user having to search for a
specific help topic.
[0047] Flowing to operation 730, a training challenge for the
feature is provided to the user. The training challenge allows the
user to use the application in order to practice the feature while
at the same time presenting the challenge using game playing
elements.
[0048] Moving to operation 740, a score is calculated based on the
interaction with the features during the challenge.
[0049] Flowing to operation 750, the user score is updated and
displayed to the user. The user may also be provided with a new
recommendation on what feature to learn next.
[0050] The process then flows to an end operation and returns to
processing other actions.
[0051] The above specification, examples and data provide a
complete description of the manufacture and use of the composition
of the invention. Since many embodiments of the invention can be
made without departing from the spirit and scope of the invention,
the invention resides in the claims hereinafter appended.
* * * * *