| Notes |
SISO-PN-015-2016
Product Nomination
for
Human Performance Markup
Language
Version 1.0
9 May 2016
SAC Approved: 02/02/2016 EXCOM Approved: 05/09/2016
SISO-PN-015-2016, Product Nomination for Human Performance Markup Language
Copyright © 2016 by the Simulation Interoperability Standards Organization, Inc.
P.O. Box 781238
Orlando, FL 32878-1238, USA
All rights reserved.
Permission is hereby granted to quote any of the material herein, or to make copies thereof, for
non-commercial purposes, as long as the proper attribution is made and this copyright notice is
included. All other uses are prohibited without written permission from the SISO, Inc. Board of
Directors.
SISO Inc. Board of Directors
P.O. Box 781238
Orlando, FL 32878-1238, USA
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This is an approved SISO Product Nomination.
SISO-PN-015-2016, Product Nomination for Human Performance Markup Language
Revision History
Version Section Date
(MM/DD/YYYY)
Description
V1.0 All 05/09/2016 Published version
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SISO-PN-015-2016, Product Nomination for Human Performance Markup Language
Table of Contents
1. Product title * .......................................................................................................... 5
2. Proponent name(s) and contact information ....................................................... 5
3. Type of product(s) (*Balloted Products)............................................................... 5
4. Product description................................................................................................ 6
5. Identification of the community to which product applies.................................. 7
6. Problem(s) and/or issue(s) that the proposed product addresses..................... 7
a) State the specific need or requirement for this product in the community (1-2 sentences) ............ 7
b) Provide a detailed discussion of the specific need or requirement for this product in the
community. .................................................................................................................................8
c) Have you investigated similar products in the community to ensure no overlap exists?................ 9
7. Indication of the maturity of the product.............................................................. 9
a) Detailed description on how the problem/issue will be solved (approach)..................................... 9
b) Brief discussion on the maturity of the proposed product. .......................................................... 10
c) Brief discussion on alternative approaches to the proposed product .......................................... 10
d) Provide examples of prototypes of the proposed product or reasons why this product will not be
prototyped................................................................................................................................. 10
e) What impact will the proposed product have on the M&S community?....................................... 12
f) What impact will this proposed product have on the SISO community?...................................... 13
g) What is the impact to the community on the LACK of this proposed product? ............................ 13
h) What are the domain implications for this proposed product? .................................................... 13
i) State which SIW conference track takes an active interest in the development of this proposed
product. .................................................................................................................................... 13
8. Planned compliance testing ................................................................................ 13
9. Schedule of product development milestones including reviews and reports13
10. Candidate volunteers for the product development effort................................ 14
11. Product review cycle ............................................................................................ 14
Acronyms..................................................................................................................... 15
References................................................................................................................... 15
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This is an approved SISO Product Nomination.
SISO-PN-015-2016, Product Nomination for Human Performance Markup Language
SISO Product Nomination for
Human Performance Markup Language
SISO-PN-015-2016
1. Product title *
Human Performance Markup Language
2. Proponent name(s) and contact information
First name: Courtney Last name: Dean
Affiliation: Aptima, Inc.
Street Address: 12 Gill Street, Suite 1400
City: Woburn State: MA Zip: 01801
Phone #: 781.496.2455 Fax #:
Email: cdean@aptima.com
First name: Michael Last name: Tolland
Affiliation: Aptima, Inc.
Street Address: 12 Gill Street, Suite 1400
City: Woburn State: MA Zip: 01801
Phone #: 781.496.2458 Fax #:
Email: mtolland@aptima.com
Additional proponents:
Name Organization Email Address
Michael Tolland Aptima, Inc. mtolland@aptima.com
Mike Paley Aptima, Inc. paley@aptima.com
Charles Amburn Army - STTC charles.amburn@us.army.mil
Courtney Dean Aptima, Inc. cdean@aptima.com
Mike Hruska Problem Solutions mike@problemsolutions.net
Rodney Long Army - STTC rodney.a.long3.civ@mail.mil
Scott Galster AFRL scott.galster@us.af.mil
Steven Burnett ARI steven.f.burnett.civ@mail.mil
Timothy Burns InnovaSystems tburns@innovasi.com
Webb Stacy Aptima, Inc. wstacy@aptima.com
Beth Atkinson NAWC-TSD Beth.atkinson@navy.mil
Eric Watz Lumir eric.watz.ctr@us.af.mil
John Costa RePubIT jbcosta@repubit.com
Alex Walker MedStar SiTEL alex.walker@email.sitel.org
3. Type of product(s) (*Balloted Products)
X Standard*
Guidance*
Reference
Administrative
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SISO-PN-015-2016, Product Nomination for Human Performance Markup Language
The SISO Standards Product will be produced IAW the approved SISO-STD Standards Product Template
found in the SISO’s Digital Library Templates folder here:
https://www.sisostds.org/DigitalLibrary.aspx?EntryId=32979
The SISO Standards Product will be published on the Approved Standards webpage here:
https://www.sisostds.org/ProductsPublications/Standards/SISOStandards.aspx
The associated XML-schema data files will be published on the SISO Product Data Files webpage here:
https://www.sisostds.org/Schemas.aspx
4. Product description
Human Performance Markup Language (HPML) is an XML-Schema-based language intended to cover all
meaningful aspects of human performance measurement in various training and operational
environments. The HPML hierarchy enables the representation of both generic concepts (e.g.,
measurements and assessments) and mission specific concepts (e.g., instances of measurements and
instances of assessments) necessary for capturing the experiences associated with human performance
and human behavior. Specifically, it is an XML based language designed to express performance
measurement concepts in a format that is both machine and human readable. It enables the explicit
combination and transformation of performance data into performance measurements and assessments.
This allows measures to be constructed independent of any specific training or operational system. At a
basic level, the performance measurement instructions defined in HPML can be used to specify the
system data elements to be collected, the calculations to use to process the data, and when to produce
performance measurement results.
At a high level, HPML is broken up into many different sub schemas that represent the different parts of
the overall HPML schema. Each part of the schema has different dependencies that work together to
calculate measures and assessments on a given data source. Figure 1 provides a schema dependencies
diagram that shows the links between each of the main groups within the schema.
The schema is separated into six distinct groups, 1) HPML, 2) Computation, 3) Results, 4) Assessments,
5) Measures, and 6) Instances and Periods. These groups make up the core components of HPML and
can be added to or expanded with additional links in the schemas. Each group is described in more detail
below:
Figure 1. HPML high level conceptual architecture
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SISO-PN-015-2016, Product Nomination for Human Performance Markup Language
HPML. The HPML group refers to shared and top level elements (e.g., MeasureDefinition element) and
attributes that all the other schemas must reference. This schema organizes all sub schemas that make
up the standard HPML Core.
Computation. The Computation group refers to the schemas that represent the algorithms, triggers, and
other computational components of HPML. These components can be combined with both the
Assessments and Measures groups.
Measures. The Measures group refers to schemas representing the linking of data sources and
computation to produce measurement outputs from a given data source.
Assessments. The Assessments group refers to schemas representing the assessment of a given
measurement’s values either by category (Expert, Novice, etc.) or Value (100%, 99%, 75%, 10.3, etc.).
Results. The Results group refers to schemas representing the output of both measures and
assessments, detailing the information produced by specific measure points throughout an entire
measurement period.
Instances and Periods. The Instances and Periods group refers to schemas representing the creation
and use of measures and assessments for a given context. This schema defines the instantiation of
HPML elements at specific points in time, or specific locations within space. Every element in this schema
has a time and/or location component. Whether that time is very short or spans several years, whether
the location is a small area or a line on a map, the schema refers to when and where data should be
computed so that measures and results can be linked to specific places and times.
While the segregation of HPML into multiple separate, but dependent, schemas may produce an added
level of complexity, ultimately, it provides the language with the added benefit of extensibility, which is
critical in the ever changing technological landscape of training environments. The modularity of HPML’s
design allows for the replacement of sub-schemas with new additions while still maintaining the core
capability. Under this design, a developer could extend the schema to allow for more functionality, or to
test new components for a specific context, while keeping the base schema intact. A full description of the
HPML schema can be found in the HPML user guide posted to the HPML SISO Study Group.. The User
Guide includes descriptions of elements of the schemas (e.g., definitions of what the elements and
attributes mean) as well as example measures utilizing these schemas.
5. Identification of the community to which product applies
Any M&S community involved in the training of human participants can benefit from the use of HPML.
HPML provides a method for defining how to measure and assess humans or other systems against data
provided from any Model or Simulation. In the near term, the community that will derive the largest benefit
will be the training simulation community.
6. Problem(s) and/or issue(s) that the proposed product addresses
There is no standard method of expressing human performance measures. Currently performance
measurement approaches rely on proprietary measurement built into individual simulations. This
approach makes it difficult to move measurement between simulations and easily make modifications to
how performance will be calculated or assessed. Also, there is a need for transparency in the calculations
so that it is clear how measurements were calculated and assessed. Typically, this is not possible
because many simulation based measures are locked within the Simulation software and not readily
available to the end user.
a) State the specific need or requirement for this product in the community (1-2 sentences)
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Within training environments there is a need for an open and standard way to measure and
assess human and system performance against varying data sources. Such an approach should
be a clear and descriptive way to understand the methods by which measurement and
assessment are obtained on specific data points.
b) Provide a detailed discussion of the specific need or requirement for this product in the
community.
The amount of data we generate grows daily. According to Eric Schmidt, former CEO of Google,
There were 5 exabytes of information created between the dawn of civilization through 2003,
but that much information is now created every 2 days. (Schmidt, 2010 at Google’s Atmosphere
convention.)
This is true, in microcosm, in the training domain. Simulator repositories, computer-based
instruction systems, and educational data management systems are full of video and audio files
and archived responses to a wide variety of scenario situations and computer and machinescored tests.
These data might be used to improve training in many ways, ranging from student feedback to
adaptive training to evaluating different approaches to instruction. Unfortunately, in large part
this has not happened. A primary reason is that the raw data need to be transformed in order to
be useful.
This need is particularly salient in the ever evolving context of Live, Virtual, and Constructive
(LVC) training. The addition of virtual and constructive elements to live training provides a level
of control, convenience, and cost savings that makes live training a more practical solution. On
the flip side, the addition of live elements to virtual and constructive training adds a level of
realism that cannot be otherwise achieved. There is even the possibility of dynamically mixing
these three kinds of elements. In the future, for example, when a maintenance problem
develops with an actual aircraft, a virtual or even constructive entity might be substituted during
training [1], and when there is trouble with the distributed simulation network that prevents live
elements from seeing virtual or constructive elements, an actual aircraft might be substituted
instead to enable the continuation of a training exercise.
Standardized modern simulation network protocols such as the High Level Architecture (HLA),
Distributed Interactive Simulation (DIS), and Test and Training Enabling Architecture (TENA)
make much of this possible, because they track and report on entities in a similar fashion
whether they are live, virtual, or constructive. Because LVC training, especially LVC after-action
reviews, are enhanced by objective, automatically computed performance measurements, it
follows that a standard that can track and measure the performance of all three kinds of
entities—that is, all the entities in the training battlespace, even as they change from live to
virtual to constructive—is an important component of training of the future [2].
This in turn implies a need to go beyond device-specific measurement for LVC training.
Measurements that are embedded in actual platforms, simulators, or even in behavior
specifications for constructive entities, might not be transportable from medium to medium
unless they agree on a standard for expressing and capturing performance measurement and
assessment.
HPML holds the promise to be such a standard. It is agnostic with respect to the kinds of data
used to compute measurements and assessments. It also externalizes measurement and
assessment specifications, so that they can be used with any data source. As long as there is a
way to map data from live platforms to simulators to constructive entities, HPML will be able to
specify measurements that can seamlessly adapt to LVC environments as the environments
themselves change.
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HPML was designed to provide a means by which the transformation of raw data can be
specified and the results recorded [3]. Two particularly important transformations are
measurements, which are direct computations on the raw data, and assessments, which are
computations on the measurements and the data that provide interpretation for measurement.
To help clarify this distinction, consider the following examples. A student’s answers on an exam
are the raw data, percent correct on the exam is a measurement, and conversion of percent
correct into a letter grade is an assessment. A pilot’s glideslope position as they land the plane
is the raw data, computation of the deviation from ideal glideslope during landing is the
measurement, and categorization of the size of that error as acceptable or unacceptable is the
assessment. A leader’s electronic communications with her distributed team are the raw data,
the patterns inherent in those communications are the measurements, and the extent to which
her communication patterns match the communication patterns of known high-performance
leaders is the assessment. And so on.
Measures and assessments make it considerably more likely that training professionals can use
available data to provide more effective training experiences [4]. Historically, getting such
measurements and assessments has meant making changes to the simulation equipment,
training environment, or computer-based instruction system. Because this can be timeconsuming and expensive, HPML is designed to adapt to a wide range of data sources, and to
provide a way to specify measurements and assessments that is external to specific training
equipment. This also enables applications in the training environment to share measurement
and assessment specifications and results, thus encouraging a healthy ecosystem of training
applications that will result in improved training experiences.
c) Have you investigated similar products in the community to ensure no overlap exists?
We have reviewed all existing Study Groups, Product Groups in SISO and determined that
nothing overlaps sufficiently with HPML. We have also reviewed standards relating to the logging
of human activity (i.e., Activity streams , Contextualized Attention Metadata [CAM], Tutor
Message Format [TMF], Experience API [xAPI], and eXtensible Event Stream) and found that
none of them provide a specific nor sufficient coverage of human performance within simulation
or learning environments.
7. Indication of the maturity of the product
a) Detailed description on how the problem/issue will be solved (approach)
The problem revolves around the need for a configuration/document that can be read by both
humans and machines and can be used to measure and assess the performance of humans
operating in various simulation environments. The solution that we propose is the adoption of an
XML schema called HPML (Human Performance Markup Language) as a universal approach to
capturing human performance in simulation environments.
The schema will create a soft link between specific data points and measurement allowing for
easier transition between different simulations with different data structures. We call these Data
Requests. These elements in the schema allow you to query data from any data source like a
Structured Query Language (SQL) statement. The Data Requests can then be linked to a
measurement. If the data source changes only the Data Request must change - not the entire
measurement.
This standard schema outlines how a measurement should be calculated using a format that is
generic enough to allow people to create and implement new algorithms, but strict enough to
provide a recognizable structure that people can use to understand the intent of the measurement
or assessment. Standardization facilitates interoperability. With the consistent use of a standard
schema, measures and assessments become transferable and usable in multiple domains (e.g.,
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different weapon platforms) and interpretable by different simulators and users within the
modeling and simulation community. If people cannot understand how a measurement or
assessment is derived, then we will lose the ability to be interoperable.
The schema also adds ways of representing the output of these measurements and
assessments. This is important for traceability as it allows you to link the results back to the
measures and assessments that produced them. We have created both guidelines on how this
schema and resulting documents can be validated, and user guides describing best practices for
using the schema and resulting documents.
b) Brief discussion on the maturity of the proposed product.
HPML has been used internally at Aptima for over 7 years and has evolved over those 7 years
through review and implementation. The current version of HPML has been used in practice in
many platforms and simulations. An HLA BOM was developed for the NASMP FOM called the
HPM BOM, this BOM allows the passing of HPML via HLA. A comprehensive User Guide
detailing the library of HPML schemas and schema elements has been produced and is available
for reference.
c) Brief discussion on alternative approaches to the proposed product
The bottom line is that without a standard, uniform measurement across domains and platforms
cannot exist. This leaves few viable alternatives other than continuing with the status quo.
Detailed documentation of measurements for each platform is a good first step. It will allow
people to better understand how measurement in a simulation works and how the results were
gathered. However, this action must be repeated for each instance of measurement and for each
platform into which measurement is introduced. The amount of labor required to achieve such
documentation would likely be prohibitively time consuming.
xAPI is an alternatively that solves part of the problem outlined in this nomination. xAPI provides
a standard format for passing measure results between learning management systems (LMSs)
and other performance systems. However, it does not provide a standard way for defining and
calculating human performance. Thus, while it can help pass data from multiple sources to a
single integrated location, it does not pass any of the contextual information necessary to allow
for interpretation of the results. Those exposed to the results from multiple sources may have only
limited information from which to make assessments about the performance of their trainees.
d) Provide examples of prototypes of the proposed product or reasons why this product will
not be prototyped.
Figure 2, below, provides an example of a simple performance measure implemented in HPML.
In this example, the DataRequest identifies the object and its specific attributes that are required
as input to a measurement. In this case, the DataRequest is requesting the X,Y and Z
components of the WorldLocation attribute of the Aircraft, which has an Id equal to a value that
will be supplied later as a parameter. The SystemMeasureTemplate (part of the Measures
group) in our example uses the WorldLocation attribute of the Aircraft object to determine if the
aircraft is currently above a prescribed altitude. The maximum altitude in this measure is defined
as a constant of 4000 ft. in the SystemMeasureTemplate. A Parameter is also passed into the
SystemMeasureTemplate, specifying the specific Aircraft from which to retrieve the Altitude.
The use of a Parameter here allows the SystemMeasureTemplate to be reused for different
aircraft. At the core of the SystemMeasureTemplate are two nested MeasureComputations. The
inner most computation uses the DataRequest (WorldLocation.X,Y,Z) and passes the parameter
defined in the template to the data request. The inner most computation also uses a function
library plugin to compute the Altitude. The result of this computation is then used as an operand
for the outer MeasureComputation, which compares the altitude value to a constant that points to
the maximum altitude ref and determines if the aircraft’s altitude is greater than the prescribed
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SISO-PN-015-2016, Product Nomination for Human Performance Markup Language
maximum altitude. The SystemMeasureDefinition finalizes the specification contained within the
SystemMeasureTemplate. More specifically, the SystemMeasureDefinition defines any
parameters that have been exposed, in this case the marking identifier of the aircraft.
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SISO-PN-015-2016, Product Nomination for Human Performance Markup Language
Figure 1. Simple performance measure implemented in HPML
e) What impact will the proposed product have on the M&S community?
The incorporation of HPML as a standard will have several positive benefits to the M&S
community including, briefly: measurement reuse, increased availability of the right data,
increased understanding of trainee strengths and weaknesses, and reduced workload for
instructors and system operators. HPML use will provide a way for the M&S community to create
interoperable performance systems in simulation and modeling systems. It will enable users to
<DataRequests>
<DataRequest
id="61300000-0000-0000-0000-000000000003" type="ENTITY"
dataSourceRef="Source" from="Aircraft"
select="WorldLocation.X, WorldLocation.Y,
WorldLocation.Z" where="[Marking] == {Marking}"> <Parameters> <Parameter name="Marking" type="String"/> </Parameters>
</DataRequest>
</DataRequests>
<Measures>
<SystemMeasureTemplate id="61300000-0000-0000-0000-000000000004" oneOff="true" name="CrossedAltitudeThreshold">
<Description>
Measure to determine if aircraft broke the altitude threshold
</Description> <Constants>
<Constant name="MaxAltitude” type="Int32" value="4000" units="feet"/> </Constants>
<Parameters>
<Parameter name="Aircraft_Marking" type="String"/> </Parameters>
<MeasureComputation operator="Greater_Than" functionName="Math">
<MeasureComputation operator="default" functionName="Altitude">
<Input
type="datarequest"
ref="61300000-0000-0000-0000-000000000003">
<Input type="parameter"
ref="Aircraft_Marking" name="Marking"/>
</Input> </MeasureComputation>
<Input type="constant" ref="MaxAltitude"/> </MeasureComputation>
</SystemMeasureTemplate>
</Measures>
<MeasureDefinitions>
<SystemMeasureDefinition name="CrossedAltitudeThreshold"
id="7F12964C-1DF7-E3FE-5FCF-E5870A1879A4"
systemMeasureTemplateId="61300000-0000-0000-0000-000000000004" visibility="VISIBLE">
<Input inputType="VALUE"
name="Aircraft_Marking" type="String"
value="AC1"/> </SystemMeasureDefinition>
</MeasureDefinitions>
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SISO-PN-015-2016, Product Nomination for Human Performance Markup Language
leverage existing HPML performance measures in new domains and platforms with minimal
modification reducing. The status quo customization for every implementation is costly and
inefficient. Reuse will eliminate this, especially when reapplying measures to similar platforms
(e.g., fifth generation fighters). The standard language of HPML being human readable enables
community stakeholders to review and understand what measures are capturing, ensuring that
the right data are being used. With increased accessibility to measures and the consequential
reduced workload, more and richer measures can be applied to better assess trainees and more
precisely diagnose proficiency gaps.
f) What impact will this proposed product have on the SISO community?
This will open a new avenue for SISO, which has historically focused solely on Simulation and
Modeling systems and not on the humans using those systems for training, or understanding
purposes.
g) What is the impact to the community on the LACK of this proposed product?
Human measurement is here to stay and will only grow in the future. Simulation systems will need
a way to measure performance and end users will want a way to reuse performance measures
defined across multiple simulation and modeling systems. This proposed product has had a long
period of review and good backing from multiple domains. It provides a solution to a pervasive
problem that will continue as the focus on human performance measurement remains forefront.
h) What are the domain implications for this proposed product?
This will work across multiple domains and be geared specifically at bringing Human performance
to all domains. We hope to deliver a clear and standard way to define Human Performance
across all domains.
i) State which SIW conference track takes an active interest in the development of this
proposed product.
M&S Specialty (SPEC) Track
8. Planned compliance testing
Specification of compliance tests will be included in the standard, but there is no planned
compliance service.
9. Schedule of product development milestones including reviews and reports
Approval phase
Study group final report and product nomination August 2015
Approval of product nomination by SAC April 2016
2015-2016: Technical specification of HPML
HPML PDG Kickoff May 2016
Review and commenting on HPML 1.1 May - July 2016
First draft for PDG discussion July-Aug 2016
HPML First draft approval Aug - Sept 2016
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SISO-PN-015-2016, Product Nomination for Human Performance Markup Language
Review and commenting on HPML 1.2 Oct - Nov 2016
Second draft for PDG discussion December 2016
Second draft approval Jan - Feb 2017
HPML User Guide update and Schema document
User Guide and Schema for PDG discussion December 2016
User Guide and Schema draft approval Jan-Feb 2017
SAC / EXCOM processing
HPML PDG provide Circulation Package to SAC March 2017
SAC conduct Initial Ballot April 2017
HPML PDG conduct Balloter Comment Resolution 2017 Spring TIM
HPML PDG document Comment Resolution in Tracking System 2017 Spring TIM
SAC conduct Recirculation Ballot (if needed) July 2017
HPML PDG conduct Balloter Comment Resolution (if needed) 2017 Fall SIW – Sep 2017
HPML PDG document Comment Resolution in Tracking System (if needed) Sep 2017
HPML PDG provide Product Approval Package to SAC for processing Oct 2017
EXCOM approval Dec 2017
SAC publish approved SISO Standard Jan 2018
HPML PDG provide SAC Terms of Reference for Product Support Group (PSG) Feb 2018
10. Candidate volunteers for the product development effort
Name Organization Email Address Phone Numbers
Michael Tolland Aptima, Inc. mtolland@aptima.com 781.496.2458
Mike Knapp Aptima, Inc. knapp@aptima.com 321.710.3201
Courtney Dean Aptima, Inc. cdean@aptima.com 781.496.2455
Webb Stacy Aptima, Inc. wstacy@aptima.com 781.496.2437
Beth Atkinson NAWC-TSD beth.atkinson@navy.mil 407.380.4773
Eric Watz Lumir eric.watz.ctr@us.af.mil 937.938.4068
Alex Walker MedStar - SiTEL alex.walker@email.sitel.org 202.364.5180 ext. 9248
Marc Banghart Wyle, Inc marc.banghart@wyle.com 904-644-6605
Robert Pratten Transmedia
Storyteller, Ltd
robert.pratten@gmail.com 415-287-4150
11. Product review cycle
Product(s) should be reviewed in accordance with SISO policy and procedures. Most importantly, the
product(s) should be reviewed as often as technology changes and/or new information becomes
available.
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SISO-PN-015-2016, Product Nomination for Human Performance Markup Language
Acronyms
BOM Base Object Model
CAM Contextualized Attention Metadata
CEO Chief Executive Officer
DIS Distributed Interactive Simulation
FOM Federation Object Model
HLA High Level Architecture
HPM Human Performance Management
HPML Human Performance Markup Language
LMS Learning Management System
LVC Live, Virtual, and Constructive
M&S Modeling and Simulation
NASMP Naval Aviation Simulation Master Plan
PDG Product Development Group
SAC Standards Activity Committee
SISO Simulation Interoperability Standards Organization
SPEC Specialty
SQL Structured Query Language
TENA Test and Training Enabling Architecture
TMF Tutor Message Format
xAPI Experience Application Program Interface
XML Extensible Markup Language
References
Author Name Document Title Event Name
Date
Published Name of Publication
Roessingh, J.
J. M., &
Verhaaf, G. G.
Training Effectiveness
of embedded training
in a (multi-) fighter
environment-a
discussion paper
NATO HFM-169
Research
Workshop on the
Human Dimensions
in Embedded
Virtual Simulation
2010 proceedings of the
NATO HFM-169
Research Workshop
on the Human
Dimensions in
Embedded Virtual
Simulation
Schreiber, B.
T.
Transforming training:
A perspective on the
need for and payoffs
from common
standards
2013 Educational
Publishing
Foundation
Stacy, E. W.,
Merket, D.,
Freeman, J.,
Wiese, E., &
Jackson, C.
A Language for
Rapidly Creating
Performance
Measures in
Simulators
2005
Interservice/Industry
Training, Simulation
& Education
Conference
2005 In Proceedings of the
2005
Interservice/Industry
Training, Simulation &
Education
Conference
MacMillan, J.,
Entin, E. B.,
Morley, R., &
Bennett Jr, W.
Measuring team
performance in
complex and dynamic
military environments:
2013 Military Psychology
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SISO-PN-015-2016, Product Nomination for Human Performance Markup Language
Author Name Document Title Event Name
Date
Published Name of Publication
The SPOTLITE
method.
Poepppelman,
T., Hruska,
M., Long, R.,
Amburn, C.
Interoperable
Performance
Assessment for
Individuals and
Teams Using
Experience API
Second Annual
GIFT Users
Symposium
2015 Proceedings of the
Second Annual GIFT
Users Symposium
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