U.S. patent application number 15/993555 was filed with the patent office on 2019-03-21 for digital credential field data mapping.
The applicant listed for this patent is Pearson Education, Inc.. Invention is credited to Ronald Lancaster, Mark Mercury, Peter Pascale, Clarke Porter, Jarin Schmidt, Andrew Stockinger.
Application Number | 20190087832 15/993555 |
Document ID | / |
Family ID | 65719286 |
Filed Date | 2019-03-21 |
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United States Patent
Application |
20190087832 |
Kind Code |
A1 |
Mercury; Mark ; et
al. |
March 21, 2019 |
DIGITAL CREDENTIAL FIELD DATA MAPPING
Abstract
Techniques described herein relate to receiving multiple sources
of verified data associated with a digital credential receiver, and
mapping the digital credential receiver to one or more data field
data objects based on analyses of the verified data. In some
embodiments, a digital credential platform server may analyze the
various data sources associated with the digital credential
receiver, in order to determine and calculate correlation scores
between the digital credential receiver and various field data
objects. A combination of analyses and/or comparisons may be used
between the credential receiver data and the corresponding
retrieved from field data objects, such as the digital credential
objects earned by the credential receiver, the credential
receiver's verified evaluation records, and/or the career phase of
the digital credential receiver.
Inventors: |
Mercury; Mark; (Minneapolis,
MN) ; Schmidt; Jarin; (Eden Prairie, MN) ;
Porter; Clarke; (Minneapolis, MN) ; Pascale;
Peter; (Edina, MN) ; Stockinger; Andrew;
(Bloomington, MN) ; Lancaster; Ronald; (Saint
Paul, MN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Pearson Education, Inc. |
New York |
NY |
US |
|
|
Family ID: |
65719286 |
Appl. No.: |
15/993555 |
Filed: |
May 30, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
62559433 |
Sep 15, 2017 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 21/32 20130101;
G06K 9/00302 20130101; G06T 2207/10016 20130101; G06Q 50/2057
20130101; H04L 63/0861 20130101; G06Q 10/105 20130101; G06F 3/011
20130101; H04L 63/083 20130101; G06K 9/00288 20130101; G06Q 30/018
20130101; G06F 16/2379 20190101; G06Q 10/067 20130101; H04N 7/18
20130101; H04L 67/22 20130101; G06F 21/316 20130101; H04W 4/38
20180201; G06Q 10/063112 20130101; G06N 20/00 20190101; G06Q
10/06398 20130101; G06T 7/74 20170101; H04L 67/306 20130101; G06F
16/2365 20190101; G06Q 10/06393 20130101; G09B 7/00 20130101; G06F
40/186 20200101; H04L 63/107 20130101; G06F 30/20 20200101; H04L
63/0876 20130101; G06F 16/285 20190101; G06K 9/00335 20130101; G06T
2207/30201 20130101; H04L 67/38 20130101 |
International
Class: |
G06Q 30/00 20060101
G06Q030/00; G06F 17/30 20060101 G06F017/30 |
Claims
1. A digital credential platform server configured to map
credential receivers to field data objects, the digital credential
platform server comprising: a processing unit comprising one or
more processors; one or more network interfaces; and memory coupled
with and readable by the processing unit and storing therein a set
of instructions which, when executed by the processing unit, causes
the digital credential platform server to: receive a request to
match a first credential receiver to one or more field data
objects; retrieve data associated with the first credential
receiver, including data identifying one or more digital
credentials issued to the first credential receiver; retrieve and
analyze a plurality of field data objects stored in a data
structure; select a first subset of the plurality of field data
objects correlating to the first credential receiver, wherein the
first subset of field data objects is selected based on a
correlation analysis between the one or more digital credentials
issued to the first credential receiver and a plurality of
characteristics of the plurality of field data objects; for each
particular field data object of the selected first subset of field
data objects, determine a correlation metric between the particular
field data object and the first credential receiver; transmit data
identifying the correlation metric for each of the selected first
subset of field data objects, in response to the request.
2. The digital credential platform server of claim 1, wherein
performing the correlation analysis between the digital credentials
issued to the first credential receiver and the plurality of
characteristics of the field data objects comprises: determining a
set of capabilities of the credential receiver, based on the
digital credentials issued to the credential receiver; and
determining a matching set of field data objects having capability
characteristics matching the determined set of capabilities of the
credential receiver.
3. The digital credential platform server of claim 2, wherein
performing the correlation analysis between the digital credentials
issued to the first credential receiver and the plurality of
characteristics of the field data objects further comprises:
determining first location data based on the digital credentials
issued to the credential receiver; and determining matching
location data associated with each of the selected first subset of
field data objects.
4. The digital credential platform server of claim 2, wherein
performing the correlation analysis between the digital credentials
issued to the first credential receiver and the plurality of
characteristics of the field data objects further comprises:
determining an expected salary range based on the digital
credentials issued to the credential receiver; and determining
matching salary range data associated with each of the selected
first subset of field data objects.
5. The digital credential platform server of claim 2, wherein
performing the correlation analysis between the digital credentials
issued to the first credential receiver and the plurality of
characteristics of the field data objects further comprises:
determining a current career phase of the credential receiver,
based on the digital credentials issued to the credential receiver;
and determining matching career phase data associated with each of
the selected first subset of field data objects.
6. The digital credential platform server of claim 1, wherein the
request to match the first credential receiver to one or more field
data objects is initiated automatically in response to an issuance
of a new digital credential to the credential receiver, and wherein
the memory stores additional instructions which, when executed by
the processing unit, causes the digital credential platform server
to: determine an owner associated with each of the selected first
subset of field data objects; and transmit a notification
identifying the correlation metric for each of the selected first
subset of field data objects, to the determined owner of each
selected field data object.
7. The digital credential platform server of claim 1, wherein the
request to match the first credential receiver to one or more field
data objects is initiated automatically in response to the creation
of a new data field object, and wherein the memory stores
additional instructions which, when executed by the processing
unit, causes the digital credential platform server to: transmit a
notification identifying the correlation metric for each of the
selected first subset of field data objects, including the new data
field object, to the credential receiver.
8. The digital credential platform server of claim 1, wherein
transmitting the data identifying the correlation metric comprises,
for each selected field data object of the first subset of field
data objects: transmitting a first notification to the credential
receiver, wherein the first notification identifies the correlation
metric for the selected field data object but does not identify the
selected field data object; and transmitting a second notification
to an owner associated with the selected field data object, wherein
the second notification identifies the correlation metric for the
selected field data object but does not identify the credential
receiver.
9. A method of determining correlation metrics between field data
objects and credential receivers, the method comprising: receiving,
by a digital credential platform server, a request to match a first
credential receiver to one or more field data objects; retrieving
by the digital credential platform server, data associated with the
first credential receiver, including data identifying one or more
digital credentials issued to the first credential receiver;
retrieving and analyzing, by the digital credential platform
server, a plurality of field data objects stored in a data
structure; selecting, by the digital credential platform server, a
first subset of the plurality of field data objects correlating to
the first credential receiver, wherein the first subset of field
data objects is selected based on a correlation analysis between
the one or more digital credentials issued to the first credential
receiver and a plurality of characteristics of the plurality of
field data objects; for each particular field data object of the
selected first subset of field data objects, determining, by the
digital credential platform server, a correlation metric between
the particular field data object and the first credential receiver;
and transmitting, by the digital credential platform server, data
identifying the correlation metric for each of the selected first
subset of field data objects, in response to the request.
10. The method of claim 9, wherein performing the correlation
analysis between the digital credentials issued to the first
credential receiver and the plurality of characteristics of the
field data objects comprises: determining a set of capabilities of
the credential receiver, based on the digital credentials issued to
the credential receiver; and determining a matching set of field
data objects having capability characteristics matching the
determined set of capabilities of the credential receiver.
11. The method of claim 10, wherein performing the correlation
analysis between the digital credentials issued to the first
credential receiver and the plurality of characteristics of the
field data objects further comprises: determining first location
data based on the digital credentials issued to the credential
receiver; and determining matching location data associated with
each of the selected first subset of field data objects.
12. The method of claim 10, wherein performing the correlation
analysis between the digital credentials issued to the first
credential receiver and the plurality of characteristics of the
field data objects further comprises: determining an expected
salary range based on the digital credentials issued to the
credential receiver; and determining matching salary range data
associated with each of the selected first subset of field data
objects.
13. The method of claim 10, wherein performing the correlation
analysis between the digital credentials issued to the first
credential receiver and the plurality of characteristics of the
field data objects further comprises: determining a current career
phase of the credential receiver, based on the digital credentials
issued to the credential receiver; and determining matching career
phase data associated with each of the selected first subset of
field data objects.
14. The method of claim 9, wherein the request to match the first
credential receiver to one or more field data objects is initiated
automatically in response to an issuance of a new digital
credential to the credential receiver, and wherein the method
further comprises: determining an owner associated with each of the
selected first subset of field data objects; and transmitting a
notification identifying the correlation metric for each of the
selected first subset of field data objects, to the determined
owner of each selected field data object.
15. The method of claim 9, wherein the request to match the first
credential receiver to one or more field data objects is initiated
automatically in response to the creation of a new data field
object, and wherein the method further comprises: transmitting a
notification identifying the correlation metric for each of the
selected first subset of field data objects, including the new data
field object, to the credential receiver.
16. The method of claim 9, wherein transmitting the data
identifying the correlation metric comprises, for each selected
field data object of the first subset of field data objects:
transmitting a first notification to the credential receiver,
wherein the first notification identifies the correlation metric
for the selected field data object but does not identify the
selected field data object; and transmitting a second notification
to an owner associated with the selected field data object, wherein
the second notification identifies the correlation metric for the
selected field data object but does not identify the credential
receiver.
17. A non-transitory computer-readable medium, having instructions
stored therein, which when executed by a computing device cause the
computing device to perform a set of operations comprising:
receiving a request to match a first credential receiver to one or
more field data objects; retrieving data associated with the first
credential receiver, including data identifying one or more digital
credentials issued to the first credential receiver; retrieving and
analyzing a plurality of field data objects stored in a data
structure; selecting a first subset of the plurality of field data
objects correlating to the first credential receiver, wherein the
first subset of field data objects is selected based on a
correlation analysis between the one or more digital credentials
issued to the first credential receiver and a plurality of
characteristics of the plurality of field data objects; for each
particular field data object of the selected first subset of field
data objects, determining a correlation metric between the
particular field data object and the first credential receiver; and
transmitting data identifying the correlation metric for each of
the selected first subset of field data objects, in response to the
request.
18. The non-transitory computer-readable medium of claim 17,
wherein performing the correlation analysis between the digital
credentials issued to the first credential receiver and the
plurality of characteristics of the field data objects comprises:
determining a set of capabilities of the credential receiver, based
on the digital credentials issued to the credential receiver; and
determining a matching set of field data objects having capability
characteristics.
19. The non-transitory computer-readable medium of claim 17,
wherein the request to match the first credential receiver to one
or more field data objects is initiated automatically in response
to an issuance of a new digital credential to the credential
receiver, and wherein the instructions cause the computing device
to perform a further set of operations comprising: determining an
owner associated with each of the selected first subset of field
data objects; and transmitting a notification identifying the
correlation metric for each of the selected first subset of field
data objects, to the determined owner of each selected field data
object.
20. The non-transitory computer-readable medium of claim 17,
wherein the request to match the first credential receiver to one
or more field data objects is initiated automatically in response
to the creation of a new data field object, and wherein the
instructions cause the computing device to perform a further set of
operations comprising: transmitting a notification identifying the
correlation metric for each of the selected first subset of field
data objects, including the new data field object, to the
credential receiver.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a non-provisional of and claims priority
to U.S. Provisional Patent Application No. 62/559,433, entitled
"DIGITAL CREDENTIAL PLATFORM," filed Sep. 15, 2017, the entire
contents of which are incorporated by reference herein for all
purposes.
BACKGROUND
[0002] Changes in computing technologies have provided individuals
with additional options for obtaining and validating technical
skills and proficiencies. Rather than attending traditional
educational institutions and professional training courses, many
individuals may now obtain their technical skills and proficiencies
from alternative sources, such as structured or unstructured and
asynchronous eLearning programs using distance learning technology,
self-study research without any direct supervision, or various
alternative technical learning, training, and testing entities.
Although such advances in technologies and increasing globalization
trends provide many more options for individuals to obtain
technical skills and proficiencies, they also present challenges in
publishing, verifying and tracking the sets of technical skills and
proficiencies that these individuals have obtained. Many
individuals and institutions no longer rely on physical
certificates such as diplomas, transcripts, certification
statements, and physical licenses, to verify the authenticity of an
individual's proficiencies or qualifications. Instead, certain
institutions may issue digital credentials (or digital badges) to
qualifying individuals, and these digital credential earners may
use the digital credentials to certify the skills or qualifications
that the earner obtained vis-a-vis the institution.
BRIEF SUMMARY
[0003] Various techniques are described herein for receiving data
sources associated with digital credential receivers, and mapping
the digital credential receivers to one or more data field data
objects based on analyses of the verified data. In various
embodiments, a digital credential platform server may receive
requests from client devices identifying a digital credential
receiver. In response to such requests, the digital credential
platform server may retrieve data corresponding to a set of digital
credential objects received by the digital credential receiver. The
digital credential platform server also may retrieve one or more
verified evaluation records, for example, from a secure third-party
provider server, associated with the digital credential receiver.
Verified evaluation records may include, for instance, results of
personality or interest evaluations administered to the digital
credential receiver, results of automated evaluations of the
receiver's digital records of interactions, and the like, in order
to further assess compatibility of the digital credential receiver
with particular fields. Additionally, in some embodiments, the
digital credential platform server may retrieve and/or determine a
career phase associated with the digital credential receiver, which
may be relevant to the mapping analysis.
[0004] Additional techniques are described herein in which the
digital credential platform server may analyze the various data
sources associated with the digital credential receiver, in order
to determine and calculate correlation scores between the digital
credential receiver and various field data objects. In some
embodiments, the digital credential platform server may use a
combination of analyses and/or comparisons between the receiver
data and related data retrieved from a plurality of different field
data objects. For example, the digital credential objects (or
digital badges) earned by the receiver may be compared to the
corresponding capabilities, skills, certifications, etc.,
associated with different fields in a field data structure.
Additionally, the receiver's verified evaluation records may be
compared to the corresponding interest or personality data
associated with the different fields. Further, in some cases, the
current career phase of the digital credential receiver may be
compared to corresponding career phase data associated with the
different fields. Based on the various combination of analyses and
comparisons, the platform server may calculate correlation scores
for a plurality of different field data objects, and
designate/transmit a subset of the fields that correlate most
closely to the digital credential receiver.
[0005] Various additional techniques described herein relate to
both the retrieval of different types of credential receiver data
and/or field data from different data sources, and/or to the
analyses and correlation calculations between digital credential
receivers and field data objects. For example, in some embodiments,
the platform server may store and maintain expiration dates and/or
half-lives for various types of data associated with digital
credential receivers, such as the receiver's digital credentials,
the receiver's verified evaluation data, and the receiver's career
phase data. Expiration dates and/or half-lives may be used as a
multiplier to weight the correlation calculations of credential
receivers to field data objects. Additionally, in some embodiments,
reverse analyses and calculations may be performed, in which a
plurality of different digital credential receivers are selected
and scored based on their correlation to a particular field data
object representing an occupation or an individual job listing.
Additionally, various embodiments described herein may include
digital credentials issued to receivers based on the detection of
specific interests and/or personality traits within the users,
specific DNA traits and/or health-based traits, and/or for various
other types or combinations of traits that may be detected for
particular digital credential receivers, and these digital
credentials may further be used in the correlation analyses. Still
other aspects described herein may relate to a secure digital
certification platform and/or service, to provide digital
credential certification, verification, and security, in order to
address problems associated with anonymous and/or unverified
digital credentials and/or credential receivers.
BRIEF DESCRIPTION OF THE DRAWINGS
[0006] FIG. 1 is a block diagram showing illustrating an example of
a content distribution network.
[0007] FIG. 2 is a block diagram illustrating a computer server and
computing environment within a content distribution network.
[0008] FIG. 3 is a block diagram illustrating an embodiment of one
or more data store servers within a content distribution
network.
[0009] FIG. 4 is a block diagram illustrating an embodiment of one
or more content management servers within a content distribution
network.
[0010] FIG. 5 is a block diagram illustrating the physical and
logical components of a special-purpose computer device within a
content distribution network.
[0011] FIG. 6 is a block diagram illustrating an example computing
environment for generating, managing, and tracking digital
credential templates and digital credentials, according to one or
more embodiments of the disclosure.
[0012] FIG. 7 is an diagram illustrating an example computing
environment for executing and monitoring physical simulations
within a digital credential system, according to one or more
embodiments of the disclosure.
[0013] FIG. 8 is a flow diagram illustrating an example process of
executing and monitoring physical simulations for generation of
digital credentials, according to one or more embodiments of the
disclosure.
[0014] FIG. 9A is an diagram illustrating a computer terminal-based
system for sensor-based monitoring and generation of digital
credentials, according to one or more embodiments of the
disclosure.
[0015] FIG. 9B is an diagram illustrating a physical
environment-based system for sensor-based monitoring, and
generation of digital credentials, according to one or more
embodiments of the disclosure.
[0016] FIG. 10 is a flow diagram illustrating an example process of
generating and issuing digital credentials in a sensor-monitored
environment, according to one or more embodiments of the
disclosure.
[0017] FIG. 11 is an diagram illustrating an example computing
environment for analyzing sensor-based activity monitoring within a
digital credential system, according to one or more embodiments of
the disclosure.
[0018] FIG. 12 is a flow diagram illustrating an example process of
generating digital credentials and tracking the corresponding
activities in a sensor-monitored environment, according to one or
more embodiments of the disclosure.
[0019] FIG. 13 is a flow diagram illustrating an example process of
analyzing activities in a sensor-monitored environment to determine
digital credential expiration and/or recertification times,
according to one or more embodiments of the disclosure.
[0020] FIG. 14 is an diagram illustrating an example computing
environment for generating and analyzing digital credentials using
received sensor monitoring data, according to one or more
embodiments of the disclosure.
[0021] FIG. 15 is a flow diagram illustrating an example process of
generating and storing digital credentials with associated data
from sensor-monitored environments, according to one or more
embodiments of the disclosure.
[0022] FIGS. 16A-16B are flow diagrams illustrating example
processes of retrieving sensor data associated with issued digital
credentials, and generating additional and/or updated digital
credentials based on the retrieved sensor data, according to one or
more embodiments of the disclosure.
[0023] FIGS. 17A-17B are diagrams illustrating facial recognition
and analysis functionality performed during digital credential
generation and analyses processes within sensor-monitored
environments, according to one or more embodiments of the
disclosure.
[0024] FIG. 18 is a flow diagram illustrating an example process of
generating and storing digital credentials with associated user
feedback data from sensor-monitored environments, according to one
or more embodiments of the disclosure.
[0025] FIG. 19 is a block diagram illustrating an example system
for analyzing and mapping digital credential receivers to field
data objects, according to one or more embodiments of the
disclosure.
[0026] FIG. 20 is a flow diagram illustrating an example process of
generating notifications based on determined correlations between
digital credential receivers and field data objects, according to
one or more embodiments of the disclosure.
[0027] In the appended figures, similar components and/or features
may have the same reference label. Further, various components of
the same type may be distinguished by following the reference label
by a dash and a second label that distinguishes among the similar
components. If only the first reference label is used in the
specification, the description is applicable to any one of the
similar components having the same first reference label
irrespective of the second reference label.
DETAILED DESCRIPTION
[0028] The ensuing description provides illustrative embodiment(s)
only and is not intended to limit the scope, applicability or
configuration of the disclosure. Rather, the ensuing description of
the illustrative embodiment(s) will provide those skilled in the
art with an enabling description for implementing a preferred
exemplary embodiment. It is understood that various changes can be
made in the function and arrangement of elements without departing
from the spirit and scope as set forth in the appended claims.
[0029] Various techniques (e.g., systems, methods, computer-program
products tangibly embodied in a non-transitory machine-readable
storage medium, etc.) are described herein for receiving data
sources associated with digital credential receivers, and mapping
the digital credential receivers to one or more data field data
objects based on analyses of the verified data. In various
embodiments, a digital credential platform server may receive
requests from client devices identifying a digital credential
receiver. In response to such requests, the digital credential
platform server may retrieve data corresponding to a set of digital
credential objects received by the digital credential receiver. The
digital credential platform server also may retrieve one or more
verified evaluation records, for example, from a secure third-party
provider server, associated with the digital credential receiver.
Verified evaluation records may include, for instance, results of
personality or interest evaluations administered to the digital
credential receiver, results of automated evaluations of the
receiver's digital records of interactions, and the like, in order
to further assess compatibility of the digital credential receiver
with particular fields. Additionally, in some embodiments, the
digital credential platform server may retrieve and/or determine a
career phase associated with the digital credential receiver, which
may be relevant to the mapping analysis.
[0030] Additional techniques are described herein in which the
digital credential platform server may analyze the various data
sources associated with the digital credential receiver, in order
to determine and calculate correlation scores between the digital
credential receiver and various field data objects. In some
embodiments, the digital credential platform server may use a
combination of analyses and/or comparisons between the receiver
data and related data retrieved from a plurality of different field
data objects. For example, the digital credential objects (or
digital badges) earned by the receiver may be compared to the
corresponding capabilities, skills, certifications, etc.,
associated with different fields in a field data structure.
Additionally, the receiver's verified evaluation records may be
compared to the corresponding interest or personality data
associated with the different fields. Further, in some cases, the
current career phase of the digital credential receiver may be
compared to corresponding career phase data associated with the
different fields. Based on the various combination of analyses and
comparisons, the platform server may calculate correlation scores
for a plurality of different field data objects, and
designate/transmit a subset of the fields that correlate most
closely to the digital credential receiver.
[0031] Various additional techniques described herein relate to
both the retrieval of different types of credential receiver data
and/or field data from different data sources, and/or to the
analyses and correlation calculations between digital credential
receivers and field data objects. For example, in some embodiments,
the platform server may store and maintain expiration dates and/or
half-lives for various types of data associated with digital
credential receivers, such as the receiver's digital credentials,
the receiver's verified evaluation data, and the receiver's career
phase data. Expiration dates and/or half-lives may be used as a
multiplier to weight the correlation calculations of credential
receivers to field data objects. Additionally, in some embodiments,
reverse analyses and calculations may be performed, in which a
plurality of different digital credential receivers are selected
and scored based on their correlation to a particular field data
object representing an occupation or an individual job listing.
Additionally, various embodiments described herein may include
digital credentials issued to receivers based on the detection of
specific interests and/or personality traits within the users,
specific DNA traits and/or health-based traits, and/or for various
other types or combinations of traits that may be detected for
particular digital credential receivers, and these digital
credentials may further be used in the correlation analyses. Still
other aspects described herein may relate to a secure digital
certification platform and/or service, to provide digital
credential certification, verification, and security, in order to
address problems associated with anonymous and/or unverified
digital credentials and/or credential receivers.
[0032] With reference now to FIG. 1, a block diagram is shown
illustrating various components of a content distribution network
(CDN) 100 which implements and supports certain embodiments and
features described herein. Content distribution network 100 may
include one or more content management servers 102. As discussed
below in more detail, content management servers 102 may be any
desired type of server including, for example, a rack server, a
tower server, a miniature server, a blade server, a mini rack
server, a mobile server, an ultra-dense server, a super server, or
the like, and may include various hardware components, for example,
a motherboard, a processing units, memory systems, hard drives,
network interfaces, power supplies, etc. Content management server
102 may include one or more server farms, clusters, or any other
appropriate arrangement and/or combination or computer servers.
Content management server 102 may act according to stored
instructions located in a memory subsystem of the server 102, and
may run an operating system, including any commercially available
server operating system and/or any other operating systems
discussed herein.
[0033] The content distribution network 100 may include one or more
data store servers 104, such as database servers and file-based
storage systems. Data stores 104 may comprise stored data relevant
to the functions of the content distribution network 100.
Illustrative examples of data stores 104 that may be maintained in
certain embodiments of the content distribution network 100 are
described below in reference to FIG. 3. In some embodiments,
multiple data stores may reside on a single server 104, either
using the same storage components of server 104 or using different
physical storage components to assure data security and integrity
between data stores. In other embodiments, each data store may have
a separate dedicated data store server 104.
[0034] Content distribution network 100 also may include one or
more user devices 106 and/or supervisor devices 110. User devices
106 and supervisor devices 110 may display content received via the
content distribution network 100, and may support various types of
user interactions with the content. User devices 106 and supervisor
devices 110 may include mobile devices such as smartphones, tablet
computers, personal digital assistants, and wearable computing
devices. Such mobile devices may run a variety of mobile operating
systems, and may be enabled for Internet, e-mail, short message
service (SMS), Bluetooth.RTM., mobile radio-frequency
identification (M-RFID), and/or other communication protocols.
Other user devices 106 and supervisor devices 110 may be general
purpose personal computers or special-purpose computing devices
including, by way of example, personal computers, laptop computers,
workstation computers, projection devices, and interactive room
display systems. Additionally, user devices 106 and supervisor
devices 110 may be any other electronic devices, such as
thin-client computers, Internet-enabled gaming systems, business or
home appliances, and/or personal messaging devices, capable of
communicating over network(s) 120.
[0035] In different contexts of content distribution networks 100,
user devices 106 and supervisor devices 110 may correspond to
different types of specialized devices, for example, student
devices and teacher devices in an educational network, employee
devices and presentation devices in a company network, different
gaming devices in a gaming network, etc. In some embodiments, user
devices 106 and supervisor devices 110 may operate in the same
physical location 107, such as a classroom or conference room. In
such cases, the devices may contain components that support direct
communications with other nearby devices, such as a wireless
transceivers and wireless communications interfaces, Ethernet
sockets or other Local Area Network (LAN) interfaces, etc. In other
implementations, the user devices 106 and supervisor devices 110
need not be used at the same location 107, but may be used in
remote geographic locations in which each user device 106 and
supervisor device 110 may use security features and/or specialized
hardware (e.g., hardware-accelerated SSL and HTTPS, WS-Security,
firewalls, etc.) to communicate with the content management server
102 and/or other remotely located user devices 106. Additionally,
different user devices 106 and supervisor devices 110 may be
assigned different designated roles, such as presenter devices,
teacher devices, administrator devices, or the like, and in such
cases the different devices may be provided with additional
hardware and/or software components to provide content and support
user capabilities not available to the other devices.
[0036] The content distribution network 100 also may include a
privacy server 108 that maintains private user information at the
privacy server 108 while using applications or services hosted on
other servers. For example, the privacy server 108 may be used to
maintain private data of a user within one jurisdiction even though
the user is accessing an application hosted on a server (e.g., the
content management server 102) located outside the jurisdiction. In
such cases, the privacy server 108 may intercept communications
between a user device 106 or supervisor device 110 and other
devices that include private user information. The privacy server
108 may create a token or identifier that does not disclose the
private information and may use the token or identifier when
communicating with the other servers and systems, instead of using
the user's private information.
[0037] As illustrated in FIG. 1, the content management server 102
may be in communication with one or more additional servers, such
as a content server 112, a user data server 112, and/or an
administrator server 116. Each of these servers may include some or
all of the same physical and logical components as the content
management server(s) 102, and in some cases, the hardware and
software components of these servers 112-116 may be incorporated
into the content management server(s) 102, rather than being
implemented as separate computer servers.
[0038] Content server 112 may include hardware and software
components to generate, store, and maintain the content resources
for distribution to user devices 106 and other devices in the
network 100. For example, in content distribution networks 100 used
for professional training and educational purposes, content server
112 may include data stores of training materials, presentations,
interactive programs and simulations, course models, course
outlines, and various training interfaces that correspond to
different materials and/or different types of user devices 106. In
content distribution networks 100 used for media distribution,
interactive gaming, and the like, a content server 112 may include
media content files such as music, movies, television programming,
games, and advertisements.
[0039] User data server 114 may include hardware and software
components that store and process data for multiple users relating
to each user's activities and usage of the content distribution
network 100. For example, the content management server 102 may
record and track each user's system usage, including their user
device 106, content resources accessed, and interactions with other
user devices 106. This data may be stored and processed by the user
data server 114, to support user tracking and analysis features.
For instance, in the professional training and educational
contexts, the user data server 114 may store and analyze each
user's training materials viewed, presentations attended, courses
completed, interactions, evaluation results, and the like. The user
data server 114 may also include a repository for user-generated
material, such as evaluations and tests completed by users, and
documents and assignments prepared by users. In the context of
media distribution and interactive gaming the user data server 114
may store and process resource access data for multiple users
(e.g., content titles accessed, access times, data usage amounts,
gaming histories, user devices and device types, etc.).
[0040] Administrator server 116 may include hardware and software
components to initiate various administrative functions at the
content management server 102 and other components within the
content distribution network 100. For example, the administrator
server 116 may monitor device status and performance for the
various servers, data stores, and/or user devices 106 in the
content distribution network 100. When necessary, the administrator
server 116 may add or remove devices from the network 100, and
perform device maintenance such as providing software updates to
the devices in the network 100. Various administrative tools on the
administrator server 116 may allow authorized users to set user
access permissions to various content resources, monitor resource
usage by users and devices 106, and perform analyses and generate
reports on specific network users and/or devices (e.g., resource
usage tracking reports, training evaluations, etc.).
[0041] The content distribution network 100 may include one or more
communication networks 120. Although only a single network 120 is
identified in FIG. 1, the content distribution network 100 may
include any number of different communication networks between any
of the computer servers and devices shown in FIG. 1 and/or other
devices described herein. Communication networks 120 may enable
communication between the various computing devices, servers, and
other components of the content distribution network 100. As
discussed below, various implementations of content distribution
networks 100 may employ different types of networks 120, for
example, computer networks, telecommunications networks, wireless
networks, and/or any combination of these and/or other
networks.
[0042] With reference to FIG. 2, an illustrative distributed
computing environment 200 is shown including a computer server 202,
four client computing devices 206, and other components that may
implement certain embodiments and features described herein. In
some embodiments, the server 202 may correspond to the content
management server 102 discussed above in FIG. 1, and the client
computing devices 206 may correspond to the user devices 106.
However, the computing environment 200 illustrated in FIG. 2 may
correspond to any other combination of devices and servers
configured to implement a client-server model or other distributed
computing architecture.
[0043] Client devices 206 may be configured to receive and execute
client applications over one or more networks 220. Such client
applications may be web browser based applications and/or
standalone software applications, such as mobile device
applications. Server 202 may be communicatively coupled with the
client devices 206 via one or more communication networks 220.
Client devices 206 may receive client applications from server 202
or from other application providers (e.g., public or private
application stores). Server 202 may be configured to run one or
more server software applications or services, for example,
web-based or cloud-based services, to support content distribution
and interaction with client devices 206. Users operating client
devices 206 may in turn utilize one or more client applications
(e.g., virtual client applications) to interact with server 202 to
utilize the services provided by these components.
[0044] Various different subsystems and/or components 204 may be
implemented on server 202. Users operating the client devices 206
may initiate one or more client applications to use services
provided by these subsystems and components. The subsystems and
components within the server 202 and client devices 206 may be
implemented in hardware, firmware, software, or combinations
thereof. Various different system configurations are possible in
different distributed computing systems 200 and content
distribution networks 100. The embodiment shown in FIG. 2 is thus
one example of a distributed computing system and is not intended
to be limiting.
[0045] Although exemplary computing environment 200 is shown with
four client computing devices 206, any number of client computing
devices may be supported. Other devices, such as specialized sensor
devices, etc., may interact with client devices 206 and/or server
202.
[0046] As shown in FIG. 2, various security and integration
components 208 may be used to transmit, receive, and manage
communications between the server 202 and user devices 206 over one
or more communication networks 220. The security and integration
components 208 may include separate servers, such as web servers
and/or authentication servers, and/or specialized networking
components, such as firewalls, routers, gateways, load balancers,
and the like. In some cases, the security and integration
components 208 may correspond to a set of dedicated hardware and/or
software operating at the same physical location and under the
control of same entities as server 202. For example, components 208
may include one or more dedicated web servers and network hardware
in a datacenter or a cloud infrastructure. In other examples, the
security and integration components 208 may correspond to separate
hardware and software components which may be operated at a
separate physical location and/or by a separate entity.
[0047] Security and integration components 208 may implement
various security features for data transmission and storage, such
as authenticating users and restricting access to unknown or
unauthorized users. In various implementations, security and
integration components 208 may provide, for example, a file-based
integration scheme or a service-based integration scheme for
transmitting data between the various devices in the content
distribution network 100. Security and integration components 208
also may use secure data transmission protocols and/or encryption
for data transfers, for example, File Transfer Protocol (FTP),
Secure File Transfer Protocol (SFTP), and/or Pretty Good Privacy
(PGP) encryption.
[0048] In some embodiments, one or more web services may be
implemented within the security and integration components 208
and/or elsewhere within the content distribution network 100. Such
web services, including cross-domain and/or cross-platform web
services, may be developed for enterprise use in accordance with
various web service standards, such as RESTful web services (i.e.,
services based on the Representation State Transfer (REST)
architectural style and constraints), and/or web services designed
in accordance with the Web Service Interoperability (WS-I)
guidelines. Some web services may use the Secure Sockets Layer
(SSL) or Transport Layer Security (TLS) protocol to provide secure
connections between the server 202 and user devices 206. SSL or TLS
may use HTTP or HTTPS to provide authentication and
confidentiality. In other examples, web services may be implemented
using REST over HTTPS with the OAuth open standard for
authentication, or using the WS-Security standard which provides
for secure SOAP messages using XML, encryption. In other examples,
the security and integration components 208 may include specialized
hardware for providing secure web services. For example, security
and integration components 208 may include secure network
appliances having built-in features such as hardware-accelerated
SSL and HTTPS, WS-Security, and firewalls. Such specialized
hardware may be installed and configured in front of any web
servers, so that any external devices may communicate directly with
the specialized hardware.
[0049] Communication network(s) 220 may be any type of network
familiar to those skilled in the art that can support data
communications using any of a variety of commercially-available
protocols, including without limitation, TCP/IP (transmission
control protocol/Internet protocol), SNA (systems network
architecture), IPX (Internet packet exchange), Secure Sockets Layer
(SSL) or Transport Layer Security (TLS) protocols, Hyper Text
Transfer Protocol (HTTP) and Secure Hyper Text Transfer Protocol
(HTTPS), Bluetooth.RTM., Near Field Communication (NFC), and the
like. Merely by way of example, network(s) 220 may be local area
networks (LAN), such as one based on Ethernet, Token-Ring and/or
the like. Network(s) 220 also may be wide-area networks, such as
the Internet. Networks 220 may include telecommunication networks
such as a public switched telephone networks (PSTNs), or virtual
networks such as an intranet or an extranet. Infrared and wireless
networks (e.g., using the Institute of Electrical and Electronics
(IEFF) 802.11 protocol suite or other wireless protocols) also may
be included in networks 220.
[0050] Computing environment 200 also may include one or more data
stores 210 and/or back-end servers 212. In certain examples, the
data stores 210 may correspond to data store server(s) 104
discussed above in FIG. 1, and back-end servers 212 may correspond
to the various back-end servers 112-116. Data stores 210 and
servers 212 may reside in the same datacenter or may operate at a
remote location from server 202. In some cases, one or more data
stores 210 may reside on a non-transitory storage medium within the
server 202. Other data stores 210 and back-end servers 212 may be
remote from server 202 and configured to communicate with server
202 via one or more networks 220. In certain embodiments, data
stores 210 and back-end servers 212 may reside in a storage-area
network (SAN), or may use storage-as-a-service (STaaS)
architectural model.
[0051] With reference to FIG. 3, an illustrative set of data stores
and/or data store servers is shown, corresponding to the data store
servers 104 of the content distribution network 100 discussed above
in FIG. 1. One or more individual data stores 301-309 may reside in
storage on a single computer server 104 (or a single server farm or
cluster) under the control of a single entity, or may reside on
separate servers operated by different entities and/or at remote
locations. In some embodiments, data stores 301-309 may be accessed
by the content management server 102 and/or other devices and
servers within the network 100 (e.g., user devices 106, supervisor
devices 110, administrator servers 116, etc.). Access to one or
more of the data stores 301-309 may be limited or denied based on
the processes, user credentials, and/or devices attempting to
interact with the data store.
[0052] The paragraphs below describe examples of specific data
stores that may be implemented within some embodiments of a content
distribution network 100. It should be understood that the below
descriptions of data stores 301-309, including their functionality
and types of data stored therein, are illustrative and
non-limiting. Data stores server architecture, design, and the
execution of specific data stores 301-309 may depend on the
context, size, and functional requirements of a content
distribution network 100. For example, in content distribution
systems 100 used for professional training and educational
purposes, separate databases or file-based storage systems may be
implemented in data store server(s) 104 to store trainee and/or
student data, trainer and/or professor data, training module data
and content descriptions, training results, evaluation data, and
the like. In contrast, in content distribution systems 100 used for
media distribution from content providers to subscribers, separate
data stores may be implemented in data stores server(s) 104 to
store listings of available content titles and descriptions,
content title usage statistics, subscriber profiles, account data,
payment data, network usage statistics, etc.
[0053] A user profile data store 301 may include information
relating to the end users within the content distribution network
100. This information may include user characteristics such as the
user names, access credentials (e.g., login and passwords), user
preferences, and information relating to any previous user
interactions within the content distribution network 100 (e.g.,
requested content, posted content, content modules completed,
training scores or evaluations, other associated users, etc.).
[0054] An accounts data store 302 may generate and store account
data for different users in various roles within the content
distribution network 100. For example, accounts may be created in
an accounts data store 302 for individual end users, supervisors,
administrator users, and entities such as companies or educational
institutions. Account data may include account types, current
account status, account characteristics, and any parameters,
limits, restrictions associated with the accounts.
[0055] A content library data store 303 may include information
describing the individual content items (or content resources)
available via the content distribution network 100. In some
embodiments, the library data store 303 may include metadata,
properties, and other characteristics associated with the content
resources stored in the content server 112. Such data may identify
one or more aspects or content attributes of the associated content
resources, for example, subject matter, access level, or skill
level of the content resources, license attributes of the content
resources (e.g., any limitations and/or restrictions on the
licensable use and/or distribution of the content resource), price
attributes of the content resources (e.g., a price and/or price
structure for determining a payment amount for use or distribution
of the content resource), rating attributes for the content
resources (e.g., data indicating the evaluation or effectiveness of
the content resource), and the like. In some embodiments, the
library data store 303 may be configured to allow updating of
content metadata or properties, and to allow the addition and/or
removal of information relating to the content resources. For
example, content relationships may be implemented as graph
structures, which may be stored in the library data store 303 or in
an additional store for use by selection algorithms along with the
other metadata.
[0056] A pricing data store 304 may include pricing information
and/or pricing structures for determining payment amounts for
providing access to the content distribution network 100 and/or the
individual content resources within the network 100. In some cases,
pricing may be determined based on a user's access to the content
distribution network 100, for example, a time-based subscription
fee, or pricing based on network usage and. In other cases, pricing
may be tied to specific content resources. Certain content
resources may have associated pricing information, whereas other
pricing determinations may be based on the resources accessed, the
profiles and/or accounts of the user, and the desired level of
access (e.g., duration of access, network speed, etc.).
Additionally, the pricing data store 304 may include information
relating to compilation pricing for groups of content resources,
such as group prices and/or price structures for groupings of
resources.
[0057] A license data store 305 may include information relating to
licenses and/or licensing of the content resources within the
content distribution network 100. For example, the license data
store 305 may identify licenses and licensing terms for individual
content resources and/or compilations of content resources in the
content server 112, the rights holders for the content resources,
and/or common or large-scale right holder information such as
contact information for rights holders of content not included in
the content server 112.
[0058] A content access data store 306 may include access rights
and security information for the content distribution network 100
and specific content resources. For example, the content access
data store 306 may include login information (e.g., user
identifiers, logins, passwords, etc.) that can be verified during
user login attempts to the network 100. The content access data
store 306 also may be used to store assigned user roles and/or user
levels of access. For example, a user's access level may correspond
to the sets of content resources and/or the client or server
applications that the user is permitted to access. Certain users
may be permitted or denied access to certain applications and
resources based on their subscription level, training program,
course/grade level, etc. Certain users may have supervisory access
over one or more end users, allowing the supervisor to access all
or portions of the end user's content, activities, evaluations,
etc. Additionally, certain users may have administrative access
over some users and/or some applications in the content management
network 100, allowing such users to add and remove user accounts,
modify user access permissions, perform maintenance updates on
software and servers, etc.
[0059] A source data store 307 may include information relating to
the source of the content resources available via the content
distribution network. For example, a source data store 307 may
identify the authors and originating devices of content resources,
previous pieces of data and/or groups of data originating from the
same authors or originating devices, and the like.
[0060] An evaluation data store 308 may include information used to
direct the evaluation of users and content resources in the content
management network 100. In some embodiments, the evaluation data
store 308 may contain, for example, the analysis criteria and the
analysis guidelines for evaluating users (e.g., trainees/students,
gaming users, media content consumers, etc.) and/or for evaluating
the content resources in the network 100. The evaluation data store
308 also may include information relating to evaluation processing
tasks, for example, the identification of users and user devices
106 that have received certain content resources or accessed
certain applications, the status of evaluations or evaluation
histories for content resources, users, or applications, and the
like. Evaluation criteria may be stored in the evaluation data
store 308 including data and/or instructions in the form of one or
several electronic rubrics or scoring guides for use in the
evaluation of the content, users, or applications. The evaluation
data store 308 also may include past evaluations and/or evaluation
analyses for users, content, and applications, including relative
rankings, characterizations, explanations, and the like.
[0061] In addition to the illustrative data stores described above,
data store server(s) 104 (e.g., database servers, file-based
storage servers, etc.) may include one or more external data
aggregators 309. External data aggregators 309 may include
third-party data sources accessible to the content management
network 100, but not maintained by the content management network
100. External data aggregators 309 may include any electronic
information source relating to the users, content resources, or
applications of the content distribution network 100. For example,
external data aggregators 309 may be third-party data stores
containing demographic data, education related data, consumer sales
data, health related data, and the like. Illustrative external data
aggregators 309 may include, for example, social networking web
servers, public records data stores, learning management systems,
educational institution servers, business servers, consumer sales
data stores, medical record data stores, etc. Data retrieved from
various external data aggregators 309 may be used to verify and
update user account information, suggest user content, and perform
user and content evaluations.
[0062] With reference now to FIG. 4, a block diagram is shown
illustrating an embodiment of one or more content management
servers 102 within a content distribution network 100. As discussed
above, content management server(s) 102 may include various server
hardware and software components that manage the content resources
within the content distribution network 100 and provide interactive
and adaptive content to users on various user devices 106. For
example, content management server(s) 102 may provide instructions
to and receive information from the other devices within the
content distribution network 100, in order to manage and transmit
content resources, user data, and server or client applications
executing within the network 100.
[0063] A content management server 102 may include a content
customization system 402. The content customization system 402 may
be implemented using dedicated hardware within the content
distribution network 100 (e.g., a content customization server
402), or using designated hardware and software resources within a
shared content management server 102. In some embodiments, the
content customization system 402 may adjust the selection and
adaptive capabilities of content resources to match the needs and
desires of the users receiving the content. For example, the
content customization system 402 may query various data stores and
servers 104 to retrieve user information, such as user preferences
and characteristics (e.g., from a user profile data store 301),
user access restrictions to content recourses (e.g., from a content
access data store 306), previous user results and content
evaluations (e.g., from an evaluation data store 308), and the
like. Based on the retrieved information from data stores 104 and
other data sources, the content customization system 402 may modify
content resources for individual users.
[0064] A content management server 102 also may include a user
management system 404. The user management system 404 may be
implemented using dedicated hardware within the content
distribution network 100 (e.g., a user management server 404), or
using designated hardware and software resources within a shared
content management server 102. In some embodiments, the user
management system 404 may monitor the progress of users through
various types of content resources and groups, such as media
compilations, courses or curriculums in training or educational
contexts, interactive gaming environments, and the like. For
example, the user management system 404 may query one or more
databases and/or data store servers 104 to retrieve user data such
as associated content compilations or programs, content completion
status, user goals, results, and the like.
[0065] A content management server 102 also may include an
evaluation system 406. The evaluation system 406 may be implemented
using dedicated hardware within the content distribution network
100 (e.g., an evaluation server 406), or using designated hardware
and software resources within a shared content management server
102. The evaluation system 406 may be configured to receive and
analyze information from user devices 106. For example, various
ratings of content resources submitted by users may be compiled and
analyzed, and then stored in a data store (e.g., a content library
data store 303 and/or evaluation data store 308) associated with
the content. In some embodiments, the evaluation server 406 may
analyze the information to determine the effectiveness or
appropriateness of content resources with, for example, a subject
matter, an age group, a skill level, or the like. In some
embodiments, the evaluation system 406 may provide updates to the
content customization system 402 or the user management system 404,
with the attributes of one or more content resources or groups of
resources within the network 100. The evaluation system 406 also
may receive and analyze user evaluation data from user devices 106,
supervisor devices 110, and administrator servers 116, etc. For
instance, evaluation system 406 may receive, aggregate, and analyze
user evaluation data for different types of users (e.g., end users,
supervisors, administrators, etc.) in different contexts (e.g.,
media consumer ratings, trainee or student comprehension levels,
teacher effectiveness levels, gamer skill levels, etc.).
[0066] A content management server 102 also may include a content
delivery system 408. The content delivery system 408 may be
implemented using dedicated hardware within the content
distribution network 100 (e.g., a content delivery server 408), or
using designated hardware and software resources within a shared
content management server 102. The content delivery system 408 may
receive content resources from the content customization system 402
and/or from the user management system 404, and provide the
resources to user devices 106. The content delivery system 408 may
determine the appropriate presentation format for the content
resources based on the user characteristics and preferences, and/or
the device capabilities of user devices 106. If needed, the content
delivery system 408 may convert the content resources to the
appropriate presentation format and/or compress the content before
transmission. In some embodiments, the content delivery system 408
may also determine the appropriate transmission media and
communication protocols for transmission of the content
resources.
[0067] In some embodiments, the content delivery system 408 may
include specialized security and integration hardware 410, along
with corresponding software components to implement the appropriate
security features content transmission and storage, to provide the
supported network and client access models, and to support the
performance and scalability requirements of the network 100. The
security and integration layer 410 may include some or all of the
security and integration components 208 discussed above in FIG. 2,
and may control the transmission of content resources and other
data, as well as the receipt of requests and content interactions,
to and from the user devices 106, supervisor devices 110,
administrative servers 116, and other devices in the network
100.
[0068] With reference now to FIG. 5, a block diagram of an
illustrative computer system is shown. The system 500 may
correspond to any of the computing devices or servers of the
content distribution network 100 described above, or any other
computing devices described herein. In this example, computer
system 500 includes processing units 504 that communicate with a
number of peripheral subsystems via a bus subsystem 502. These
peripheral subsystems include, for example, a storage subsystem
510, an I/O subsystem 526, and a communications subsystem 532.
[0069] Bus subsystem 502 provides a mechanism for letting the
various components and subsystems of computer system 500
communicate with each other as intended. Although bus subsystem 502
is shown schematically as a single bus, alternative embodiments of
the bus subsystem may utilize multiple buses. Bus subsystem 502 may
be any of several types of bus structures including a memory bus or
memory controller, a peripheral bus, and a local bus using any of a
variety of bus architectures. Such architectures may include, for
example, an Industry Standard Architecture (ISA) bus, Micro Channel
Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics
Standards Association (VESA) local bus, and Peripheral Component
Interconnect (PCI) bus, which can be implemented as a Mezzanine bus
manufactured to the IEEE P1386.1 standard.
[0070] Processing unit 504, which may be implemented as one or more
integrated circuits (e.g., a conventional microprocessor or
microcontroller), controls the operation of computer system 500.
One or more processors, including single core and/or multicore
processors, may be included in processing unit 504. As shown in the
figure, processing unit 504 may be implemented as one or more
independent processing units 506 and/or 508 with single or
multicore processors and processor caches included in each
processing unit. In other embodiments, processing unit 504 may also
be implemented as a quad-core processing unit or larger multicore
designs (e.g., hexa-core processors, octo-core processors, ten-core
processors, or greater.
[0071] Processing unit 504 may execute a variety of software
processes embodied in program code, and may maintain multiple
concurrently executing programs or processes. At any given time,
some or all of the program code to be executed can be resident in
processor(s) 504 and/or in storage subsystem 510. In some
embodiments, computer system 500 may include one or more
specialized processors, such as digital signal processors (DSPs),
outboard processors, graphics processors, application-specific
processors, and/or the like.
[0072] I/O subsystem 526 may include device controllers 528 for one
or more user interface input devices and/or user interface output
devices 530. User interface input and output devices 530 may be
integral with the computer system 500 (e.g., integrated audio/video
systems, and/or touchscreen displays), or may be separate
peripheral devices which are attachable/detachable from the
computer system 500.
[0073] Input devices 530 may include a keyboard, pointing devices
such as a mouse or trackball, a touchpad or touch screen
incorporated into a display, a scroll wheel, a click wheel, a dial,
a button, a switch, a keypad, audio input devices with voice
command recognition systems, microphones, and other types of input
devices. Input devices 530 may also include three dimensional (3D)
mice, joysticks or pointing sticks, gamepads and graphic tablets,
and audio/visual devices such as speakers, digital cameras, digital
camcorders, portable media players, webcams, image scanners,
fingerprint scanners, barcode reader 3D scanners, 3D printers,
laser rangefinders, and eye gaze tracking devices. Additional input
devices 530 may include, for example, motion sensing and/or gesture
recognition devices that enable users to control and interact with
an input device through a natural user interface using gestures and
spoken commands, eye gesture recognition devices that detect eye
activity from users and transform the eye gestures as input into an
input device, voice recognition sensing devices that enable users
to interact with voice recognition systems through voice commands,
medical imaging input devices, MIDI keyboards, digital musical
instruments, and the like.
[0074] Output devices 530 may include one or more display
subsystems, indicator lights, or non-visual displays such as audio
output devices, etc. Display subsystems may include, for example,
cathode ray tube (CRT) displays, flat-panel devices, such as those
using a liquid crystal display (LCD) or plasma display,
light-emitting diode (LED) displays, projection devices, touch
screens, and the like. In general, use of the term "output device"
is intended to include all possible types of devices and mechanisms
for outputting information from computer system 500 to a user or
other computer. For example, output devices 530 may include,
without limitation, a variety of display devices that visually
convey text, graphics and audio/video information such as monitors,
printers, speakers, headphones, automotive navigation systems,
plotters, voice output devices, and modems.
[0075] Computer system 500 may comprise one or more storage
subsystems 510, comprising hardware and software components used
for storing data and program instructions, such as system memory
518 and computer-readable storage media 516. The system memory 518
and/or computer-readable storage media 516 may store program
instructions that are loadable and executable on processing units
504, as well as data generated during the execution of these
programs.
[0076] Depending on the configuration and type of computer system
500, system memory 318 may be stored in volatile memory (such as
random access memory (RAM) 512) and/or in non-volatile storage
drives 514 (such as read-only memory (ROM), flash memory, etc.) The
RAM 512 may contain data and/or program modules that are
immediately accessible to and/or presently being operated and
executed by processing units 504. In some implementations, system
memory 518 may include multiple different types of memory, such as
static random access memory (SRAM) or dynamic random access memory
(DRAM). In some implementations, a basic input/output system
(BIOS), containing the basic routines that help to transfer
information between elements within computer system 500, such as
during start-up, may typically be stored in the non-volatile
storage drives 514. By way of example, and not limitation, system
memory 518 may include application programs 520, such as client
applications, Web browsers, mid-tier applications, server
applications, etc., program data 522, and an operating system
524.
[0077] Storage subsystem 510 also may provide one or more tangible
computer-readable storage media 516 for storing the basic
programming and data constructs that provide the functionality of
some embodiments. Software (programs, code modules, instructions)
that when executed by a processor provide the functionality
described herein may be stored in storage subsystem 510. These
software modules or instructions may be executed by processing
units 504. Storage subsystem 510 may also provide a repository for
storing data used in accordance with the present invention
[0078] Storage subsystem 300 may also include a computer-readable
storage media reader that can further be connected to
computer-readable storage media 516. Together and, optionally, in
combination with system memory 518, computer-readable storage media
516 may comprehensively represent remote, local, fixed, and/or
removable storage devices plus storage media for temporarily and/or
more permanently containing, storing, transmitting, and retrieving
computer-readable information.
[0079] Computer-readable storage media 516 containing program code,
or portions of program code, may include any appropriate media
known or used in the art, including storage media and communication
media, such as but not limited to, volatile and non-volatile,
removable and non-removable media implemented in any method or
technology for storage and/or transmission of information. This can
include tangible computer-readable storage media such as RAM, ROM,
electronically erasable programmable ROM (EEPROM), flash memory or
other memory technology, CD-ROM, digital versatile disk (DVD), or
other optical storage, magnetic cassettes, magnetic tape, magnetic
disk storage or other magnetic storage devices, or other tangible
computer readable media. This can also include nontangible
computer-readable media, such as data signals, data transmissions,
or any other medium which can be used to transmit the desired
information and which can be accessed by computer system 500.
[0080] By way of example, computer-readable storage media 516 may
include a hard disk drive that reads from or writes to
non-removable, nonvolatile magnetic media, a magnetic disk drive
that reads from or writes to a removable, nonvolatile magnetic
disk, and an optical disk drive that reads from or writes to a
removable, nonvolatile optical disk such as a CD ROM, DVD, and
Blu-Ray.RTM. disk, or other optical media. Computer-readable
storage media 516 may include, but is not limited to, Zip.RTM.
drives, flash memory cards, universal serial bus (USB) flash
drives, secure digital (SD) cards, DVD disks, digital video tape,
and the like. Computer-readable storage media 516 may also include,
solid-state drives (SSD) based on non-volatile memory such as
flash-memory based SSDs, enterprise flash drives, solid state ROM,
and the like, SSDs based on volatile memory such as solid state
RAM, dynamic RAM, static RAM, DRAM-based SSDs, magnetoresistive RAM
(MRAM) SSDs, and hybrid SSDs that use a combination of DRAM and
flash memory based SSDs. The disk drives and their associated
computer-readable media may provide non-volatile storage of
computer-readable instructions, data structures, program modules,
and other data for computer system 500.
[0081] Communications subsystem 532 may provide a communication
interface from computer system 500 and external computing devices
via one or more communication networks, including local area
networks (LANs), wide area networks (WANs) (e.g., the Internet),
and various wireless telecommunications networks. As illustrated in
FIG. 5, the communications subsystem 532 may include, for example,
one or more network interface controllers (NICs) 534, such as
Ethernet cards, Asynchronous Transfer Mode NICs, Token Ring NICs,
and the like, as well as one or more wireless communications
interfaces 536, such as wireless network interface controllers
(WNICs), wireless network adapters, and the like. Additionally
and/or alternatively, the communications subsystem 532 may include
one or more modems (telephone, satellite, cable, ISDN), synchronous
or asynchronous digital subscriber line (DSL) units, FireWire.RTM.
interfaces, USB.RTM. interfaces, and the like. Communications
subsystem 536 also may include radio frequency (RF) transceiver
components for accessing wireless voice and/or data networks (e.g.,
using cellular telephone technology, advanced data network
technology, such as 3G, 4G or EDGE (enhanced data rates for global
evolution), WiFi (IEEE 802.11 family standards, or other mobile
communication technologies, or any combination thereof), global
positioning system (GPS) receiver components, and/or other
components.
[0082] The various physical components of the communications
subsystem 532 may be detachable components coupled to the computer
system 500 via a computer network, a FireWire.RTM. bus, or the
like, and/or may be physically integrated onto a motherboard of the
computer system 500. Communications subsystem 532 also may be
implemented in whole or in part by software.
[0083] In some embodiments, communications subsystem 532 may also
receive input communication in the form of structured and/or
unstructured data feeds, event streams, event updates, and the
like, on behalf of one or more users who may use or access computer
system 500. For example, communications subsystem 532 may be
configured to receive data feeds in real-time from users of social
networks and/or other communication services, web feeds such as
Rich Site Summary (RSS) feeds, and/or real-time updates from one or
more third party information sources (e.g., data aggregators 309).
Additionally, communications subsystem 532 may be configured to
receive data in the form of continuous data streams, which may
include event streams of real-time events and/or event updates
(e.g., sensor data applications, financial tickers, network
performance measuring tools, clickstream analysis tools, automobile
traffic monitoring, etc.). Communications subsystem 532 may output
such structured and/or unstructured data feeds, event streams,
event updates, and the like to one or more data stores 104 that may
be in communication with one or more streaming data source
computers coupled to computer system 500.
[0084] Due to the ever-changing nature of computers and networks,
the description of computer system 500 depicted in the figure is
intended only as a specific example. Many other configurations
having more or fewer components than the system depicted in the
figure are possible. For example, customized hardware might also be
used and/or particular elements might be implemented in hardware,
firmware, software, or a combination. Further, connection to other
computing devices, such as network input/output devices, may be
employed. Based on the disclosure and teachings provided herein, a
person of ordinary skill in the art will appreciate other ways
and/or methods to implement the various embodiments.
[0085] With reference now to FIG. 6, a block diagram is shown
illustrating an example of a digital credential management system
600 for generating, managing, and tracking digital credential
templates and digital credentials. As shown in this example, a
digital credential management system 600 may include a digital
credential platform server 610 configured to communicate with
various other digital credential systems 620-680. As discussed
below, the digital credential platform server 610 may receive and
store digital credential templates from various digital credential
template owner systems 620. Systems 620 may correspond to the
computer servers and/or devices of educational institutions or
professional training organizations, which may have the primary
responsibility for defining a digital credential template and
controlling the content and requirements for users to receive a
digital credential from the organization. The digital credential
management system 600 may include one or more digital credential
issuer systems 630. As discussed below, each issuer system 630 may
communicate with the platform server to request and receive access
to issue digital credentials based on specific digital credential
templates. The platform server 610 may process template access
requests from the credential issuer systems 630, permitting or
denying a specific system 630 to generate (or issue) a digital
credential based on a specific digital credential template.
[0086] As used herein, a digital credential template (or digital
badge template) may refer to an electronic document or data
structure storing a general (e.g., non-user specific) template or
description of a specific type of digital credential that may be
issued to an individual. Digital credential templates may include,
for example, a description of the skills, proficiencies, and/or
achievements that the digital credential represents. This
description may take the form of diploma data, certification data,
and/or license data, including the parent organization (i.e., the
digital credential template owner) responsible for creating and
defining the digital credential template. Examples of digital
credential templates may include templates for various technology
certifications, licensure exams, professional tests, training
course completion certificates, and the like. In contrast to a
digital credential template, a digital credential (or digital
badge) may refer to an instance of an electronic document or data
structure, generated for a specific individual (i.e., the
credential receiver), and based on a digital credential template.
Thus, a digital credential document or data structure may be based
on a corresponding digital credential template, but may be
customized and populated with user-specific information such as
individual identification data (e.g., name, email address, and
other user identifiers), credential issuance data (e.g., issue
date, geographic location of issuance, authorized issuer of the
credential, etc.), and links or embedded data that contain the
specific user's supporting documentation or evidence relating to
the credential.
[0087] As shown in this example, the system 600 also may include a
digital credential receiver system 640 and a digital credential
endorser system 650. The digital credential receiver system 640 may
be a computing device associated with a credential receiver (or
credential earner), for example, an individual user of an
electronic learning system, professional training system, online
certification course, etc. In some embodiments, credential
receivers may access the platform server 610 via systems 640 to
accept or reject newly issued digital credentials, review and
update their own set of previously earned digital credentials, as
well as to publish (or share) their digital credentials via
communication applications or publishing platforms such as social
media systems. Digital credential endorser system 650 may be a
computing system associated with an endorsing entity, such as an
educational institution, business, or technical organization that
has chosen to review and endorse a specific digital credential
template. The platform server 610 may receive and track the
endorsements received from systems 650, and may associate the
endorsements with the user-specific digital credentials issued
based on the endorsed templates.
[0088] Additionally, the digital credential management system 600
in this example includes a number of external client devices 660
and external digital credential publishers 670. External client
devices 660 may correspond to computing systems of third-party
users that may interact with the platform server 610 to initiate
various functionality or retrieve data relating to templates
and/digital credentials managed by the platform 610. For example, a
client device 660 may query the platform server 610 for data
metrics and/or analyses relating to a subset of digital credentials
stored in the digital credential data store 615. The third-party
systems 660 also may provide data to the platform server 610 that
may initiate updates to the templates and/digital credentials
stored in the data store 615. External digital credential
publishers 670 may correspond to third-party systems configured to
receive digital credential data from the platform 610 and publish
(or present) the digital credential data to users. Examples of
publishers 670 may include social media website and systems,
digital badge wallets, and/or other specialized servers or
applications configured to store and present views of digital
badges to users.
[0089] In various embodiments described herein, the generation and
management of digital credentials, as well as the tracking and
reporting of digital credential data, may be performed within CDNs
100, such as eLearning, professional training, and certification
systems 100. For example, within the context of an eLearning CDN
100, a content management server 102 or other CDN server (e.g.,
104, 112, 114, or 116) may create and store digital credential
templates to describe and define various proficiencies,
achievements, or certifications supported by the eLearning CDN 100.
Additionally or alternatively, the content management server 102 or
other servers of an eLearning CDN 100 may issue digital credentials
to users, based on its own digital certificate templates and/or
templates received from other systems or CDNs. Further, in some
implementations, an eLearning CDN 100 may be configured to include
a digital credential platform server 610 to store and manage
templates and digital credentials between separate systems within
the CDN 100. Thus, in various different implementations, the
content management server(s) 102 of a CDN 100 may incorporate one
or more digital certificate template owner system(s) 620, digital
certificate issuer system(s) 630, and/or digital certificate
platform server(s) 610. In such embodiments, the various components
and functionalities described herein for the platform server 610,
owner system 620, and/or issuer system 630 all may be implemented
within one or more content management servers 102 (and/or other
servers) of an eLearning or professional training CDN 100. In other
examples, a digital credential platform server 610 may be
implemented using one or more computer servers, and other
specialized hardware and software components, separately from any
other CDN components such as content servers 112, content
management servers 102, data store servers 104, and the like. In
these examples, the digital credential platform server 610 may be
configured to communicate directly with related systems 620-670, or
indirectly through content management servers 102 and/or other
components and communications networks of the CDN 100.
[0090] In order to perform these features and other functionality
described herein, each of the components and sub-components
discussed in the example digital credential management system 600
may correspond to a single computer server or a complex computing
system including a combination of computing devices, storage
devices, network components, etc. Each of these components and
their respective subcomponents may be implemented in hardware,
software, or a combination thereof. Certain systems 620-670 may
communicate directly with the platform server 610, while other
systems 620-670 may communicate with the platform server 610
indirectly via one or more intermediary network components (e.g.,
routers, gateways, firewalls, etc.) or other devices (e.g., content
management servers 102, content servers 112, etc.). Although the
different communication networks and physical network components
have not been shown in this example so as not to obscure the other
elements depicted in the figure, it should be understood that any
of the network hardware components and network architecture designs
may be implemented in various embodiments to support communication
between the systems, servers, and devices in the digital credential
management system 600. Additionally, different systems 620-670 may
use different networks and networks types to communicate with the
platform server 610, including one or more telecommunications
networks, cable networks, satellite networks, cellular networks and
other wireless networks, and computer-based IP networks, and the
like. Further, certain components within the digital credential
management system 600 may include special purpose hardware devices
and/or special purpose software, such as those included in I/O
subsystem 611 and memory 614 of the platform server 610, as well as
those within the memory of the other systems 620-670, and the
digital credential data store 615 maintained by the platform server
610, discussed below.
[0091] Although the various interactions between the platform
server 610 and other systems 620-670 may be described below in
terms of a client-server model, it should be understood that other
computing environments and various combinations of servers and
devices may be used to perform the functionality described herein
in other embodiments. For instance, although the requests/responses
to determine the authorized issuers 630 for specific digital
credential templates, the generation of digital credentials, and
the retrieval and presentation of digital credential tracking and
reporting data, may be performed by a centralized web-based
platform server 610 in collaboration with various client
applications at the other systems 620-670 (e.g., web browser
applications or standalone client software), in other cases these
techniques may be performed entirely by a specialized digital
credential platform server 610, or entirely by one or more digital
credential tools (e.g., software services) executing on any one of
the systems 620-670. In other examples, a client-server model may
be used as shown in system 600, but different functional components
and processing tasks may be allocated to the client-side or the
sever-side in different embodiments. Additionally, the digital
credential data store 615 may be implemented as separate servers or
storage systems in some cases, and may use independent hardware and
software service components. However, in other implementations,
some or all of the digital credential data store 615 may be
incorporated into the platform server 610 (as shown in this
example) and/or may be incorporated into various other systems
620-670.
[0092] In some embodiments, each of the systems 620-670 that
collaborate and communicate with the platform server 610 may be
implemented as client computing systems, such desktop or laptop
computers, smartphones, tablet computers, and other various types
of computing devices, each of which may include some or all of the
hardware, software, and networking components discussed above.
Specifically, any of client systems 620-670 may be implemented
using any computing device with sufficient processing components,
memory and software components, and I/O system components for
interacting with users and supporting the desired set of
communications with the platform server 610, as described herein.
Accordingly, client systems 620-670 may include the necessary
hardware and software components to establish the network
interfaces, security and authentication capabilities, and
capabilities for transmitting/receiving digital credential
templates and digital credentials, digital credential data
requests/responses to the platform server 610, etc. Each client
system 620-670 may include an I/O subsystem, network interface
controller, a processing unit, and memory configured to operate
client software applications. The digital credential platform
server 610 may be configured to receive and execute various
programmatic and graphical interfaces for generating, managing, and
tracking issued digital credentials, in collaboration with the
various client systems 620-670. Accordingly, each client system
620-670 may include an I/O subsystem 611 having hardware and
software components to support a specific set of output
capabilities (e.g., LCD display screen characteristics, screen
size, color display, video driver, speakers, audio driver, graphics
processor and drivers, etc.), and a specific set of input
capabilities (e.g., keyboard, mouse, touchscreen, voice control,
cameras, facial recognition, gesture recognition, etc.). Different
client systems 620-670 may support different input and output
capabilities within their I/O subsystems, and thus different types
of user interactions, and platform server 610 functionality may be
compatible or incompatible with certain client systems 620-670. For
example, certain types of digital credential generation and search
functionality may require specific types of processors, graphics
components, network components, or I/O components in order to be
optimally designed and constructed using a client system
620-670.
[0093] In some embodiments, the digital credential platform server
610 may generate and provide software interfaces (e.g., via a
web-based application, or using other programmatic or graphical
interface techniques) used by the various client systems 620-670 to
perform the various digital credential management functionality
described herein. In response to receiving inputs from a client
system 620-670 corresponding to digital credentials, templates,
credential search requests and criteria, etc., the platform server
610 may access the underlying digital credential data store 615
perform the various functionality described herein. In other to
perform the tasks described herein, platform server 610 may include
components such as network interface controllers 612, processing
units 613, and memory 614 configured to store server software,
handle authentication and security, and to store, analyze, and
manage the digital credentials, templates, and credential tracking
data stored within the digital credential data store 615. As shown
in this example, the digital credential data store 615 may be
implemented as separate dedicated data stores (e.g., databases,
file-based storage, etc.) used for storing digital credential
template objects, issued digital credentials, credential tracking
data, and authorized user/role data. The platform server 610 and
data store 615 may be implemented as separate software (and/or
storage) components within a single computer server 610 in some
examples, while in other examples may be implemented as separate
computer servers/systems having separate dedicated processing
units, storage devices, and/or network components.
[0094] Certain aspects described herein related to the testing and
certification processes used to verify the skills or qualifications
that a user (or earner) has obtained in order to be awarded with a
digital credential (or badge) or any other skill certification from
an institution or credentialing body. In some embodiments, physical
testing environments including "simulation laboratories" may use
implemented to allow users to perform physical tasks (including
mental and/or computer-based tasks) in a monitored environment.
Such physical testing environments may use virtual reality and/or
augmented reality in various cases. The simulation lab and/or the
user may be monitored by various sensors during testing or
certification processes, and the results may be analyzed to
determine (at least in part) whether or not the user should be
awarded a particular digital credential or certification. As
discussed below in more detail, simulation labs may be implemented
as testing environments for manual tasks, computer-based tasks,
scenario training, etc., and various monitoring of the simulation
lab environment during test may provide data metrics relating to
successful completion of tasks, efficiency of task completion, user
response times, user decision making behaviors, user biometrics and
risk factors, etc. Further, as discussed below, certain simulation
labs may provide the ability to change testing scenarios as well as
environmental conditions (lighting noise, temperature, etc.) during
testing.
[0095] Referring now to FIG. 7, an example is shown of a physical
testing environment that may be used for badge testing, skills
certification, and other behavior monitoring and digital credential
generation, in accordance with certain aspects described herein. In
this example, a basic testing environment 700 is shown to
illustrate certain features and concepts that may be included in
various embodiments. Depending on the particular digital
credential, activity, skill or ability to be verified, different
devices and components may be included in the simulation
environments 700. For example, simulation environments 700 for
standardized testing and completion of computer-based tasks may be
setup to simulate an office environment, for instance, with a
computer, keyboard, monitor, desk and chair, etc. Other testing
environments 700 designed for other badges and/or skills
certifications may be configured differently. For instance, testing
environments 700 may be configured as a driving simulator (e.g.,
having front and side display screens, an installed automobile seat
with steering wheel, pedals, vehicle controls and gauges, simulated
mirror displays, etc.), or a flight simulator (e.g., having front
and side display screens, up and down fields of vision, a pilot
seat with a center stick and/or other airplane controls and gauges,
etc.). Other testing environments 700 might not require or have any
display screens, for example testing environments 700 for CPR
certification may include one or more CPR manikins and other
accessories to test CPR scenarios. Additional testing environments
700 may be implemented for law enforcement use of force or
defensive tactics scenarios (with or with display screens, with or
without live firearms capabilities, etc.). Still other testing
environments 700 may be implemented for skills testing and
verification on machine assembly tasks, and/or on machine use
tasks. The machines in testing environments 700 in such scenarios
may range from simple to complex, to allow users to any testable
task on any machine, from bicycle assembly, to automobile
maintenance, to semiconductor design, to electrical work, to laser
fabrication, to welding. Other testing environments 700 may be
implemented for skills testing and verification in performance of
medical or dental procedures, and the like, and thus may resemble a
hospital operating room or dentist office with a full complement of
medical tools and devices necessary to perform the tasks to be
verified. Still other testing environments 700 may be configured to
test/verify skills with respect to sports or other physical
activities, and thus the testing environments 700 may comprise a
dance studio, gymnastics apparatus, golf driving range, or other
sports equipment. For each of these examples, and many others, it
should be understood that the different configuration of testing
environments 700 may require different sets of testing equipment,
as well as different monitoring and environmental control features.
Further, although many examples and implementations described
herein refer to human users as the subjects of testing and
simulation scenarios, in some cases the test subjects may include
mechanical devices (e.g., machines configured to assemble parts),
artificial intelligences and/or other software programs configured
to perform certain tasks, etc.
[0096] In addition to the testing equipment and apparatuses in the
physical testing environment 700, the environment may have cameras
705 and sensors configured to monitor the performance and behavior
of the user during the testing. As shown in this example, a number
of cameras 705 may be installed throughout the testing environment
700 to capture image/video data of the user from different angles
during the testing/skills verification process. In addition to
cameras, in various embodiments (depending on the type of test or
skill being evaluated), additional sensors may be deployed within
the testing environment 700, including microphones, light sensors,
heat sensors, vibration sensors, and any other sensor type,
depending on the type of testing/evaluation being performed. For
instance, for testing of computer-based tasks, additional sensors
such as mouse movement trackers, keystroke loggers, and user
eye-tracking software may be used. For machine usage tasks,
scenario training, and the like, movement sensors may be placed on
the user and/or on any objects with which the user may interact
during the testing scenario. Additionally, for any testing or
skills evaluation scenario, certain embodiments may include
biometric sensors and devices 710 configured to detect and track
the user's biometric data during the testing process. Such
biometric sensors and devices may measure the user's temperature,
heartrate, blood pressure, respiration, skin conductivity, body
movements, brainwave activities, etc.
[0097] In some embodiments, the physical testing environment 700
also may include various environmental controls that allow a test
administrator to control the physical environmental conditions
during a test or skills evaluation. Such environmental controls may
include lights 715 that allow the test administrator to control the
light levels, angles, and/or colors during a test. By way of
example, lighting control within the environment 700 may allow the
test administrator to evaluate the user's ability to perform a
driving maneuver or roadside maintenance task at night, etc.
Additional environmental controls may include may include
temperature controls, weather simulation (e.g., wind, rain, snow,
sunshine, fog, etc.), speakers to provide background noise or
distraction, olfactory control that provides scents/odors to
simulate the smells that be present during a comparable real-life
scenario, vibration control to simulate the activity, and so
on.
[0098] Referring now to FIG. 8, a flow diagram is shown
illustrating an example process of executing tests or simulations,
as well as monitoring and analyzing the results of the tests or
simulations. As described below, the steps in this process may be
performed using various components of a simulation lab and/or other
physical test (or simulation) environment 700, described above. For
example, each of steps 801-810 may be performed by a computer
server of a test administrator associated with a physical
simulation environment 700. In other examples, physical simulation
environments 700 might be configured to receive test content and
configuration parameters, to execute the tests and monitor the
execution, and then to transmit the test results and related
observation data to a separate server (e.g., a digital credential
platform server 610) for scoring and analysis.
[0099] In step 801, a computer server controlling the physical
testing environment 700 may receive input relating to the test or
skills evaluation scenario to be executed within the physical
testing environment 700. In step 802, the server may receive data
identifying the particular user designated to complete the test or
skills evaluation scenario.
[0100] In step 803, the server may retrieve the test or scenario to
be loaded/executed within the physical testing environment 700. As
noted above, the test or scenario may include interactive user
software (e.g., driving or flight simulator programs, law
enforcement scenarios, etc.) and/or may include testing software or
other software programs loaded onto a desktop, laptop, or tablet
computer. For instance, the test or scenario may require the user
to work with computer-aided design software, spreadsheet software,
database development software, etc. In other cases, the test or
scenario may include audio and/or video files to be played via
speakers and/or display screens within the physical testing
environment 700, such as instructional videos or audio/visual test
questions.
[0101] The test or scenario retrieved in step 803 also may be
retrieved based on the identity of the particular user who will be
completing the test or skills evaluation scenario. In some
embodiments, the server of the physical testing environment 700 may
be configured to select the appropriate test, scenario, and/or
simulation (e.g., a particular software scenario, skill level,
etc.) based on the user's current set of badges or digital
credentials, the user's skill level, and/or the user's performance
history on previous tests or scenarios within the testing
environment 700. Additionally, in some cases, the server may vary
scenarios/test questions so that a particular user does not receive
the same test questions, scenarios, or other testing content that
they have already completed (or completed within a particular
recent time window).
[0102] In step 804, the server may determine and apply a set of
environmental conditions within the physical testing environment
700 for the execution of the test or scenario. As noted above, the
physical testing environment 700 in some embodiments may be capable
of setting various environment conditions such as lighting (e.g.,
to simulate different day or night, and/or different real-world
working environments), temperature and weather conditions (e.g., to
simulate outdoor scenarios, different seasons and locations), noise
(e.g., to provide background noise, traffic noise, distractions,
etc.) and other various environment conditions. The server may
select and apply environmental conditions as part of the test or
scenario selected in step 803, or as a separate determination which
is performed based on random chance or selected by a test
administrator, etc. For instance, for certain types of badges and
other certifications, separate day and night testing of certain
tasks may be required. In other cases, the environmental conditions
may be selected randomly and changed for each testing session. In
still other cases, user may select and/or save their preferred
environmental conditions for different types of testing. Further,
in some embodiments, the physical testing environment 700 may track
and analyze the user's various testing or scenario performance
metrics (e.g., accuracy, efficiency, safety, compliance,
biometrics, etc.) under different environmental conditions, in
order to determine the optimal environmental conditions for the
particular user. In such cases, user's may receive different badges
or certifications (or may have different badge assigned
characteristics or endorsements) based on their test or scenario
performance in different environmental conditions.
[0103] In step 805, the computer server(s) associated with the
physical testing environment 700 may execute the test or simulation
scenario, during which the user's performance and any/all user
reactions or responses may be monitored. As noted above, even for
certain tests that are entirely manual in nature, the physical
testing environment 700 may use cameras and any other sensors to
monitor the user's actions. Such monitoring may include various
aspects of the user's performance, such as answers to test
questions selected via a testing computer terminal, or the user's
interactions with physical objects (and/or other people) within the
physical testing environment 700. The user's answers and actions
may be recorded by cameras and computer input devices, and
additional user data may be collected using various other sensors
such as microphones, biometric sensors, etc.
[0104] In step 806, the results for the test and/or simulation
scenario completed by the user may be analyzed. In some
embodiments, the such analyses may be performed based not only on
the user's responses to particular test questions or scenarios.
Additionally or alternatively, the analysis in step 806 may include
an evaluation of the user's other reactions or responses, such as
speed and confidence of action (e.g., as determined by user
comments, speed of response, facial expression analysis, body
movement analysis, biometric data, etc.), efficiency, safety,
decision making, and user biometrics. One or more of these separate
analyses may be performed in steps 807-810, and each may be
performed independently of the others, or may be combined into a
single analysis. For instance, in some cases the goal of the
simulation might be only to measure the user's biometric data, and
the user's actual responses to the questions/scenarios may be
irrelevant and need not be evaluated in step 807. In other tests or
simulation scenarios, the opposite analysis may be applied, where
only the accuracy of the user's responses or behaviors are measured
and analyzed in step 807, and the user's biometric data is
irrelevant and thus the analysis in step 810 is not performed. As
another example, in a certain simulation of driving, machine
operation, use of force training, etc., the only relevant analysis
to be performed may be a safety/decision making analysis in step
809, while the efficiency analysis in step 808 need not be
performed. In other similar tests/situations, the server may apply
both a safety/decision making analysis in step 809 and an
efficiency analysis in step 808 (e.g., to confirm that a driving
maneuver or route was completed both safely and efficiently, to
confirm that a suspect was subdued safely and quickly, to assure
that a manufacturing assembly task was performed safely and
efficiently, etc.).
[0105] For example, in certain embodiments and implementations of
the concepts discussed above in reference to FIGS. 8-9, various
techniques (e.g., systems, methods, computer-program products
tangibly embodied in a non-transitory machine-readable storage
medium, etc.) may include evaluating a physical simulation by a
digital credential generator system (e.g., 630 and/or 610). Such
techniques may include monitoring, by a digital credential
generator system, a physical simulation area using a plurality of
sensors, during a physical simulation. During the monitoring the
digital credential generator system may detect, using the plurality
of sensors, various physical actions performed by a user during the
physical simulation. The digital credential generator system may
analyze data corresponding to the plurality of physical actions
performed by the user during the physical simulation, and determine
that the user corresponds to a particular credential receiver. The
digital credential generator system then may determine whether the
first credential receiver is eligible to receive a digital
credential, by comparing the data corresponding to the analysis of
the physical actions performed by the user during the physical
simulation, to one or more digital credential requirements.
Finally, the digital credential generator system may generate a
first digital credential associated with the first credential
receiver and with the digital credential requirements, in response
to determining that the first credential receiver is eligible to
receive the first digital credential.
[0106] In some embodiments, outputting a physical simulation may
include outputting audio and/or video simulation components within
the physical simulation area, manipulating physical objects (e.g.,
motorized objects) during a live-action simulation within the
physical simulation area, and/or outputting virtual reality
simulations via a virtual reality headset. Additionally, certain
embodiments may include generating physical simulation environments
within a physical simulation area, including, for example,
simulating ambient light conditions within the physical simulation
area, outputting one or more background noise conditions within the
physical simulation area, monitoring and controlling the physical
temperature using a heating and cooling system installed at the
physical simulation area, outputting smells to the physical
simulation area using a smell output device, and/or outputting
vibratory effect within the physical simulation area, using a
vibration system.
[0107] As noted above, the monitoring of a test/simulation may
include monitoring physical actions/activities performed by the
user using video recording devices and/or motions. Additionally or
alternatively, the monitoring may be of computer-based tasks, using
additional software-based sensors such as mouse movement trackers,
keystroke loggers, and user eye-tracking software, etc.
[0108] In accordance with certain aspects described herein, the
processes used for testing/evaluating a user and determining that a
user is eligible for a particular digital credential (or badge)
need not include a specific test, designated evaluation, or scored
scenario training. Rather, the testing and badging determinations
may be performed automatically during the user's normal course of
on-the-job performance of tasks. In such embodiments, the testing
and credentialing of users may be based on observation of workers
during their normal work activities. Cameras and other sensors may
be installed and used to detect the completion of tasks and/or
certain competencies of the users, and the data from these sensors
may be evaluated to automatically determine when the user is
eligible for a digital credential. Thus, on the job testing and
badging may be performed entirely transparently to the worker
performance of their job duties, and need not require any delay or
distraction from job performance, or any designated time or
location needed to perform formal testing.
[0109] In order to perform automatic and on-the-job testing and
credentialing of workers or other users (e.g., students, athletes,
etc.), the "work" environment of the user may be monitored with
cameras and/or sensors capable of tracking the user's activities
and performance. As discussed above with respect to the
implementation of physical testing environments (e.g., 700),
different types of digital credentials relate to different
activities that may be performed in a variety of different work
environments. Referring briefly to FIG. 9A, an example work
environment 900a is shown for a user completing computer-based
tasks. In this example, the work environment 900a may include a
basic workstation, server, modem, printer, monitor, keyboard, etc.,
as well as desk and chair to allow the user to complete normal
computer-based work activities. In this example, the user may be
data entry specialist, computer programmer or design engineer, call
center customer support operator, or may be performing any other
computer-based job. In such examples, sensors 905 and 910 may
include cameras, network monitoring devices, keystroke loggers,
mouse movement monitors, biometric devices and sensors, etc. Such
software tools may operate as background processes on a computer
terminal being monitored. Additional monitoring devices may be
built into specific software programs with which the user is
interacting, and may be able to determine the correctness, quality,
and efficiency of the user's interaction with the particular
software. For example, if a user is interacting with a spreadsheet
software application or computer-aided design application to
perform a work task, then monitoring features within the software
application may be used to determine how quickly the user performed
the task, how many attempts it took the user, how correct/accurate
was the finished product, etc. In other examples, the monitoring of
the user's interaction with a particular software program need not
involve any monitoring features within the software itself, but
instead may include monitoring at the operating system or hardware
layers, or monitoring that is entirely external to the workstation.
For example, external cameras 905 and other sensors may capture and
analyze the user's interactions with the software application, and
thus need not affect the operation of the software at all.
[0110] Another example work environment is shown in FIG. 9B. In
this example work environment 900b, the entire layout of workplace
floor is shown and monitored by a series of cameras 905 and/or
other sensors. The monitoring in this example may apply to works
who do not perform only computer-based tasks, but whose work
requires them to interact with physical objects within their
workspace, and/or to move around the work environment 900b to other
workspaces. For instance, maintenance works, office mail delivery
works, construction workers, electricians, plumbers, machine
assembly or manufacturing works, etc., may be monitored with such
systems. When monitoring a larger area for the performance of
non-computer-based work tasks, in addition to cameras 905, the work
environment 900b may include motion sensors, microphones and noise
sensors, as wells as movement sensors and/or tracking devices that
may be placed on specific physical objects within the environment.
By way of example, work environment 900b may correspond to a shop
floor, mechanic's garage, or manufacturing assembly plant, and the
cameras 905 and other sensors may be used to confirm that workers
are complying with safety requirements and/or health codes with
respect with their work with machinery or hazardous materials, etc.
As another example, work environment 900b may be an office
environment, and the cameras 905 and other sensors may be used to
confirm that individual workers are working efficiently, in their
assigned areas, etc., and that workers without assigned areas
(e.g., cleaning, mail delivery, maintenance workers, etc.) are
working efficiently and not skipping any portion of the floor
900b.
[0111] Referring now to FIG. 10, a flow diagram is shown
illustrating an example process of automatically monitoring work
activities and issuing digital credentials via "on-the-job"
testing. As described below, the steps in this process may be
performed by monitoring and credentialing computing devices
operating within various types of work environments 900, such as
those described above. For example, each of steps 1001-1006 may be
performed by a computer server operating automatically and
unassisted (or at the direction of an administrator) within a work
environment 900. In other examples, work environments 900 might be
configured only to monitor work activities and performance, and
then to transmit the results and related observation data regarding
various worker to a separate server (e.g., a digital credential
platform server 610) for scoring, analysis, and the issuance of
digital credentials.
[0112] In step 1001, a computer server controlling the on-the-job
badging system may activate the cameras, sensors, monitoring
software, etc., within the workstation and/or work environment. As
discussed above, this activation may include specific monitoring
software to detect computer-based tasks, and/or location monitoring
devices such as cameras, sensors, biometrics, etc., depending on
the type of workers and work environments 900 being monitored. In
some cases, an on-the-job testing and credentialing system may be
implemented as an "always on" system, in which the
workstation/workplace monitoring is constantly recording and
analyzing worker activities. Thus, step 1001 may be optional in
such embodiments. However, in other cases, workstation/workplace
monitoring might only be activated at certain times and not others,
for example, only during normal work hours, only on certain
specific work days designated for work evaluation, etc. In some
embodiments, a system administrator and/or individual workers may
activate or de-activate the workstation/workplace monitoring
systems within their work environment at any time. Thus, such
systems need not be an invasion of privacy for any worker that does
not choose for their work to be monitored and evaluated, but
workers may choose to turn the monitoring systems on in order to be
eligible for evaluation and earning of additional work related
digital credentials and credentials.
[0113] In step 1002, the workstation/workplace monitoring systems
may capture the user's work-related activities and behaviors,
including performing various computer-based tasks and
non-computer-based tasks as discussed above. In step 1003, the
user's working data as collected by the workstation/workplace
monitoring systems and sensors may be analyzed by the server, in
order to determine in step 1004 whether or not the user is eligible
for one or more digital credentials or other credentials (e.g.,
professional certifications, etc.) based on their on-the job work
activities. Certain digital credentials or credentials may be made
available to users in response to detecting that the user has
successful completed one or more specialized work tasks, thus
demonstrating that the user has obtained the particular skill
associated with the digital credential. In some cases, the server
and/or the monitoring systems and sensors may also be configured to
detect a certain level of efficiency by the user in performing the
tasks, and/or may require that the user perform a certain task N
number of times before the user is eligible for the digital
credential or credential.
[0114] In step 1004, if the system determines that the user is
eligible for one or more particular digital credentials (1004:Yes),
then in step 1005 the system may either issue the digital
credential directly (e.g., if the workplace server is permitted to
be digital credential issuer), and/or may initiate a communication
session with a badging platform 610 and/or digital credential
issuer 630 to request that a new digital credential is issued for
the worker. In such examples, the workplace server may provide the
information identifying the worker (e.g., name, employee ID,
digital credential system profile ID, etc.) to a digital credential
platform 610 or issuer 630, along with verification that the worker
has completed the requirements to earn a particular digital
credential. In some embodiments, the servers operating at the
workplace may be configured to capture evidence (e.g., video
evidence, screen captures, facial/identity verification, etc.) and
transmit the evidence to the digital credential-issuing authority,
before the digital credential may be issued.
[0115] In step 1006, the worker may be notified that they have
received a digital credential based on their normal on-the-job
activities. In some embodiments, the worker may indicate interest
in obtaining one or more particular digital credentials, and the
workstation/workplace monitoring system may be configured to
evaluate the worker with respect to the particular digital
credentials or credentials that the worker has expressed interest
in. However, in other examples, it may be possible for a worker to
receive an issued digital digital credential without expressing any
interest in the digital credential (or even being aware of such a
digital credential), but solely based on the determination that the
worker has achieved the level of skills mastery required for the
digital credential/credential, based on the automated monitoring of
the worker within the workplace. In certain cases, a user may be
informed that they are eligible for receiving a digital credential
prior to the issuance of the digital credential in step 1005, and
the user may be allowed to accept or reject the digital credential.
Additionally, in some cases, the user may receive status reports
(e.g., daily, weekly, etc.) identifying which digital credentials
the user is being monitored for, and the user's progress with
respect to earning those digital credentials. This data may include
indications to the worker that he/she may earn a particular digital
credential after performing a task another N times, or performing
the task N amount faster, or performing the task without making any
errors or backtracking, etc.
[0116] For example, in certain embodiments and implementations of
the concepts discussed above in reference to FIGS. 10-11, various
techniques (e.g., systems, methods, computer-program products
tangibly embodied in a non-transitory machine-readable storage
medium, etc.) may include generating digital credentials for
particular credential receivers, based on monitoring of a physical
environment using a plurality of sensors. A digital credential
issuer (or generator) 630 and/or 610 may detect or receiver sensor
data from a number of sensors corresponding to the user actions
performed by a user within the physical environment. The digital
credential generator may determine the operations that were/were
not performed within the physical environment, based on the user
actions detected. The digital credential issuer then may retrieve
data from a credential receiver data store associated with the
user/credential receiver, and determine one or more digital
credential templates, based on the retrieved data associated with
the first credential receiver. For each of the digital credential
templates, the digital credential issuer/generator may retrieve
criteria associated with the digital credential template, compare
the operations performed by the user within the physical
environment to the criteria associated with the digital credential
template, and then determine whether or not a credential receiver
is eligible to receive a digital credential based on the digital
credential template. If the first credential receiver is eligible
to receive a digital credential based on the digital credential
template, the digital credential generator may generate a digital
credential based on the digital credential template and user data
associated with the first credential receiver.
[0117] In such cases, the generated (or issued digital credential)
may be embedded with additional data such as the
evaluation/simulation time, location, or the sensor system/physical
environment within which the evaluation/simulation was performed.
Additionally, in some cases, facial recognition data and/or
biometric data may be collected from the user (credential
receiver), and may be used to validate or authenticate the digital
credential by verifying the user's identity. As in the above
examples, the monitoring may be done using physical movement
tracking sensors such as video recorders and/or motion detectors,
or may use software-based sensors such as network monitoring
devices, keystroke loggers, mouse movement monitors, touch screen
monitors. Such software-based tools may operate as background
processes on a computer terminal being monitored, and/or may be
built into specific software programs with which the user is
interacting.
[0118] Additional aspects related to the automated tracking of user
or worker activities, after the user/worker has been issued a badge
(or digital credential), in order to determine how often the
user/worker is "using" their digital credential. Depending on type
of digital credential or credential, post-credentialing monitoring
of the user may involve analysis of user's physical work product
(e.g., documents produced, parts/items created, etc.), or may be
involve observations of the user (e.g., via a workstation/workplace
monitoring system). In order to evaluate how often a user is using
a particular digital credential, a data store of digital
credentials may be linked to particular skills, work-related, or
activities. The user/worker may then be tracked to determine the
number of such tasks performed, and/or the quality, efficiency,
and/or competence of the user's performing those tasks, in order to
determine to what extend the user/worker is "using" the digital
credential.
[0119] Referring now to FIG. 11, an example computing environment
1100 is shown, including a digital credential platform server 1110,
one or more workstation/workplace monitoring systems 1120, and a
credential-to-activity mapping data store 1130. In some examples,
the digital credential platform server 1110 may be a badging server
similar or identical to the server 610 discussed above. Thus,
server 1110 may be configured as a digital credential repository
and credentialing system, acting as a clearinghouse for digital
credential owners, issuers, earners, endorsers, etc. Server 1110
may include a digital credential (or digital credential) data store
configured to store badging information such as the details of the
particular digital credentials earned by particular users. As noted
above, such details may include the date on which a digital
credential was issued to a user, and for certain digital
credentials, an expiration date associated with the digital
credential.
[0120] In this example, system 1100 also includes a
credential-to-activity mapping data store 1120, which may be
implemented as a separate external data store and/or may be
integrated into the digital credential data store of server 1100.
The credential-to-activity mapping data store 1130 may include
mappings of one or more tasks or activities associated with each
digital credential type that a user may potentially earn. For
example, a digital credential relating to automotive maintenance
for a particular make of car may have associated activities and
tasks that include particular maintenance tasks (e.g., tune-ups,
part replacements, etc.) for different model cars having the make.
As another example, an operating system administrator-related
digital credential may list, within data store 1130, various system
administrator tasks and that a user may perform on the particular
operating system. In some cases, the activities or tasks associated
with a particular digital credential may correspond to the same set
of activities or tasks that a user is required to perform to earn
the particular digital credential, and as discussed below, these
activities or tasks may serve as a metric to evaluate how much the
user is "using" the digital credential.
[0121] One or more workstation and/or workplace monitoring systems
1120 may provide user monitoring data to the server 1110, to allow
the sever 1110 to analyze the user's activities and determine to
what extent the user is using the activities and abilities
associated with their digital credentials. In some embodiments, the
workstation and/or workplace monitoring systems 1120 may be similar
or identical to any of the workstation/workplace monitoring systems
and sensors discussed above. For example, workplace monitoring
systems 1120 may collect records detailing the user's physical work
product (e.g., documents produced, modified or accessed by the
user, inventory or work order records indicating tasks performed by
the user, etc.). Additionally, workplace monitoring systems 1120
may include observation systems (e.g., workplace monitoring
systems) including cameras and other sensors to track the user's
activities and determine which specific tasks have been performed
by the user.
[0122] In some embodiments, the monitoring and tracking of
post-credentialing activities by the user may be used to analyze
and provide digital credential or credential feedback data to
various entities. For example, referring now to FIG. 12, a flow
diagram is shown illustrating an example process that may be used
to determine whether a user has or has not used the activities
associated with a particular digital credential that they have
obtained, and then to aggregate and report that digital credential
usage data to the relevant parties. In step 1201, a particular
digital credential is issued to a user based on the user's
successful completion of the badging requirements. As in the
various examples discussed above, the digital credential may be
associated with a computer-based activity, non-computer-based
activity, or any other set of digital credential requirements
determined by a digital credential owner or issuer. Additionally,
the digital credential issuance in step 1201 may be the result of
formal testing and/or certification processes, or may be based on
on-the-job or other observational data collected for the user.
[0123] In step 1202, the digital credential server 1110 and/or
monitoring systems 1120 may monitor and track the activities of the
credentialed user, including, for example, the workplace tasks
performed by the user based on analyses of the various monitoring
systems/sensor data installed at the user's workstation and/or
workplace environment. As described above, determining what
activities and tasks the credentialed user has performed, and when,
may be performed using a variety of techniques. In some cases,
determining what work-related tasks a user has performed, and what
other activities they have been engaged in, may be done by analyses
of written and electronic documents associated with the user or
workplace. For instance, documents such as maintenance requests,
work orders, customer tickets, purchase receipts, and the like may
be analyzed to determine what activities or tasks the user has
completed and when. For instance, a maintenance record listing the
user as the assigned technician may be used in determination that
the user has performed the specified task/activity at the time
listed on the record. In other examples, the user's electronic mail
and other electronic documents may be searched and analyzed (e.g.,
using a keyword analysis and/or trained artificial intelligence) to
determine what tasks the user has performed and/or what activities
the user has demonstrated during the relevant time periods. In some
embodiments, there may be particular advantages in implementing a
post-credentialing usage analysis and/or digital credential
valuation process for certain digital credentials/tasks that are
more discrete and detectable, for instance, a number of
transmissions changed after earning a vehicle transmission
certification, a number of particular medical procedures done
following a digital credential credential for the procedure, a
number of IT tickets resolved successfully following receiving an
advanced IT computer services and computer repair digital
credential, etc. In contrast, for other tasks and activities for
which a user may receive a digital credential, such as leadership,
communication skills, advanced C software programming, jujitsu
skill levels, and the like, it may be more difficult to quantify if
when, and how often a user is using the particular skill or task
associated with the digital credential.
[0124] In step 1203, a set of tasks and/or activities associated
with the digital credentials obtained by the specific user may be
retrieved using the credential-activity mapping data store 1130,
and in step 1204 the retrieved tasks and/or activities may be
compared to the tasks and activities that have been performed by
the user subsequent to the digital credentials being earned (as
determined in step 1202). As an example, the comparison in step
1204 may determine that in the six month since the user was issued
a professional certification to perform a particular technical
task, the user has performed that task on a weekly basis.
Alternatively, for a different digital credential issued to the
user directed to expertise in a particular software program, the
comparison in step 1204 may determine that the user has used that
software program only once since receiving the digital credential
two years ago. In this case, the system may conclude that the
professional certification issued six months ago to the user has
been of greater usefulness than the software digital credential
issued two years ago (allowing for the possibility of career
changes, prestige-driven digital credentials rather than functional
digital credentials, etc.).
[0125] In step 1205, data from the comparison of step 1204, i.e.,
data indicating the post-credentialing usage by the user of the
digital credential-associated activities or tasks, may be
aggregated and analyzed, and then transmitted to one or more of the
relevant system components. In various embodiments, any of several
different components and roles associated with the credentialing
platform 1110 may request and receive this information for their
associated digital credentials and/or associated users. For
instance, digital credential owners and/or digital credential
issuers may request and receive from the platform server 1110 data
regarding the post-issuance usage of the digital credentials they
own or have issued. In other cases, digital credential endorsers
may request and receive from the platform server 1110 data
regarding the post-issuance usage of the digital credentials they
have endorsed. Digital credential earners, the users themselves
also may request reports from the platform server 1110 quantifying
the post-credentialing usage (which may be expressed in terms of
time, value, and/or dollar amounts) associated with their
previously earned digital credentials. Employers and other
organizations also may request such reports for their employees or
organization members, in order to determine which digital
credentials have been the most used and most useful to the
organization.
[0126] Referring now to FIG. 13, another flow diagram is shown
illustrating an related process involving determining whether a
user has or has not used the activities associated with a
particular digital credential that they have obtained, and then
adjusting an expiration or re-certification date associated with
the digital credential based on the user's usage of the digital
credential skills. The steps in this example may be similar or
identical to the corresponding steps in FIG. 12, and in some
embodiments, the analyses and transmission of the
post-credentialing usage described in step 1205 may be performed in
conjunction with the setting of an expiration or re-certification
date for the digital credential as discussed below.
[0127] Steps 1301-1304 may correspond to steps 1201-1204 in some
cases, and may be performed using similar or identical techniques
to those discussed above. For example, in step 1301 a platform
server 1110 and/or digital credential issuer may issue a digital
credential associated with one or more activities or tasks to a
particular user, recording the digital credential issuance data
within the digital credential data store. In step 1302, the
post-issuance activities of the particular user may be monitored,
including monitoring of the user's work-related activities and
tasks performed/completed, in order to determine the particular
tasks and activities with which the user has been engaged following
issuance of the digital credential. In step 1303, the skills,
activities, and tasks associated with the user's digital
credential(s) are retrieved, and in step 1304 are compared to the
post-issuance user tasks and activities determined for the user in
step 1302. Finally, in step 1305, based on the comparison in step
1304, the platform server 1110 may determine that an expiration
date and/or recertification date associated with the user's digital
credential should be adjusted based on the user's post-issuance
activities. As an example, if the system determines in step 1305
that a user who received a digital credential corresponding to a
forklift operator's license or commercial truck driving license
three years ago, but has infrequently (or not at all) driven a
forklift or a commercial truck since receiving their digital
credential, then the system may determine that the user's license
should expire at the earliest possible time (e.g., the expiration
time as of when the digital credential was first issued). In
contrast, if the system determines in step 1305 that the same user
has frequently and consistently driven a forklift or a commercial
truck ever since receiving their digital credential, and also that
the user has a high-safety rating and/or high safety compliance
scores, then the system may determine that the user's license may
be extended. In such cases, the platform server 1110 may determine
a new extended expiration or recertification time for the digital
credential, update the user's digital credential record within the
digital credential data store, and transmit notifications to the
affected entities (e.g., the user, employer, digital credential
issuer, digital credential owner, etc.) providing the new
expiration date. In other examples, rather than changing the
expiration date or recertification date of a digital credential (or
eliminating the expiration altogether), the platform server 1110
may in other examples determine a new recertification course or
procedure for the user, such as simple refresher course to allow
the user to recertify quick than the longer complete
recertification course used by other users with less
post-credentialing digital credential usage.
[0128] Additional aspects described herein relate to capturing and
using "evidence" data in connection with user testing and
credentialing systems, on-the-job evaluation and badging systems,
and/or post-credential monitoring systems. For example, within any
automated badging/certification/verification system, evidence of
the user's performance may be extracted and saved, for example, in
a digital credential server along with an associated issued digital
credential, or as part of a separate user portfolio of evidence.
Evidence data may include, for example, audio and video of the user
during a live simulation, or during a virtual reality or augment
reality simulation, audio and keystroke data from the user during
the testing processing, the user's reaction time and/or
decision-making data during a split-second simulated scenario or
relevant real-life event (e.g., a workplace accident, etc.), and/or
any other sensor or biometric data collected during testing,
credentialing, and/or monitoring. As discussed below, evidence data
associated with a user may be saved with the user's digital
credential and/or into a separate portfolio of evidence, which may
be available to the user for review, and also may be provided upon
request to potential employers for review during a review or hiring
process. Such evidence data also may be applied to updated digital
credential credentialing requirements, so that in some cases a user
may simply resubmit their evidence portfolio instead of being
required to recertify their digital credential when the test or
credentialing standards are updated.
[0129] Referring now to FIG. 14, an example computing environment
is shown including a digital credential platform server 1410 in
communication with a plurality of testing, credentialing, and/or
monitoring systems 1421-1423, and one or more external client
devices 1460. In some examples, the digital credential platform
server 1410 may be a digital credentialing server similar or
identical to the server 610 discussed above. Thus, server 1410 may
be configured as a digital credential repository and credentialing
system, acting as a clearinghouse for digital credential owners,
issuers, earners, endorsers, etc. Server 1410 may include a digital
credential (or digital credential) data store configured to store
digital credential information such as the details of the
particular digital credentials earned by particular users. As noted
above, such details may identify the digital credential issuer
and/or other testing/credential authorities responsible for
administering testing or simulation scenarios as part of the
digital credentialing process, and/or for pre-digital credential or
post-digital credential monitoring of workstations/workplaces to
detect and analyze user tasks performance and user
skills/abilities
[0130] In this example, the platform server 1410 may receive data
from three testing/credentialing systems 1421-1423. Similar to the
above examples, the simulation lab system 1421 may correspond to a
simulation lab or other physical testing environment, an on-the-job
credentialing systems 1422 may include workstation/workplace
monitoring systems and sensors to record and analyze the user's
on-the-job performance, and may issue digital credentials in some
cases without the need for any separate formal testing procedure;
and post-credential monitoring systems 1423 may be configured to
monitor users following the issuance of a digital credential,
including tracking task performance data, skills usage, and the
like, and comparing the data to the skills/tasks associated with
the user's digital credentials.
[0131] In some embodiments, one or more systems 1421-1423 which
perform user testing, credentialing, and/or monitoring, such as
those systems discussed above, may capture and transmit "evidence
data" of the user during a test, simulation, or during an
on-the-job monitoring process. Evidence data may include, for
example, video and/or audio of the user during a test, simulation
(e.g., live, VR, or AR), collected by the sensors of a physical
testing environment 700. Additional evidence data may include user
reaction time data, decision-making data, facial expression and
body language data, keystroke and mouse movement data, and/or user
biometric data. The evidence data may correspond to a time period
just before, during, and just after a test, simulation, or a task
or activity performed during on-the-job monitoring.
[0132] As shown in this example, the various evidence data
collected by systems 1421-1423 may be transmitted to the platform
server 1410 and stored in an evidence portfolio data store. The
evidence data collected by the testing, credentialing and/or user
monitoring systems may be associated with a particular user (or
users) and with a particular digital credential (or digital
credentials) that the user is in the process of earning or using
(e.g., for post-credentialing monitoring). Thus, the evidence data
may provide documented proof that the user actually completed the
digital credential requirements, along with additional contextual
evidence showing how the user performed during the testing,
simulation, or monitoring.
[0133] Referring now to FIG. 15, a flow diagram is shown
illustrating an example process by which a testing system,
simulator, credentialing systems, workstation/workplace monitoring
system, and the like, may collect and preserve evidence data
related to a user and a digital credential. In step 1501, a
testing, credentialing, and/or monitoring system such as those
described above may execute a test, simulation, or user monitoring
process for a particular user in connection with a digital
credential that the user is seeking or has already obtained. The
particular types of tests may include, for example, live
simulations and/or virtual or augmented reality simulations
executed within a physical testing environment 700. In other
examples, the testing in step 1501 may correspond to an on-the-job
credentialing system that monitors and evaluates a user's workplace
tasks and activities, or to a post-credentialing user monitoring
system configured to determine whether the user is using their
previously issued digital credentials. In step 1502, during any of
these testing, simulation, or monitoring processes, the system
1421-1423 may capture evidence data relating to the user. As noted
above, evidence data may include audio or video of the user, user
reaction time data, decision-making data, facial expression data,
body language data, the user's keystrokes and mouse movement data,
particular software interaction data, and/or the user's biometric
data. In step 1503, the evidence data may be encapsulated and
transmitted to the platform server 1410 for storage within the
user's evidence portfolio, and in step 1504 the platform server
1410 may store the evidence data files with data records associated
with the user and the particular digital credential(s) to which the
evidence applies. In other embodiments, certain systems 1421-1423
may retain and store user evidence data locally, rather than the
evidence data being stored in a central repository. Additionally,
when the evidence data is transmitted, it may be compressed and
edited as needed, and/or encrypted in order to assure data security
and user privacy.
[0134] In some cases, the platform server 1410 may determine a
subset of the user activities matching digital credential
requirements associated with the digital credential, wherein other
user activities might bare no relevance to the requirements of the
digital credential. In such cases, the platform server may store
only the corresponding subset of the evidence/sensor data for the
user activities matching digital credential requirements, and might
not store other evidence/sensor data corresponding to irrelevant
user activities upon which digital credentials do not depend.
[0135] Referring now to FIGS. 16A and 16B, two additional flow
diagrams are shown illustrating example processes by which evidence
data may be retrieved and/or accessed from a platform server 1410
or other data repository. As noted above, individual evidence data
files stored by the platform server 1410 may be associated with a
particular user and/or with a particular digital credential or
credential earned (or in process of earning) by the user. Thus, in
some embodiments, evidence data may be stored and made available to
certain authorized entities. For instance, in step 1601 of FIG.
16A, the platform server 1410 may receive a request for some or all
of the user's evidence portfolio. In step 1602, the platform server
1410 may perform authorization/authentication on the request to
determine (1) whether the requestor is authorized to access the
user's evidence data, and/or (2) whether the requested evidence is
current and valid. One or both of these determinations may require
explicit authorization from the user himself or herself, in order
to (1) prevent any unwanted parties from accessing the user's
evidence data, and (2) to prevent any old and obsolete from being
accessed, even by authorized parties. Thus, step 1602 may include
verifying the requestor's identity or role and comparing to an
access control list or other permissions data associated with the
evidence. In some cases, step 1602 may include a real-time request
sent by the platform server 1410 to a client device associated with
the user, to allow the user the option to allow or reject the
request. Additionally, the request in step 1601 may specify one or
more particular users and/or one or more particular digital
credentials for which the associated evidence is to be retrieved,
and thus authorization in step 1602 may be granted or denied for
evidence relating to each possible combination of users and digital
credentials. In step 1603, assuming that the requestor has been
granted access to the requested evidence data, the corresponding
evidence data files may be retrieved and forwarded to the
requestor.
[0136] In some examples, the request in step 1601 may be from the
user himself/herself, who wants to review and study the evidence
from his/her previous tests, simulations, and monitoring data. In
other examples, the request in step 1601 may be from a current or
potential employer, who has been authorized by the user to retrieve
and view the user's evidence data associated with all work-relevant
digital credentials, as part of a hiring process or review process.
The user's evidence data may verify to the employer or potential
employer that the user actually completed the digital credential
requirements, and also may allow the employer or potential employer
to observe the user's behaviors, responses, reactions first-hand,
thus allowing them to evaluate the user's reaction time,
efficiency, mental state, decision-making, etc., and other
difficult to quantify characteristics. In still other examples, the
user may authorize a digital credential issuer or digital
credential owner to view the user's evidence files related to the
digital credentials issued and owned by those entities. Finally,
users may make some or all of their evidence data publicly
available (e.g., on a file-by-file basis) and/or may actively post
their evidence data as a multimedia file or data records within a
digital credential profile page of the user that is maintained and
published by the platform server 1410.
[0137] In some embodiments, in addition to (or instead of)
providing evidence data in response to requests, the platform
server 1410 may provide the functionality to receive updated tests,
digital credential requirements, credentialing data, etc., and to
apply a user's previously stored evidence to the new testing or
credentialing requirements. For instance, in step 1604 of FIG. 16B,
the platform server 1410 may receive a request to apply previously
stored evidence data within a user's portfolio to an updated
testing/credentialing process. For example, testing or
credentialing authorities (e.g., a digital credential owners or
issuers, employers, etc.) may periodically update digital
credentialing requirements in order to improve the quality of the
digital credential testing, to comply with new best industry
practices, to make a digital credential more restrictive by
increasing the required scores or efficiency, etc. Additionally,
certain testing or credentialing authorities may implement multiple
different levels of the same digital credential, in which users are
subjected to the same test, same simulation, same monitoring
processes, etc., but different scoring ranges may equate to
different levels of the digital credential that may be earned by
the user. In these scenarios, whenever digital credential
requirements are updated, or if a new digital credential level is
made available, it may be possible to apply the user's previously
collected evidence data to the new digital credential requirements
or digital credential level, rather than requiring the user to
retake the test, simulation, or monitoring process. As an example,
a set of new requirements for particular digital credential may be
similar to the previous set of requirement, with the addition of a
newly imposed time limit by which the test or simulated scenario
must be completed. In other example, new digital credential
requirements or digital credential levels may raise the minimum
performance level during a test or simulation to a higher level,
and/or may require additional steps or procedures during the test
or simulation that were not required in the previous version of the
digital credential requirements. In these cases, rather than
require the user to retest/recertify to earn the updated digital
credential, the platform server 1410 may provide the service of
receiving the updated digital credential requirements or new
digital credential levels, and automatically evaluating the new
digital credential requirements/levels using the user's evidence
data that was collected with earning the previous version of the
digital credential. Thus, in step 1605, the requestor may be
authenticated and the requested data may be validated, and in step
1605 the user's evidence data may be applied the updated
testing/credentialing process. Referring to these same digital
credential requirements changes discussed above, the evaluation in
step 1606 may include automated analysis of the user's evidence
data to determine whether the user complied with the newly imposed
time limit, the new minimum performance level, and/or performed the
additional new steps or procedures during the user's previous
digital credential testing. If so, the digital credential authority
may allow the user to upgrade their digital credential
automatically without having to retake the test or simulation, etc.
If not, the user may be informed that they are required to retake
the test or simulation (or in some cases they may receive a lower
digital credential level). Either way, in step 1607, the results of
the evidence analysis and application to the new credentialing
requirements may be output to the requestor. Another potential
advantage in certain embodiments may include the protection of the
user's evidence data itself. For instance, in the above example,
the platform server 1410 might perform the analysis and application
of the user's previously stored evidence data to the new testing
requirement, without ever allowing any other entity access to the
evidence data. In other examples, the platform server 1410 may
perform the analysis and/or may provide the actual evidence data
files to the requestor device, with the sufficient authorization
from the user.
[0138] In various embodiments, the updated testing/credentialing
process in step 1604 may correspond to a re-issuance of a digital
credential, with the same or updated requirements, or may
corresponding to a different digital credential having similar
and/or overlapping issuance requirements. For instance, the
platform server 1410 may receive an updated set of requirements for
a digital credential previously issued to a credential receiver,
may retrieve the stored set of sensor data corresponding to the
relevant activities performed by the credential receiver in
connection with the issuance, may compare the retrieved set of
sensor data/activities to the updated set of digital credential
requirements, and then may generate/issue an updated digital
credential to the credential receiver, based on the comparison of
the retrieved set of sensor/activity data to the updated set of
digital credential requirements. Similar techniques may be
performed to generate and issue digital credentials to receivers
for entirely different digital credentials, rather than updated
credentials, such as similar credentials and/or credentials having
overlapping eligibility requirements.
[0139] Additional aspects described herein relate to capturing and
using user biometric data, physical user cues, and the like, in
connection with user testing and credentialing systems, on-the-job
evaluation and badging systems, and/or post-credential monitoring
systems. For example, within any automated
badging/certification/verification system, data identifying
particular physical user cues and/or user biometric data may be
collected during testing/simulation/monitoring processes and saved,
for example, in a digital credential platform server along with an
associated issued digital credential and/or the associated user.
Physical user cues may include, for example, facial expressions,
user reactions and/or noises made by the user during
testing/simulations, user body language, eye movement, and any
other user behavior or reaction detectable via cameras and external
sensors. Additionally or alternatively, various types of user
biometric data also may be collected during the testing,
simulation, and/or monitoring processes performed on the user. Such
biometric data may include, for instance, the user's temperature,
heartrate, blood pressure, respiration, skin conductivity, and
brainwave activity, and/or any known types of biometric data that
may collected during testing, credentialing, and/or monitoring
processes.
[0140] As discussed in more detail below, the user's physical cues
and/or biometric data may be collected and saved within a digital
credential platform server, and associated with the user, one or
more particular digital credentials, and/or with the particular
testing/simulation/monitoring processes during which the data was
originally detected. Once collected, the data may be used to
authenticate the testing, simulation, and/or monitoring processes,
to confirm the user's identity and to prevent errors or fraudulent
activities by users. The data may be saved with the user's digital
credential and/or into a separate portfolio of evidence, which may
be available to the user for review, and also may be provided upon
request to potential employers for review during a review or hiring
process. Such evidence data also may be applied to updated
credentialing requirements, so that in some cases a user may simply
resubmit their evidence portfolio instead of being required to
recertify their digital credential when the test or credentialing
standards are updated. In certain embodiments, the user's physical
cues and/or biometric data also may be analyzed to determine the
user's emotional states and reactions during the testing,
simulation, and/or monitoring. Additionally or alternatively, the
physical cues and biometric data may be detected for several users
and analyzed collectively to provide feedback regarding the digital
credential testing processes, simulations, monitoring, physical
testing environments, etc.
[0141] Referring now to FIGS. 17A-17B, examples are shown
illustrating facial recognition and analysis functionality that may
be performed in connection with a user testing/credentialing
process (live or simulation), or with user on-the-job credentialing
or monitoring processes. In this example, one or more cameras may
be configured to capture the user's facial features and expressions
at different points during the testing/credentialing/monitoring
processes. For tests performed within a simulation lab-type
physical testing environment, a number of designated cameras may
capture not only the user's face but also the user's body from
several different angles. Thus, certain physical testing
environments may be capable not only of capturing facial images of
the user, but also detecting detailed facial expressions at
different times during the test/simulation, and potentially eye
movement patterns, gestures, body language, and any other
non-verbal and non-written user expression data.
[0142] In other embodiments, such as for certain on-the-job
credentialing or monitoring systems, or for formal
testing/credentialing when sophisticated high-tech physical testing
environments are not used, the physical cue data and/or biometrics
data collected may be limited by the cameras and sensors available.
In some cases, a laptop camera or webcam installed at the user's
workstation may be use to capture facial images and/or to recognize
facial expressions at different times during the
testing/monitoring. However, such cameras may or may not have the
resolution and image capture capabilities to perform advanced
facial expression monitoring, eye movement, and/or body language
detection. In other examples, such as on-the-job credentialing and
monitoring scenarios, facial images might only be detectable using
lower-quality security cameras or the like that are configured to
monitor an entire floor or workspace. In such examples, the facial
images may be still be useful for certain purposes (e.g.,
confirmation of user identification), but potential may be
unsuitable for facial expression analysis, eye movement analysis,
and the like.
[0143] Additionally or alternatively, physical testing environments
(e.g., simulation labs) and/or workstation or workplace monitoring
systems may include various biometric sensors configured to detect
biometric data of the user at different times during the
test/simulation. As noted above, such biometric data may include
the user's temperature, heartrate, blood pressure, respiration,
skin conductivity, and brainwave activity, and/or any known types
of biometric data. Thus, the biometric metric may be detected and
captured via a combination of external sensors, wearable sensors,
and/or implanted sensors in some cases. For on-the-job
credentialing and monitoring, mobile wearable sensors such as
heartrate monitors, step trackers, and the like, may be used when
more advanced wearable sensors (e.g., blood pressure, respiration,
skin conductivity, brainwave activity, etc.) are not practical.
[0144] Referring now to FIG. 18, a flow diagram is shown
illustrating an express process of collecting physical cue data
and/or biometric data for a user during a user testing,
credentialing, or monitoring processes, and using the physical cue
and biometrics to authenticate the user's identity and the
associated data. The process shown in this example may be
implemented within any of the testing/credentialing systems,
simulators, workstation or workplace monitoring systems, and the
like described herein. In step 1801, a testing, credentialing,
and/or monitoring system such as those described above may execute
a test, simulation, or user monitoring process for a particular
user in connection with a digital credential that the user is
seeking or has already obtained. The particular types of tests may
include, for example, live simulations and/or virtual or augmented
reality simulations executed within a physical testing environment
700. In other examples, the testing in step 1801 may correspond to
an on-the-job credentialing system that monitors and evaluates a
user's workplace tasks and activities, or to a post-credentialing
user monitoring system configured to determine whether the user is
using their previously issued digital credentials. In step 1802,
during any of these testing, simulation, or monitoring processes,
one or more of the user monitoring devices described above,
including cameras, microphones, motion sensors, tracking devices,
and/or user biometrics sensors, may capture physical cues from the
user and/or biometric data of the user during the testing,
simulation, or monitoring processes. Such physical cues may include
particular facial expressions, user reactions and/or noises made by
the user during testing/simulations/monitoring, as well as user
body language and eye movements. In step 1803, the physical cue and
user biometric data may be encapsulated and transmitted to the
transmitted to the platform server 1410. In other embodiments,
certain systems (e.g., 1421-1423) may retain and store user's
physical cues and biometrics data locally, rather than the evidence
data being stored in a central repository. Regardless of storage
location, the physical cues and biometrics data of the user may be
associated with particular test questions and/or particular time
stamps during a testing or simulation. Additionally, when the data
is transmitted, it may be compressed and edited as needed, and/or
encrypted in order to assure data security and user privacy.
[0145] In some embodiments, the platform server 1410 may use the
physical cues and/or biometrics data collected for the user as part
of an authentication process in step 1804. For example, during any
testing/credentialing process (e.g., written testing,
computer-based testing, simulation lab testing, etc.) the user's
facial images, physical cues, and/or biometrics may be compared
against previously stored corresponding data (e.g., user images,
physical cue patterns, biometrics, etc.) in order to verify that
the correct user is taking the test/simulation. Additionally, the
user's physical cues and biometrics may provide an additional level
of authentication, by comparing the observed physical cues and
biometrics at particular times during the test or simulation to
expected physical cues and biometrics, based on what is happening
during the test or simulation at that particular time. For
instance, a simulation may be designed to present a challenging and
stressful situation to the user at a particular timestamp or within
a sequence of tasks the user is performed. In step 1804, the server
may compare the user's observed physical cues and biometrics to the
physical cues and biometrics that would be expected for the
challenging and stressful situation, in order to confirm that the
data is valid and/or that the user did not expect this situation in
advance (e.g., indicating cheating). In step 1805, the platform
serving 1410 having validated the user's identity and the
authenticity of the user's physical cues and biometrics, may store
the testing, credentialing, monitoring data in the digital
credential data store as valid data. In some embodiments, the image
data, facial cues, and/or biometrics data also may be retained and
stored by the platform server for future analysis.
[0146] In some embodiments, the data relating to the user's
physical cues and biometrics collected during a test, simulation,
or during on-the-job monitoring, may be further evaluated to
identify the user's emotional states at different times. For
instance, certain simulations may be specifically designed to
invoke certain emotional states (e.g., anger, boredom, frustration,
surprise, etc.), and the user's level of performance while
experiencing those emotional states may be particularly important
for certain testing/credentialing processes. In these examples and
other cases, either exhibiting or not exhibiting particular emotion
states may be an eligibility requirement for a credential receiver
to obtain certain types of digital credentials. Thus, the data
collected during the test, simulation, or monitoring in step 1801
may be used not only for user identification/authentication, but
also may be analyzed to (1) determine the user's emotional state at
different times during the test, simulation, or monitoring, (2)
compare that emotional state to an expected emotional state based
on what the user is experiencing, and (3) evaluate the user's
reactions, levels of skills performance during different emotional
states.
[0147] Additionally, in some embodiments, the physical cues,
biometrics data, and/or emotional states detected for multiple
users may be aggregated for the same tests, simulations, monitoring
environments, etc. The aggregated data for tests may be used to
revise current tests and simulations, design new tests and
simulations, and for training users how to respond to particular
scenarios and situations (e.g., workplace accidents).
[0148] Certain aspects described herein relate to an automatic
recruiting engine and corresponding functionality that may analyze
available data within a digital credential platform and determine
matches between individuals (e.g., digital credential receivers)
and potential employers. For example, in some embodiments, an
automatic recruiting engine may perform some or all of the tasks of
a professional recruiter, and may take the place of a recruiter
role or a job seeker role by proactively performing matching
analyses between available/potential job listings and potential
candidates for those jobs. The automatic recruiting engine and/or
associated digital credential platform may provide notifications to
users (e.g., credential receivers) of job listings for which the
user is qualified, and/or notifications to employers that may be
looking candidates having a specific skill set and/or matching a
specific profile. In certain embodiments, automatic recruiting
engine may also include functionality to provide credential
receivers with suggestions of particular digital credentials that
may expand their job prospects, based on analyses of the current
job market/job listings and the user's digital credential portfolio
and other qualifications. An advanced skills-based or digital
credential-based matching analysis may be performed, but in certain
examples the analysis may include additional factors such as age,
seniority, worker career arc, personal candidate data, location,
salary expectations, etc.
[0149] Referring now to FIG. 19, an example computing environment
1900 is shown, including a digital credential platform server 1910,
in communication with employer client devices 1960, digital
credential issuer devices 1930, and/or bade earner devices 1940. In
some examples, the digital credential platform server 1910 may be a
digital credential server similar or identical to the digital
credential server 610 discussed above. Thus, server 1910 may be
configured as a digital credential repository and credentialing
system, acting as a clearinghouse for digital credential owners,
issuers, earners, endorsers, etc. As shown in this example, server
1910 may include an automated recruiting engine 1915 configured to
perform, among other tasks, an automated matching analysis between
potential employees and jobs/employers. In some embodiments, the
recruiting engine 1915 may retrieve and analyze worker-related
and/or job related data from various data stores, which are shown
as internal data stores or database in this example but may be
implemented as external data sources in other cases. For instance,
digital credential data stores may be configured to store
credentialing information such as the details of the particular
digital credentials earned by particular receivers (e.g., digital
credential portfolios), including any combination of the digital
credential data and associated data discussed above. Additionally,
a user data store may store various user data for users who have
earned digital credentials stored within the digital credential
data store. Such user data may include demographic data, employment
and educational data, other qualifications, current employment
details, current salary and salary preferences, current
hours/lifestyle and hours/lifestyle preferences, current work
satisfaction, current work location and work location preferences,
etc. Additionally, a job listing database may include
recent/current jobs postings from various employers. Jobs postings
in this database may include a variety of job description data,
qualification requirements, and other factors, include data such as
job title, job description, required digital credentials, required
skills, required educational qualifications, required
abilities/traits, job location, job hours/days commitment, job
salary or range, company information, and the like. Additionally,
in some embodiments data from an employment database also may be
used in the matching analyses performed, including data relating to
the jobs/positions currently held by workers at different
companies. Such employment data may include, for a company's
current workforce, current positions held, salaries, locations, job
descriptions, skills, requirements, qualifications, technologies
used, current job satisfaction level, etc.
[0150] In this example, the digital credential platform server 1910
may receive such data from various external data sources, including
employer devices 1960, digital credential issuer devices 1930, and
digital credential receiver devices 1940, as well as other external
data sources including job data, employment market data,
technical/skills data, etc. As discussed below in more detail, the
automated recruiting engine 1915 within server 1910 may use various
matching algorithms, analytics engines, and/or artificial
intelligence components to analyze the data and identify potential
matches between workers and jobs/companies.
[0151] Referring now to FIG. 20, a flow diagram shown illustrating
an example process of analyzing worker/employee data, and
job/company data, in order to determine potential matches that may
be suggested to one or both parties. Thus, in some embodiments,
this process may be performed by digital credential platform server
1910, using an automated recruiting engine 1915 to retrieve and
analyze data in order to determine possible matches. In step 2001,
the recruiting engine 1915 may retrieve digital credential data,
user data, employment data, and/or job listing data relating to one
or more employers and users within the digital credential network
1900. The data retrieved in step 2001 may include any or all of the
data from the various data sources discussed above. In step 2002,
the recruiting engine 1915 may analyze the data retrieved in step
2001 to determine one or more potential matches between workers and
jobs. As noted above, the analysis in step 2002 may use data
matching algorithms, analytics engines, and/or artificial
intelligence components to analyze the data and identify potential
matches between workers and jobs. In some cases, the analysis in
step 2002 may be limited to only job seekers, while in other cases
the analysis may include currently employed workers (e.g., so the
recruiting engine may potentially suggest a new job or career
change). Additionally, in some cases, the analysis in step 2002 may
be limited to only existing job postings from employers, while in
other cases the analysis may match a worker to an employer even if
that employer has is not currently hiring. The matching in step
2002 may be based on any combination of the user data, digital
credential/skills data, job data, and employment data discussed
above. For instance, the recruiting engine 1915 may even include
data points such as the satisfaction level of a current employee
which may be determined based on employee surveys or other direct
feedback, or inferred based on job seeking/web-browsing behavior, a
decline in performance, and/or recently acquiring new digital
credentials or other qualifications which may indicate an intention
to change jobs or careers. For example, the platform server in step
2002 may determine a set of capabilities of the credential
receiver, based on the digital credentials issued to the credential
receiver, and then determine a matching set of field data objects
(e.g., job listings) having capability characteristics matching the
determined set of capabilities of the credential receiver.
[0152] Additional factors such as salary matching, location
matching, career arc projections, lifestyle matching (e.g., hours,
stress, dress code, corporate culture), also may be used along with
digital credentials and skills matching, to determine candidates
for jobs/companies and vice versa. In step 2003, the automated
recruiting engine 1915 may determine whether or not to transmit
notifications based on the worker-to-job/company matches identified
in step 2002. In some cases, the determination of whether to
transmit a notification may be based on the strength of the match
(e.g., a high correlation between the worker characteristics and
job listing characteristics greater than a similarly threshold
would trigger notifications). The determination also may be based
on whether or not the individual user and/or employer has requested
or subscribed for such notifications, including any specific
criteria provided by the worker (e.g., only notify me of my top 3
matches per week, only notify me of jobs in California, only notify
me of jobs with a 15% salary increase, only notify me of jobs that
use my most recent acquired digital credential-related skills,
etc.) and/or specific criteria provided by the employer (e.g., only
notify us for matches of current employees of a competitor company,
only notify us for matches who have digital credential ABC, etc.).
In step 2004, the notifications determined in step 2003 (if any)
may be generated by the automated recruiting engine 1915 and
transmitted from the digital credential platform server 2010 to the
appropriate party. In some cases, such notifications may inform the
worker or employee of the potential match, but might not reveal the
identity of the matching counterparty until a later time (e.g.,
until both parties except the match or until the party has paid
their subscription fee, etc.). For instance, a digital credential
platform server may transmit a notification to the credential
receiver identifying correlation metrics for one or more field data
objects, but the notification purposefully might not identify
selected field data object. Similarly, the digital credential
platform server may transmit a second notification to an owner
associated with a selected field data object, wherein the second
notification identifies the correlation metric for the selected
field data object but does not identify the credential
receiver.
[0153] A number of variations and modifications of the disclosed
embodiments can also be used. Specific details are given in the
above description to provide a thorough understanding of the
embodiments. However, it is understood that the embodiments may be
practiced without these specific details. For example, well-known
circuits, processes, algorithms, structures, and techniques may be
shown without unnecessary detail in order to avoid obscuring the
embodiments.
[0154] Implementation of the techniques, blocks, steps and means
described above may be done in various ways. For example, these
techniques, blocks, steps and means may be implemented in hardware,
software, or a combination thereof. For a hardware implementation,
the processing units may be implemented within one or more
application specific integrated circuits (ASICs), digital signal
processors (DSPs), digital signal processing devices (DSPDs),
programmable logic devices (PLDs), field programmable gate arrays
(FPGAs), processors, controllers, micro-controllers,
microprocessors, other electronic units designed to perform the
functions described above, and/or a combination thereof.
[0155] Also, it is noted that the embodiments may be described as a
process which is depicted as a flowchart, a flow diagram, a swim
diagram, a data flow diagram, a structure diagram, or a block
diagram. Although a depiction may describe the operations as a
sequential process, many of the operations can be performed in
parallel or concurrently. In addition, the order of the operations
may be re-arranged. A process is terminated when its operations are
completed, but could have additional steps not included in the
figure. A process may correspond to a method, a function, a
procedure, a subroutine, a subprogram, etc. When a process
corresponds to a function, its termination corresponds to a return
of the function to the calling function or the main function.
[0156] Furthermore, embodiments may be implemented by hardware,
software, scripting languages, firmware, middleware, microcode,
hardware description languages, and/or any combination thereof.
When implemented in software, firmware, middleware, scripting
language, and/or microcode, the program code or code segments to
perform the necessary tasks may be stored in a machine readable
medium such as a storage medium. A code segment or
machine-executable instruction may represent a procedure, a
function, a subprogram, a program, a routine, a subroutine, a
module, a software package, a script, a class, or any combination
of instructions, data structures, and/or program statements. A code
segment may be coupled to another code segment or a hardware
circuit by passing and/or receiving information, data, arguments,
parameters, and/or memory contents. Information, arguments,
parameters, data, etc. may be passed, forwarded, or transmitted via
any suitable means including memory sharing, message passing, token
passing, network transmission, etc.
[0157] For a firmware and/or software implementation, the
methodologies may be implemented with modules (e.g., procedures,
functions, and so on) that perform the functions described herein.
Any machine-readable medium tangibly embodying instructions may be
used in implementing the methodologies described herein. For
example, software codes may be stored in a memory. Memory may be
implemented within the processor or external to the processor. As
used herein the term "memory" refers to any type of long term,
short term, volatile, nonvolatile, or other storage medium and is
not to be limited to any particular type of memory or number of
memories, or type of media upon which memory is stored.
[0158] Moreover, as disclosed herein, the term "storage medium" may
represent one or more memories for storing data, including read
only memory (ROM), random access memory (RAM), magnetic RAM, core
memory, magnetic disk storage mediums, optical storage mediums,
flash memory devices and/or other machine readable mediums for
storing information. The term "machine-readable medium" includes,
but is not limited to portable or fixed storage devices, optical
storage devices, and/or various other storage mediums capable of
storing that contain or carry instruction(s) and/or data.
[0159] While the principles of the disclosure have been described
above in connection with specific apparatuses and methods, it is to
be clearly understood that this description is made only by way of
example and not as limitation on the scope of the disclosure.
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