U.S. patent application number 15/888799 was filed with the patent office on 2018-06-07 for simulation based learning system and method for training and scoring one or more challenges taken by a user.
The applicant listed for this patent is Analyttica Datalab Inc.. Invention is credited to Rajiv Baphna, Satyamoy Chatterjee, Ashutosh Joshi, Halasya Siva Subramania.
Application Number | 20180158353 15/888799 |
Document ID | / |
Family ID | 52583746 |
Filed Date | 2018-06-07 |
United States Patent
Application |
20180158353 |
Kind Code |
A1 |
Baphna; Rajiv ; et
al. |
June 7, 2018 |
SIMULATION BASED LEARNING SYSTEM AND METHOD FOR TRAINING AND
SCORING ONE OR MORE CHALLENGES TAKEN BY A USER
Abstract
A processor implemented method for scoring a challenge taken by
a user, and training the user using a simulation based learning
platform is provided. The processor implemented method includes (i)
obtaining, from a database, challenges to be taken by a user and
associated at least one of information, (iii) processing a
selection of, the challenge from the challenges with actions or
steps performed by the user, (iv) rendering, hints to solve the
challenge, (v) recording, steps taken by the user to solve the
challenge, (vi) comparing the steps taken by the user with steps
taken by an expert to solve the challenge to compute a deviance of
the user from a reference path, (vii) scoring, the challenge based
on the deviance of the user from the reference path to obtain a
score, and (viii) notifying, a result associated with the challenge
to the user based on the score.
Inventors: |
Baphna; Rajiv; (Bangalore,
IN) ; Chatterjee; Satyamoy; (Bangalore, IN) ;
Subramania; Halasya Siva; (Bangalore, IN) ; Joshi;
Ashutosh; (Bangalore, IN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Analyttica Datalab Inc. |
Wilimington |
DE |
US |
|
|
Family ID: |
52583746 |
Appl. No.: |
15/888799 |
Filed: |
February 5, 2018 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
14477843 |
Sep 4, 2014 |
9886867 |
|
|
15888799 |
|
|
|
|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G09B 5/08 20130101; G09B
5/00 20130101; G09B 7/04 20130101; G09B 7/00 20130101 |
International
Class: |
G09B 7/00 20060101
G09B007/00; G09B 5/00 20060101 G09B005/00 |
Foreign Application Data
Date |
Code |
Application Number |
Sep 5, 2013 |
IN |
3975/CHE/2013 |
Claims
1. A processor implemented method for scoring one or more
challenges taken by a user, and training said user using a
simulation based learning platform, said processor implemented
method comprising: obtaining, from a database, a plurality of
challenges to be taken by a user; obtaining, at least one of
information associated with said plurality of challenges, wherein
said at least one of information associated with said plurality of
challenges is selected from a group comprising (i) a description,
(ii) an objective, (iii) data sets that are created or provisioned,
(iv) rules of navigation, (v) key steps, and (vi) success criteria
among other related components; processing a selection of, at least
one challenge from said plurality of challenges with at least one
actions or steps performed by said user; rendering, one or more
hints to solve said at least one challenge; recording, one or more
steps taken by said user to solve said at least one challenge;
comparing said one or more steps taken by said user with one or
more steps taken by an expert to solve said at least one challenge
to compute a deviance of said user from a reference path; scoring,
said at least one challenge based on said deviance of said user
from said reference path to obtain a score; and notifying, a result
associated with said at least one challenge to said user based on
said score.
2. The processor implemented method of claim 1, further comprising,
(i) computing, by a rule engine module, custom rules for said data
sets which are build based on a type of data, or (ii) applying, an
existing or newly-built rules to said datasets corresponding to
said user challenge.
3. The processor implemented method of claim 1, wherein said one or
more hint is provided to said user (i) upon receiving one or more
prompts from said user, (ii) at predetermined time intervals based
on one or more steps taken by said user to solve said challenge,
(iii) a user level, (iv) admin settings, and (v) user
proficiency.
4. The processor implemented method of claim 1, further comprising,
providing, one or more solutions comprising one or more steps taken
to solve said at least one of challenge by (a) one or more experts,
or (b) one or more users to said users, wherein said one or more
solutions further comprises (i) one or more recommendations or one
or more suggestions to solve said at least one challenge, (ii) one
or more reasons for said one or more steps taken to solve said at
least one challenge by said one or more experts or said one more
users, or (iii) combination thereof.
5. The processor implemented method of claim 4, further comprising,
displaying one or more analytical functions to be used in said one
or more steps to solve said at least one challenge, wherein said
one or more analytical functions are displayed based on one or more
solutions obtained from said one or more experts or said one or
more users.
6. The processor implemented method of claim 5, wherein said score
is calculated based on one or more parameters selected from a group
comprising (i) a time taken to solve said at least one challenge,
(ii) sequence of steps taken, (iii) usage of said one or more
analytical functions in said one or more steps to solve said at
least one challenge, (iv) one or more hints used to solve said at
least one challenge, (v) exhaustiveness of functions among other
parameters to arrive at user score, and (vi) answers to
intermediate questions within said at least one challenge and at
end of said at least one challenge.
7. The processor implemented method of claim 5, further comprising,
providing, one or more solutions in a format selected from a group
comprising, (i) one or more audio, (ii) one or more video, (iii)
one or more text, or (iv) a combination thereof.
8. The processor implemented method of claim 6, further comprising,
(i) tracking a progress associated with said at least one
challenge, (ii) displaying a progress indicator for said at least
one challenge taken by said user, wherein said progress indicator
comprises (i) a progress level of said user associated with said at
least one challenge, or (ii) a comparison of a performance between
(i) said user and said one or more experts, (ii) said user and said
one or more users, or (iii) combinations thereof, and wherein said
performance comprises said one or more parameters.
9. A computer implemented system for scoring one or more challenges
taken user and training said user using a simulation based learning
platform, said computer implemented system comprising: (i) a memory
unit that stores (a) a set of modules, (b) a database, and
instructions, wherein said database comprises at least one of (i)
store one or more user information, and (ii) information
corresponding to content related to course and challenge; and (ii)
a processor when configured by said instructions executes said set
of modules, wherein said set of modules comprises: (a) a challenge
information obtaining module, executed by said processor, that
obtains at least one of information associated with a plurality of
challenges, wherein said plurality of challenges are obtained from
said database; (b) a challenge selection module, executed by said
processor, that processes a selection of at least one challenge
from said plurality of challenges one or more actions or one or
more steps performed by said user; (c) a hint rendering module,
executed by said processor, that renders one or more hints to solve
said at least one challenge; (d) a steps recording module, executed
by said processor, that records one or more steps taken by said
user to solve said at least one challenge; (e) a steps comparing
module, executed by said processor, compares said one or more steps
taken by said user with one or more steps taken by one or more
experts to solve said at least one challenge to compute a deviance
of said user from a reference path; and (f) a scoring module,
executed by said processor, that scores said at least one challenge
based on said deviance of said user from said reference path to
obtain a score.
10. The computer implemented system of claim 9, further comprising,
a rule engine module, executed by said processor, that (i) computes
custom rules for said data sets which are build based on a type of
data, or (ii) applying, an existing or newly-built rules to said
datasets corresponding to said user challenge.
11. The computer implemented system of claim 9, wherein said one or
more hints is provided to said user (i) upon receiving one or more
prompts from said user, (ii) at predetermined time intervals based
on one or more steps taken by said user to solve said challenge,
(iii) a user level, (iv) admin settings, and (v) user
proficiency.
12. The computer implemented system of claim 9, wherein said at
least one of information associated with said plurality of
challenges is selected from a group comprising (i) a description,
(ii) an objective, (iii) data sets that are created or provisioned,
(iv) rules of navigation, (v) key steps, and (vi) success criteria
among other related components.
13. The computer implemented system of claim 9, further comprising,
a notification module, executed by said processor, notifies results
associated with said plurality of challenges to said user based on
gamification elements.
14. The computer implemented system of claim 9, wherein one or more
solutions comprises one or more steps taken to solve said at least
one of challenge provided by (a) one or more experts, or (b) one or
more users to said users, wherein said one or more solutions
further comprises (i) one or more recommendations or one or more
suggestions to solve said at least one challenge, (ii) one or more
reasons for said one or more steps taken to solve said at least one
challenge by said one or more experts or said one more users, or
(iii) combinations thereof.
15. The computer implemented system of claim 14, further
comprising, a display module when executed by said processor
displays one or more analytical functions to be used in said one or
more steps to solve said at least one challenge, wherein said one
or more analytical functions are displayed based on one or more
solutions obtained from said one or more experts or said one or
more users.
16. The computer implemented system of claim 15, wherein said score
is calculated based on one or more parameters selected from a group
comprising (i) a time taken to solve said at least one challenges,
(ii) sequence of steps taken, (iii) usage of said one or more
analytical functions in said one or more steps to solve said at
least one challenge, (iv) one or more hints used to solve said at
least one challenge, (v) exhaustiveness of functions among other
parameters to arrive at user score, and (vi) answers to
intermediate questions within said at least one challenge and at
end of said at least one challenge.
17. The computer implemented system of claim 9, further comprising,
a playback module, executed by said processor, that playbacks each
step taken by said user or said expert while solving said at least
one of challenge.
18. The computer implemented system of claim 6, further comprising,
(i) a progress tracking module that tracks a progress associated
with said at least one challenge is tracked, (ii) display a
progress indicator for said at least one challenge taken by said
user, wherein said progress indicator comprises (i) said progress
of said user associated with said at least one challenge, or (ii) a
comparison of a performance between (i) said user and said one or
more experts, (ii) said user and said one or more users, or (iii)
combinations thereof, and wherein said performance comprises said
one or more parameters.
19. The computer implemented system of claim 9, a performance
determination module, executed by said processor that determines a
performance level based on at least a subset of said plurality of
challenges taken by said user.
20. The computer implemented system of claim 9, a training
determination and recommendation module, executed by said
processor, that (a) determines a knowledge level based on said
performance level during an attempt made by said user to solve (i)
said at least one challenge, (ii) said subset, or said plurality of
challenges, and (b) recommends one or more training courses based
on (i) said performance level or (ii) said knowledge level to solve
subsequent challenges.
21. One or more non-transitory computer readable storage mediums
storing one or more sequences of instructions, which when executed
by one or more processors, causes obtaining, from a database, a
plurality of challenges to be taken by a user; obtaining, at least
one of information associated with said plurality of challenges,
wherein said at least one of information associated with said
plurality of challenges is selected from a group comprising (i) a
description, (ii) an objective, (iii) data sets that are created or
provisioned, (iv) rules of navigation, (v) key steps, and (vi)
success criteria among other related components; processing a
selection of, at least one challenge from said plurality of
challenges with at least one actions or steps performed by said
user; rendering, one or more hints to solve said at least one
challenge; recording, one or more steps taken by said user to solve
said at least one challenge; comparing said one or more steps taken
by said user with one or more steps taken by an expert to solve
said at least one challenge to compute a deviance of said user from
a reference path; and scoring, said at least one challenge based on
said deviance of said user from said reference path to obtain a
score.
22. The one or more non-transitory computer readable storage
mediums of claim 21, further comprising, determining a performance
level based on at least a subset of said plurality of challenges
taken by said user.
23. The one or more non-transitory computer readable storage
mediums of claim 21, further comprising, (a) determining a
knowledge level based on said performance level during an attempt
made by said user to solve (i) said at least one challenge, (ii)
said subset, or (iii) said plurality of challenges, and (b)
recommending one or more training courses based on (i) said
performance level or (ii) said knowledge level to solve subsequent
challenges.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claim priority to Indian patent application
no. 3975/CHE/2013 filed on Sep. 5, 2013, the complete disclosure of
which, in its entirely, is herein incorporated by reference.
BACKGROUND
Technical Field
[0002] The embodiments herein generally relate to learning
management system, and more particularly to simulation based
learning system and method for training and scoring one or more
challenges taken by a user.
Description of the Related Art
[0003] Learning in analytics or related fields currently is highly
focused on knowing the tools as against the concepts i.e. focused
on `how` to apply as against `what` and `when` to apply, which is
more fundamental to learning. This translates to knowing the
underlying `statistical packages/product/code` than on statistical
concepts. The current mode of education (in statistics and
analytics or other related fields) is through online learning,
video sessions or personal training, mostly in unilateral direction
(one way learning). The current model of online education or
in-person is non-scalable and requires availability of the right
talent to teach, which is a constraint in most cases. The online
education mode relies on `one size fits all` approach, which does
not yield right results considering the diversity of talent and it
doesn't customize learning to individual needs. There are various
learning platforms out in the market, which control user's steps
and activities at very granular level. Accordingly, there remains a
need for platform with experience based learning to individual
needs which allows a user to experience real life scenarios with
better interactive learning in real time and in a collaborative
manner.
SUMMARY
[0004] In view of the foregoing, an embodiment herein provides a
processor implemented method for scoring one or more challenges
taken by a user, and training the user using a simulation based
learning platform. The processor implemented method includes (i)
obtaining, from a database, a plurality of challenges to be taken
by a user, (ii) obtaining, at least one of information associated
with the one or more challenges, (iii) processing a selection of,
at least one challenge from the one or more challenges with at
least one actions or steps performed by the user, (iv) rendering,
one or more hints to solve the at least one challenge, (v)
recording, one or more steps taken by the user to solve the at
least one challenge, (vi) comparing the one or more steps taken by
the user with one or more steps taken by an expert to solve the at
least one challenge to compute a deviance of the user from a
reference path, (vii) scoring, the at least one challenge based on
the deviance of the user from the reference path to obtain a score,
and (viii) notifying, a result associated with the at least one
challenge to the user based on the score. The at least one of
information associated with the one or more challenges is selected
from a group includes (a) a description, (b) an objective, (c) data
sets that are created or provisioned, (d) rules of navigation, (e)
key steps, and (f) success criteria among other related
components.
[0005] The processor implemented method may further includes (i)
computing, by a rule engine module, custom rules for the data sets
which are build based on a type of data, or (ii) applying, an
existing or newly-built rules to the datasets corresponding to the
user challenge. The one or more hint may provided to the user (i)
upon receiving one or more prompts from the user, (ii) at
predetermined time intervals based on one or more steps taken by
the user to solve the challenge, (iii) a user level, (iv) admin
settings, and (v) user proficiency. The processor implemented
method may further includes, providing, one or more solutions
includes one or more steps taken to solve the at least one of
challenge by (a) one or more experts, or (b) one or more users to
the users, the one or more solutions further includes (i) one or
more recommendations or one or more suggestions to solve the at
least one challenge, (ii) one or more reasons for the one or more
steps taken to solve the at least one challenge by the one or more
experts or the one more users, or (iii) combination thereof.
[0006] The processor implemented method may further includes,
displaying one or more analytical functions to be used in the one
or more steps to solve the at least one challenge. The one or more
analytical functions may be displayed based on one or more
solutions obtained from the one or more experts or the one or more
users. The score may be calculated based on one or more parameters
selected from a group includes (i) a time taken to solve the at
least one challenge, (ii) sequence of steps taken, (iii) usage of
the one or more analytical functions in the one or more steps to
solve the at least one challenge, (iv) one or more hints used to
solve the at least one challenge, (v) exhaustiveness of functions
among other parameters to arrive at user score, and (vi) answers to
intermediate questions within the at least one challenge and at end
of the at least one challenge.
[0007] In one aspect, a computer implemented system for scoring one
or more challenges taken by a user and training the user using a
simulation based learning platform is provided. The computer
implemented system includes (i) a memory unit that stores (a) a set
of modules, (b) a database, and instructions; (ii) a processor when
configured by the instructions executes the set of modules. The
database includes at least one of (i) store one or more user
information, and (ii) information corresponding to content related
to course and challenge. The set of modules includes (a) a
challenge information obtaining module, executed by the processor,
that obtains at least one of information associated with one or
more challenges, the one or more challenges are obtained from the
database, (b) a challenge selection module, executed by the
processor, that processes a selection of, at least one challenge
from the one or more challenges one or more actions or one or more
steps performed by the user, (c) a hint rendering module, executed
by the processor, that renders one or more hints to solve the at
least one challenge, (e) a steps comparing module, executed by the
processor, compares the one or more steps taken by the user with
one or more steps taken by one or more experts to solve the at
least one challenge to compute a deviance of the user from a
reference path, (f) a scoring module, executed by the processor,
that scores the at least one challenge based on the deviance of the
user from the reference path to obtain a score.
[0008] The processor implemented method may further includes,
providing, one or more solutions are provided in a format selected
from a group includes, (i) one or more audio, (ii) one or more
video, (iii) one or more text, or (iv) a combination thereof. The
processor implemented method may further includes, (i) tracking a
progress associated with the at least one challenge, (ii)
displaying a progress indicator for the at least one challenge
taken by the user. The progress indicator may include (i) a
progress level of the user associated with the at least one
challenge, or (ii) a comparison of a performance between (i) the
user and the one or more experts, the user and the one or more
users, or (iii) combinations thereof. The performance includes the
one or more parameters.
[0009] The computer implemented system may further includes, a rule
engine module, executed by the processor, that (i) computes custom
rules for the data sets which are build based on a type of data, or
(ii) applying, an existing or newly-built rules to the datasets
corresponding to the user challenge. The one or more hints may be
provided to the user (i) upon receiving one or more prompts from
the user, predetermined time intervals based on one or more steps
taken by the user to solve the challenge, (iii) a user level, (iv)
admin settings, and (v) user proficiency. The at least one of
information associated with the plurality of challenges may be
selected from a group includes (i) a description, (ii) an
objective, (iii) data sets that are created or provisioned, (iv)
rules of navigation, (v) key steps, and (vi) success criteria among
other related components.
[0010] The computer implemented system may further includes, a
notification module, executed by the processor, notifies results
associated with the one or more challenges to the user based on
gamification elements. The one or more solutions may includes one
or more steps taken to solve the at least one of challenge provided
by (a) one or more experts, or (b) one or more users to the users.
The one or more solutions may further includes (i) one or more
recommendations or one or more suggestions to solve the at least
one challenge, (ii) one or more reasons for the one or more steps
taken to solve the at least one challenge by the one or more
experts or the one more users, or (iii) combinations thereof. The
computer implemented system may further includes, a display module
when executed by the processor displays one or more analytical
functions to be used in the one or more steps to solve the at least
one challenge. The one or snore analytical functions are displayed
based on one or more solutions obtained from the one or more
experts or the one or more users.
[0011] The score may be calculated based on one or more parameters
selected from a group includes (i) a time taken to solve the at
least one challenges, (ii) sequence of steps taken, (iii) usage of
the one or more analytical functions in the one or more steps to
solve the at least one challenge, (iv) one or more hints used to
solve the at least one challenge, (v) exhaustiveness of functions
among other parameters to arrive at user score, and (vi) answers to
intermediate questions within the at least one challenge and at end
of the at least one challenge.
[0012] The computer implemented system may further includes, a
playback module, executed by the processor, that playbacks each
step taken by the user or the expert while solving the at least one
of challenge. The computer implemented system may further includes,
(i) a progress tracking module that tracks a progress associated
with the at least one challenge is tracked, (ii) display a progress
indicator for the at least one challenge taken by the user. The
progress indicator may include (i) the progress of the user
associated with the at least one challenge, or (ii) a comparison of
a performance between (i) the user and the one or more experts,
(ii) the user and the one or more users, or (iii) combinations
thereof. The performance includes the one or more parameters. The
computer implemented system may further include a performance
determination module, executed by the processor that determines a
performance level based on at least a subset of the plurality of
challenges taken by the user. The computer implemented system may
further include a training determination and recommendation module,
executed by the processor, that (a) determines a knowledge level
based on the performance level during an attempt made by the user
to solve (i) the at least one challenge, (ii) the subset, or (iii)
the plurality of challenges, and (b) recommends one or more
training courses based on (i) the performance level or (ii) the
knowledge level to solve subsequent challenges.
[0013] In yet another aspect, one or more non-transitory computer
readable storage mediums storing one or more sequences of
instructions, which when executed by one or more processors is
provided. One or more non-transitory computer readable storage
mediums includes (i) obtaining, from a database, a plurality of
challenges to be taken by a user, (ii) obtaining, at least one of
information associated with the one or more challenges, (iii)
processing a selection of, at least one challenge from the one or
more challenges with at least one actions or steps performed by the
user, (iv) rendering, one or more hints to solve the at least one
challenge, (v) recording, one or more steps taken by the user to
solve the at least one challenge, (vi) comparing the one or more
steps taken by the user with one or more steps taken by an expert
to solve the at least one challenge to compute a deviance of the
user from a reference path, (vii) scoring, the at least one
challenge based on the deviance of the user from the reference path
to obtain a score, and (viii) notifying, a result associated with
the at least one challenge to the user based on the score. The at
least one of information associated with the one or more challenges
is selected from a group includes (a) a description, (b) an
objective, (c) data sets that are created or provisioned, (d) rules
of navigation, (e) key steps, and (f) success criteria among other
related components. The one or more non-transitory computer
readable storage mediums may further include determining a
performance level based on at least a subset of the plurality of
challenges taken by the user.
[0014] The one or more non-transitory computer readable storage
mediums, further include, (a) determining a knowledge level based
on the performance level during an attempt made by the user to
solve (i) the at least one challenge, (ii) the subset, or (iii) the
plurality of challenges, and (b) recommending one or more training
courses based on (i) the performance level or (ii) the knowledge
level to solve subsequent challenges.
[0015] These and other aspects of the embodiments herein will be
better appreciated and understood when considered in conjunction
with the following description and the accompanying drawings. It
should be understood, however, that the following descriptions,
while indicating preferred embodiments and numerous specific
details thereof, are given by way of illustration and not of
limitation. Many changes and modifications may be made within the
scope of the embodiments herein without departing from the spirit
thereof, and the embodiments herein include all such
modifications.
BRIEF DESCRIPTION OF THE DRAWINGS
[0016] The embodiments herein will be better understood from the
following detailed description with reference to the drawings, in
which:
[0017] FIG. 1 illustrates a system view of a user interacting with
an simulation based learning platform through a computing device
for data oriented learning according to an embodiment herein;
[0018] FIG. 2 illustrates an exploded view of the simulation based
learning platform according to an embodiment herein;
[0019] FIG. 3 illustrates an user interface view of interaction
with an simulation based learning platform through a computing
device for data oriented learning according to an embodiment
herein;
[0020] FIG. 4 illustrates a user interface view of a user solving
an at least one challenge to achieve an interactive-learning
according to an embodiment herein;
[0021] FIG. 5 illustrates a user interface view of receiving one or
more hints while solving the at least one challenge according to an
embodiment herein;
[0022] FIG. 6 illustrates a user interface view of a user score
sheet for the challenge taken by a user according to an embodiment
herein;
[0023] FIG. 7 illustrates a user interface view of an expert
solution sheet for the at least one challenge according to an
embodiment herein.
[0024] FIG. 8 illustrates a user interface view of a consolidated
rank sheet of the user specific to one or more challenges according
to an embodiment herein;
[0025] FIG. 9 illustrates a user interface view of an user profile
sheet according to an embodiment herein;
[0026] FIG. 10 is an interaction diagram illustrating a processor
implemented method for training and scoring one or more challenges
taken by a user using a simulation based learning platform
according to an embodiment herein;
[0027] FIG. 11 illustrates an exploded view of the computing device
having an a memory having a set of computer instructions, a bus, a
display, a speaker, and a processor capable of processing a set of
instructions to perform any one or more of the methodologies
herein, according to an embodiment herein;
[0028] FIG. 12 is a flow diagram illustrates a method for training
and scoring one or more challenges taken by a user using a
simulation based learning platform according to an embodiment
herein; and
[0029] FIG. 13 a schematic diagram of computer architecture used in
accordance with the embodiment herein.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
[0030] The embodiments herein and the various features and
advantageous details thereof are explained more fully with
reference to the non-limiting embodiments that are illustrated in
the accompanying drawings and detailed in the following
description. Descriptions of well-known components and processing
techniques are omitted so as to not unnecessarily obscure the
embodiments herein. The examples used herein are intended merely to
facilitate an understanding of ways in which the embodiments herein
may be practiced and to further enable those of skill in the art to
practice the embodiments herein. Accordingly, the examples should
not be construed as limiting the scope of the embodiments
herein.
[0031] As mentioned, there remains a need for platform with
experience based learning to individual needs which allows a user
to experience real life scenarios and explore the options and
analyze data with better interactive learning on real time. The
embodiments herein achieve this by providing an
interactive-learning platform for data oriented learning with
focuses on one or more application of concepts based on simulation
of real business scenarios also by providing scenarios with
appropriate data sets and interfaces to tools. A simulation based
learning platform provides a simulation based learning system and
method for scoring one or more challenges taken by a user and
trains the user. Referring now to the drawings, and more
particularly to FIGS. 1 through 13, where similar reference
characters denote corresponding features consistently throughout
the figures, there are shown preferred embodiments.
[0032] FIG. 1 illustrates a system view of a user 102 interacting
with a simulation based learning platform 106 through the computing
device 104 for data oriented lea g according to an embodiment
herein. The system 100 includes the user 102, a computing device
104, a simulation based learning platform 106, and a network 108.
The user 102 interacts with the simulation based learning platform
106 through the computing device 104 for interactive-learning on
data oriented, learning (e.g., analytics, science) which focuses on
one or more application of concepts based on simulation. In one
embodiment, the simulation based learning platform 106 is a
web-based interactive-learning platform for analytics which
incorporates elements of serious-games such as simulation and
gamification along with machine-learning, collaboration, and
intelligent scoring. In one embodiment, the simulation based
learning platform 106 may be breaking of learning into concept of
applications which are unique to a user.
[0033] In one embodiment, the system may render a user action into
corresponding code required by the platform. For e.g. if a package
chosen is `R`, an R-code is generated by the underlying system for
the user action. In one embodiment, converting a user action (e.g.,
a user clicks) to various programming or computing instructions
(e.g., R, SAS codes) with scores and assessment (areas of
improvement) for experiential learning on analytics. In one
embodiment, learning may be segmented into at least two phases
(e.g., concept and execution using appropriate package. In one
embodiment, the simulation based learning platform 106 is
implemented in the computing device 104.
[0034] In another embodiment, the simulation based learning
platform 106 is implemented in a remote server. In one embodiment,
the simulation based learning platform 106 communicates with the
computing device 104 through the network 108. In another
embodiment, the network may be an internet. In one embodiment, the
computing device 104 is selected from a group comprising a personal
computer, a mobile communication device, a smart phone, a tablet
PC, a laptop, a desktop, and an ultra-book.
[0035] FIG. 2 illustrates an exploded view of the simulation based
learning platform 106 according to an embodiment herein. The
exploded view 106 includes a database 202, challenge information
obtaining module 204, a challenge selection module 206, a hint
rendering module 208, a steps recording module 210, a steps
comparing module 212, a scoring module 214, and a notification
module 216. In one embodiment, a database 202 that store (i) one or
more user information, and (ii) information corresponding to
content related to course and challenge. In one embodiment, the
database 202 may reside in remote server. For example, information
associated with a plurality of challenges is retrieved from a
database (Not shown in figure). The challenge information obtaining
module 204 obtains at least one of information associated a
plurality of challenges. The plurality of challenges ma be obtained
from the database 202. In one embodiment, one or more
lesson/challenge may have success criteria and the success criteria
may be within the challenge/lesson as well.
[0036] The challenge selection module 206 processes a selection of,
at least one challenge from the plurality of challenges with at
least one or more actions or one or more steps performed by the
user. The hint rendering module 208 renders one or more hints to
solve the at least one challenge selected by the user. The one or
more hints is provided to the user (i) upon receiving one or more
prompts from the user, (ii) at predetermined time intervals based
on one or more steps taken by the user to solve the challenge,
(iii) based on a user level, (iv) or more administrative settings,
and (v) a user proficiency.
[0037] For example, the hint rendering module 208 may be chosen
during such modes of training which may render a right hint and one
or more instructions to the user/trainee, (i) when the user/trainee
prompts for a hint or (ii) when the system requires an appropriate
time to provide hint based on a solution path taken by the
user/trainee. For example, outcome of the hint which is used by the
user/trainee is communicated to the scoring engine 214 and
evaluator which helps to arrive at final score for the
exercise/challenge. The hint rendering module 208 may be configured
up to be collaborative, where users who are solving a challenge
which are provided with hints from users/trainees who have solved
the challenge earlier. The one or more instructions are rendered to
the user 102 while solving the at least one of challenge.
[0038] The steps recording module 210 records one or more steps
taken by the user 102 to solve the at least one challenge. In one
embodiment, the steps recording module 210 may include built-in
intelligence to identify which are exploratory steps and which are
the steps which alter the data. In one embodiment, one or more
steps taken by the user/trainee may be displayed with hyperlink in
order to scroll back to the steps preferred by the user while
executing the challenge. In one embodiment, one or more steps are
highlighted, with one more color code in order to specify a status
of the one or more steps and/or progress of a challenge (e.g.,
start, completed) by the user. In another embodiment, the steps
recording module 210 interacts with the scoring module 214 to
compute deviance of the user/trainee from a reference path.
[0039] The simulation based learning platform 106 includes a
playback module, that playback each step taken by the user or the
expert while solving the same challenge. For example, the user 102
checks previous steps and next steps while solving the case to
avoid error/correction. In one embodiment, the playback option may
be used as a mode of learning in which a learner pickup challenges
from the challenge repository module and replay how various experts
have solved the challenge. In one embodiment, the playback module
provide an option of accessing a comparison one or more steps,
e.g., comparing the steps taken by the user/trainee and the steps
taken by the expert is viewed.
[0040] The steps comparing module 212 compares the one or more
steps taken by the user with one or more steps taken by one or more
experts to solve the at least one challenge to compute a deviance
of the user from a reference path. In one embodiment, one or more
solutions provided which includes one or more steps taken to solve
the at least one of challenge by (a) one or more experts, or (b)
one or more users to the users. One or more solutions further
includes (i) one or more recommendations or one or more suggestions
to solve the at least one challenge, (ii) one or more reasons for
the one or more steps taken to solve the at least one challenge by
the one or more experts or the one more users, or (iii) combination
thereof.
[0041] The scoring module 214 scores the at least one challenge
based on the deviance of the user from the reference path to obtain
a score. The score is calculated based on one or more parameters
selected from a group includes (i) a time taken to solve the at
least one challenge, (ii) sequence of steps taken, (iii) usage of
the one or more analytical functions in the one or more steps to
solve the at least one challenge, (iv) one or more hints used to
solve the at least one challenge, (v) exhaustiveness of functions
among other parameters to arrive at user score, and (vi) answers to
intermediate questions within the at least one challenge and at end
of the at least one challenge.
[0042] A display module 218 that displays one or more analytical
functions to be used in the one or more steps to solve the at least
one challenge. The one or more analytical functions are displayed
based on one or more solutions obtained from the one or more
experts or the one or more users. The simulation based learning
platform 106 may further include a progress tracking module that
tracks a progress associated with the at least one challenge is
tracked. Then, a progress indicator for the at least one challenge
taken by the user is displayed. The progress indicatory include at
least one of (i) the progresses of the user associated with the at
least one challenge, or (ii) a comparison of a performance between
(i) the user and the one or more experts, (ii) the user and the one
or more users, or (iii) combinations thereof. In one embodiment,
the performance includes the one or more parameters. The simulation
based learning platform 106 may further include a rule engine
module that (i) computes custom rules for the data sets which are
build based on a type of data, or (ii) applying, an existing or
newly-built rules to the datasets corresponding to the user
challenge. In one embodiment, the custom rules are rules that are
applicable for certain variables or columns based on the context of
data. For example, a "customer ID" and an "age" are both numeric,
but they can't be treated in a similar manner. The customer ID may
be primary, in which case, in which one treat the missing values by
replacing with median or mode, whereas this rule is not applicable
to "Age". Similarly, the rules may apply if data sets or columns
are marked as continuous or descriptive etc. In one embodiment, the
custom rules are driven by context and variable types marked and
tagged while uploading the data or while creating the plurality of
challenge.
[0043] The simulation based learning platform 106 may further
include an identity and access management module performs
authentication and authorization of a user along with user's
session management and self-service module. The simulation based
learning platform 106 may further include a challenge repository
module which facilitates creation of the plurality of
challenges/lessons and stores the plurality of challenges. For
example, at least one of information associated with the plurality
of challenges is at least one of (i) a description, (ii) an
objective, (iii) data sets that may be created or provisioned, (iv)
rules of navigation, (v) key steps, and (vi) success criteria among
other related components. The key steps are mandatory steps as per
an expert that has to be followed by the user to solve the at least
one challenge. A few steps may be exploratory (e.g., drawing
charts) which is more to get a sense of data, while a few of them
(e.g., regressions) are necessary within a challenge depending on
the challenge's objective.
[0044] The simulation based learning platform 106 may further
include a course managing module manages one or more courses
together and associates the one or more courses under each
sub-category. In one embodiment, there the one or more courses may
include at least one of (i) an associated tagging and (ii) a
hierarchy system. For example, the one or more courses are tagged
with appropriate keywords which may be indexed and searchable by a
user. The courses uploaded may be placed under an appropriate
hierarchy system (e.g.
Subject.fwdarw.Topic.fwdarw.Chapter.fwdarw.Lessons (or) Industry
Sub-industry.fwdarw.Topic.fwdarw.Challenge). The simulation based
learning platform 106 may further include a course uploader module
may provide an option for experts and/or tutors to upload co s
s/challenges/cases which can be solved by other users. The
simulation based learning platform 106 may further include a
statistics package updating module allows automated enhancement of
statistical functions within the simulation based learning platform
106, but not limited to, may be added and build on existing
statistical modules.
[0045] The notification module 216 notifies results associated with
the plurality of challenges to the user based on gamification
elements. For example, the gamification elements are points,
badges, level unlock leadership boards to engage users with better
notification. In one embodiment, the notification module 216 may
provide the notification (e.g., multimedia content) to the user
102. For example, the multimedia content may be an audio
representation, text representation, video representation, and icon
representation. In one embodiment, the notification module 216 may
interact with other modules such as scoring module 214, course
managing module and evaluator.
[0046] The simulation based learning platform 106 may further
include a machine learning module includes machine learning
component allowing system to mature in discovering the
optimal/recommended path for challenges and cases. In one
embodiment, an optimal path generated by the machine learning
component may be used to scale up and grade users accordingly. The
simulation based learning platform 106 may further include a user
dashboard module may provide one or more functionality to track
user progress and status. In one embodiment, the notification
module 216 may interact with the user dashboard module to provide a
snapshot of the gamification elements earned by the user 102. In
one embodiment, mailbox may be accessible from the user dashboard
module. The simulation based learning platform 106 may further
include a management information system (MIS) module may provide a
reports and progress cards at a user, group or institution level.
The simulation based learning platform 106 may further include a
feedback and collaboration module provides components to collect
feedback at a course or module or platform level. In another
embodiment, the feedback and collaboration module may provide
collaboration e.g., chat, forums, email, discussion boards for
enabling a better interaction among users and/or between system and
the user.
[0047] FIG. 3 illustrates a user interface view 300 of interaction
with the simulation based learning platform 106 through a computing
device for data oriented learning according to an embodiment
herein. The view 300 includes a category field 302A, a
specification field 302B, a classification field 304, a review
challenge field 306, and a solve challenge field 308. In one
embodiment, when a user clicks on the category field 302, one or
more categories (e.g., a financial service industry) are displayed.
The specification field 302B provides information regarding a
domain (e.g., finance, and retail) of learning. The classification
field 304 classifies an industry (e.g., consumer banking). In one
embodiment, one or more challenge with corresponding status (e.g.,
review, resume, solve) for a user action is displayed. The review
challenge field 306 which helps to review a challenge completed by
a user. For example, a challenge completed by a user is ready for
review or redo. The solve challenge field 308 displays one or more
challenges for solving. For example, when a user clicks on the
solve challenge field 308 the user can proceed with the challenge
for solving. In one embodiment, title of a challenge corresponding
description may be displayed to the user 102. In one embodiment,
the user 102 may resume with challenge at an interrupted stage
(e.g., when a user pauses before completion of the challenge) when
the user clicks on `a resume challenge` field.
[0048] FIG. 4 illustrates a user interface view of a user 102
solving a challenge to achieve an interactive-learning according to
an embodiment herein. The view includes an objective field 402, a
steps field 404, a hints field 406, an instructions field 408, an
undo step field 410, a submit field 412, and datasets field 414. In
one embodiment, when a user clicks on a case field which displays a
business case. For example, the case field explains business
problem, analytics problem, client's dilemma, overall expectation
of a client, and an overview of what a data represents. In one
embodiment, a data dictionary field provides information
corresponding to one or more data's in the column for a particular
challenge. In one embodiment, data is a sample of a customer base
having 3 Identifiers (ID). For example, (i) an household ID which
represents a unique identifier for the household (one household can
have multiple customers and each customer can have multiple
accounts), (ii) an Customer ID which represents a unique customer,
and (iii) an account ID which represents an account.
[0049] In one embodiment, when a user clicks on the objective field
402 which provides a list of objectives for the challenge. For
example, the user needs to solve an analytics problem such as three
objectives `objective 1`, `objective 2`, `objective 3`. For
example, an objective in which determine which of following factors
(i) Household size, (ii) Household age, (iii) Home ownership
status, (iv) Marital status, (v) Wealth segment, and (vi) Vintage
of the relationship have influence on a volume of household deposit
balance with a bank and an overall deposit balance respectively.
Rank order by influencing factors and compare the influence to
bank's deposit balance and overall deposit balance.
[0050] In one embodiment, when a user clicks on the steps field 404
one or more steps performed by a user to solve a challenge are
displayed and the steps are updated as and when the user modifies
the steps. In one embodiment, when a user clicks on the hints field
406 which facilitate an hint which is displayed for completing
instructions and helps the user to progress further to complete the
challenge also address most of concerns the user. In one
embodiment, functions to achieve the instruction are conveyed to
the user. In one embodiment, when a user clicks on the instructions
field 408 the instruction for solving the challenge is conveyed to
the user. In one embodiment, when a user clicks on the undo step
field 410 th platform helps to undo a particular step when an error
occurs while performing a challenge. In another embodiment, when
the user clicks on the undo step 410 which helps he/she to proceed
in right way while performing the challenge. The user clicks on the
submit field 412, once he/she completes all the involved within the
challenge. In one embodiment, the user may chat with other
user/trainee/experts while taking up the challenge,
[0051] In one embodiment, instructions support how to break down
the case into smaller parts for analysis. In one embodiment, the
hints are requested by the user (but not limited to, accessing
hints affects a user's score). For example, upon clicking on the
hint icon, an appropriate hint is displayed to the user based on
user's current position. Similarly, `Functions` are the right steps
which are recommended by expert, in order to successfully complete
the instruction. In one embodiment, `Context/Column` field
represents the column/row/cell on which the recommended `function`
may be performed. In one embodiment, `Blacklisted rules` represents
a definite `No`-`No` in which points are deducted for these
actions. In one embodiment, a chart output field displays output to
the user in a chart format.
[0052] FIG. 5 illustrates a user interface view of receiving one or
more hints while solving the at least one challenge according to an
embodiment herein. The view 500 includes a hint rendering field
502. The hint rendering field 502 renders one or more hints to the
user while solving the at least one challenge. For example, the
user while solving bank challenge the one or more hints are
provided such as "Account number is the primary key of the table
which should be unique". There is a provision for the user 102 to
access one or more hints if the one provided is not helping the
user to solve the one or more steps associated with the at least
one challenge.
[0053] FIG. 6 illustrates a user interface view of a user score
sheet for the challenge taken by a user according to an embodiment
herein. The view 600 includes a score field 602, a category score
field 604, an objective score field 606, a comment field 608, and a
view expert solution field 610. The score field 602 displays a
score and percentage of deviation achieved by the user for a
challenge. The category score field 604 displays a score achieved
by the user based on the category. Similarly, the objective score
field 606 displays a score achieved by the user for corresponding
objectives. The comment field 608 which display comment by an
expert/system for the user score sheet and one or more approaches
taken by the user 102 while solving the challenge. In one
embodiment, once the user 102 clicks on the view expert solution
field 610 redirected to expert solution page for corresponding
challenge. In one embodiment, the user may compare execution steps
of a user with execution steps of an expert while performing a
challenge to determine one or more deviation and to observe the
expert approach.
[0054] FIG. 7 illustrates a user interface view of an expert
solution sheet for the at least one challenge according to an
embodiment herein. The view 700 includes an alternatives field 702,
a comment field 704, and a steps field 706. The alternatives field
702 provides an alternative expert solution for a particular
challenge performed by a user. The comment field 704 provides one
or more comments as an expert solution for the challenge to the
user. The steps field 706 provides the one or more steps followed
by an expert for a particular challenge performed by the user 102.
For example, a challenge may include a table that includes
information e.g., sales, advertisement expenses, sales incentives)
about financial status of an industry. Upon selection of sales
which signifies an input and similarly the sales incentives signify
an output. In one embodiment, the user 102 may click on previous
step field 706 to view the previous steps performed by the expert
for a particular challenge and similarly the next step field is to
view next step performed by the expert for the particular
challenge. FIG. 8 illustrates a user interface view of a
consolidated rank sheet of the user 102 specific to one or more
challenges according to an embodiment herein. The view 800 includes
a consolidated rank sheet 802, and a cumulative field 804. The
consolidated rank sheet 802 displays the user 102/trainee who have
performed one or more challenges with corresponding score earned
and domain of learning. For example, one or more users/trainee
`John`, `Paul`, `Robert` who top three rankers for a challenge in
finance domain with corresponding score points earned. In one
embodiment, the cumulative field. 804 may be used to sort the rank
sheet according to the user based on cumulative score. Similarly,
the rank sheet may be sorted based on the challenge.
[0055] FIG. 9 illustrates a user interface view 900 of a user
profile sheet according to an embodiment herein. The view 900
includes a starred field 902. In one embodiment, the consolidated
courses sheet displays list of courses to the user with
corresponding schedule. In one embodiment, the user may add one or
more courses to his profile (e.g., add to favorites) when he/she
clicks on the starred field 902.
[0056] FIG. 10 is an interaction diagram illustrating a processor
implemented method for training and scoring one or more challenges
taken by the user 102 using the simulation based learning platform
106 according to an embodiment herein. The interaction diagram 1000
includes a series of operations carried out during various stages
of interaction between the challenge selection module 206, the hint
rendering module 208, the steps recording module 210, the steps
recording module 210, the scoring module 214 and the notification
module 216. In operation 1002, performs one or more user
actions/steps and gives results. For example, user action is `a
user clicks` on solving an at least one challenge from a plurality
of challenges. In operation 1004, the hint and instruction module
212 may renders a right hint to the user, when user prompts for
hint or when system deems it appropriate to share hint based on
where the user/trainee is in the at least one challenge. In
operation 1006, an outcome of hints used by the user is sent to the
scoring module 214 and evaluator which is used to arrive at final
score for the exercise/challenge. In operation 1008, the steps
recording module 210 records and stores the steps that user/trainee
or an expert have taken for completing a challenge. In operation
1010, interacts with a display module to display the steps taken by
the user dynamically and interacts with scoring system to compute
deviance of user from a reference path.
[0057] In operation 1012, the steps comparing module 212 compares
the one or more steps taken by the user with one or more steps
taken by one or more experts to solve the at least one challenge to
compute a deviance of the user from a reference path. In operation
1014, the steps comparing module 212 compute the deviance from one
of the optimal/recommended paths. In operation 1016, the scoring
module 214 scores the at least one challenge based on the deviance
of the user from, he reference path to obtain a score. In operation
1018, the notification module 216 provides and support gamification
elements (e.g., points, badges, level unlock, leadership boards e
the platform. In operation 1020, reports and progress cards at a
user or institution level are provided by the management
information module (MIS).
[0058] FIG. 11 illustrates an exploded view of the computing device
104 having a memory 1102 having a set of computer instructions, a
bus 1104, a display 1106, a speaker 1108, and a processor 1110
capable of processing a set of instructions o perform any one or
more of the methodologies herein, according to an embodiment
herein. In one embodiment, the receiver may be the computing device
104. The processor 1110 may also enable digital content to be
consumed in the form of video for output via one or more displays
1106 or audio for output via speaker and/or earphones 1108. The
processor 1110 may also carry out the methods described herein and
in accordance with the embodiments herein.
[0059] Digital content ay also be stored in the memory 1102 for
future processing or consumption. The memory 1102 may also store
program specific information and/or service information (PSI/SI),
including information about digital content (e.g., the detected
information bits) available in the future or stored from the past.
A user of the computing device 104 may view this stored information
on display 1106 and select an item of for viewing, listening, or
other uses via input, which may take the form of keypad, scroll, or
other input device(s) or combinations thereof. When digital content
is selected, the processor 1110 may pass information. The content
and PSI/SI may be passed among functions within the computing
device using the bus 1104.
[0060] The techniques provided by the embodiments herein may be
implemented on an integrated circuit chip (not shown). The chip
design is created in a graphical computer programming language, and
stored in a computer storage medium as a disk, tape, physical hard
drive, or virtual hard drive such as in a storage access network).
If the designer does not fabricate chips or the photolithographic
masks used to fabricate chips, the designer transmits the resulting
design by physical means (e.g., by providing a copy of the storage
medium storing the design) or electronically (e.g., through the
Internet) to such entities, directly or indirectly.
[0061] The stored design is then converted into the appropriate
format (e.g., GDSII) for the fabrication of photolithographic
masks, which typically include multiple copies of the chip design
in question that are to be formed on a wafer. The photolithographic
masks are utilized to define areas of the wafer (and/or the layers
thereon) to be etched or otherwise processed.
[0062] The resulting integrated circuit chips can be distributed by
the fabricator in raw wafer form (that is, as a single wafer that
has multiple unpackaged chips), as a bare die, or in a packaged
form. In the latter case the chip is mounted in a single chip
package (such as a plastic carrier, with leads that are affixed to
a motherboard or other higher level carrier) or in a multichip
package (such as a ceramic carrier that has either or both surface
interconnections or buried interconnections). In any case the chip
is then integrated with other chips, discrete circuit elements,
and/or other signal processing devices as part of either (a) an
intermediate product, such as a motherboard, or (b) an end product.
The end product can be any product that includes integrated circuit
chips, ranging from toys and other low-end applications to advanced
computer products having a display, a keyboard or other input
device, and a central processor.
[0063] FIG. 12 is a flow diagram illustrates a method for training
and scoring one or more challenges taken by a user using a
simulation based learning platform according to an embodiment
herein. In step 1202, a plurality of challenges to be taken by a
user is obtained from a database. In step 1204, at least one of
information associated with the one or more challenges is obtained.
In step 1206, at least one challenge from the plurality of
challenges is processed by selection with at least one action or
steps performed by the user. In step 1208, one or more hints to
solve the at least one challenge is rendered. In step 1210, one or
more steps taken by the user to solve the at least one challenge is
recorded. In step 1212, the one or more steps taken by the user is
compared with one or more steps taken by an expert to solve the at
least one challenge to compute a deviance of the user from a
reference path. In step 1214, the at least one challenge is scored
based on the deviance of the user from the reference path to obtain
a score. In step 1216, a result associated with the at least one
challenge is notified to the user based on the score. The at least
one of information associated with the plurality of challenges is
selected from a group includes (i) a description, (ii) an
objective, (iii) data sets that are created or provisioned, (iv)
rules of navigation, (v) key steps, and (vi) success criteria among
other related components.
[0064] The processor implemented method may further includes, one
or more solutions are provided in a format selected from a group
which includes, one or more audio, (ii) one or more video, (iii)
one or more text, or (iv) a combination thereof. The processor
implemented method may further includes, (i) tracking a progress
associated with the at least one challenge, displaying a progress
indicator for the at least one challenge taken by the user. The
progress indicator includes (i) a progress level of the user
associated with the at least one challenge, or (ii) a comparison of
a performance between (i) the user and the one or more experts,
(ii) the user and the one or more users, or (iii) combinations
thereof. The performance includes the one or more parameters.
[0065] The embodiments herein can take the form of, an entirely
hardware embodiment, an entirely software embodiment or an
embodiment including both hardware and software elements. The
embodiments that are implemented in software include but are not
limited to, firmware, resident software, microcode, etc.
Furthermore, the embodiments herein can take the form of a computer
program product accessible from a computer-usable or
computer-readable medium providing program code for use by or in
connection with a computer or any instruction execution system. For
the purposes of this description, a computer-usable or computer
readable medium can be any apparatus that can comprise, store,
communicate, propagate, or transport the program for use by or in
connection with the instruction execution system, apparatus, or
device.
[0066] The medium can be an electronic, magnetic, optical,
electromagnetic, infrared, or semiconductor system (or apparatus or
device) or a propagation medium. Examples of a computer-readable
medium include a semiconductor or solid state memory, magnetic
tape, a removable computer diskette, a random access memory (RAM),
a read-only memory (ROM), a rigid magnetic disk and an optical
disk. Current examples of optical disks include compact disk-read
only memory (CD-ROM), compact disk-read/write (CD-R/W) and DVD.
[0067] A data processing system suitable for storing and/or
executing program code will include at least one processor coupled
directly or indirectly to memory elements through a system bus. The
memory elements can include local memory employed during actual
execution of the program code, bulk storage, and cache memories
which provide temporary storage of at least some program code in
order to reduce the number of times code must be retrieved from
bulk storage during execution.
[0068] Input/output (I/O) devices (including but not ted to
keyboards, displays, pointing devices, remote controls, etc.) can
be coupled to the system either directly or through intervening I/O
controllers. Network adapters may also be coupled to the system to
enable the data processing system to become coupled to other data
processing systems or remote printers or storage devices through
intervening private or public networks. Modems, cable modem and
Ethernet cards are just a few of the currently available types of
network adapters.
[0069] A representative hardware environment for practicing the
embodiments herein is depicted in FIG. 13. This schematic drawing
illustrates a hardware configuration of an information
handling/computer system in accordance with the embodiments herein.
The system comprises at least one processor or central processing
unit (CPU) 10. The CPUs 10 are interconnected via system bus 12 to
various devices such as a random access memory (RAM) 14, read-only
memory (ROM) 16, and an input/output (I/O) adapter 18. The I/O
adapter 18 can connect to peripheral devices, such as disk units 11
and tape drives 13, or other program storage devices that are
readable by the system. The system can read the inventive
instructions on the program storage devices and follow these
instructions to execute the methodology of the embodiments
herein.
[0070] The system further includes a user interface adapter 19 that
connects a keyboard 15, mouse 17, speaker 24, microphone 22, and/or
other user interface devices such as a touch screen device not
shown) or a remote control to the bus 12 to gather user input.
Additionally, a communication adapter 20 connects the bus 12 to a
data processing network 25, and a display adapter 21 connects the
bus 12 to a display device 23 which may be embodied as an output
device such as a monitor, printer, or transmitter, for example.
[0071] The simulation based learning platform 106 provides a
conceptual learning, an immersive and interactive learning based on
simulation and real business cases where the learner will
experience in an analytics career. The user/trainee does riot
require prior knowledge on statistical code. The simulation based
learning platform 106 provides application of concepts on real time
data and on real time challenges. The simulation based learning
platform 106 simulates a real business scenario and allows a user
to explore the data as he/she deems fit and appropriate. The
simulation based learning platform 106 segments
analytics/statistical learning and allows a user to focus
application of business, analytic and statistical concepts separate
from a mechanics of tools and programming.
[0072] The simulation based learning platform 106 facilitates
learning by allowing the user to focus on choosing a right/optimal
step and an application/execution, which may interface with the
chosen package (e.g. `R` or `SAS` among others for
statistics/business analytics/optimization). There exists a
combination of objective and descriptive questions at critical
point to test concepts. The instruction and hints facilitate the
user and his/her progress on completion of the challenge. An
intelligent scoring which helps in determination of the user's
score and determine areas of improvement. Comparison of user steps
and actions against expert's recommended approach helps in
identifying areas of deviation.
[0073] The simulation based learning platform 106 enables a
collaboration, intelligent scoring and learning by experience. The
simulation based learning platform 106 enables the user/analyst to
quickly go up the learning curve, and reduce time spent on training
a user/analyst. The simulation based learning platform 106 provides
extensive and broad exposure to many practical and relevant real
life experiences through use cases and simulated journeys to solve
business challenges. The simulation based learning platform 106
which enables the user/analyst to define the problem thoroughly
before arriving at a solution. The simulation based learning
platform 106 quantifies business impact at every step and helps to
train the user/analyst, and script a story to implement for the
impact, for every analytical solution given.
[0074] The foregoing description of the specific embodiments will
so fully reveal the general nature of the embodiments herein that
others can, by applying current knowledge, readily modify and/or
adapt for various applications such specific embodiments without
departing from the generic concept, and, therefore, such
adaptations and modifications should and are intended to be
comprehended within the meaning and range of equivalents of the
disclosed embodiments. It is to be understood that the phraseology
or terminology employed herein is for the purpose of description
and not of limitation. Therefore, while the embodiments herein have
been described in terms of preferred embodiments, those skilled in
the art will recognize that the embodiments herein can be practiced
with modification within the spirit and scope of the appended
claims.
* * * * *