<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alberto Tremori</style></author><author><style face="normal" font="default" size="100%">Sasha B. Godfrey</style></author><author><style face="normal" font="default" size="100%">Luca Berretta</style></author><author><style face="normal" font="default" size="100%">Arnau Carrera Viñas</style></author><author><style face="normal" font="default" size="100%">Pavlina Nikolova</style></author><author><style face="normal" font="default" size="100%">Iliyan Hutov</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Simulation-Based Training with Gamified Components for Augmented Border Protection</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">High Level Architecture</style></keyword><keyword><style  face="normal" font="default" size="100%">interoperable simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Modelling and Simulation</style></keyword><keyword><style  face="normal" font="default" size="100%">serious games  and gamification</style></keyword><keyword><style  face="normal" font="default" size="100%">training</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2022</style></year></dates><volume><style face="normal" font="default" size="100%">53</style></volume><pages><style face="normal" font="default" size="100%">255-272</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">ARESIBO, an EU H2020 funded project, aims to improve the efficiency of border surveillance systems by providing the operational teams and the tactical command and control levels with accurate and comprehensive information by means of augmented reality (AR). This article describes the training system, with gamified modules, that was designed and developed within the project to deliver training on the AR applications developed to operators in border security missions. The ARESIBO Training System is fed by a set of interoperable, distributed simulators (Simulation Engine) comprised of detailed landscapes, realistic assets, and end-user vetted border control scenarios. By generating virtual incidents and situations, the Training System creates realistic operational conditions in which to train and employ the ARESIBO AR devices. It also includes the front-end tools and interfaces for the trainer to setup and execute the training sessions, such as the Trainer Editor GUI. Additional gamified modules were developed to investigate the effectiveness of serious gaming for training; these modules work both on- and off-line and independently of each other to maximize the autonomy of the trainer. This work concludes with a description of the training scenario and training events.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><section><style face="normal" font="default" size="100%">255</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jeffrey A. Krinock</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Standards Integration in E-Learning, Simulations, and Technical Manuals</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">advanced distributed learning</style></keyword><keyword><style  face="normal" font="default" size="100%">High Level Architecture</style></keyword><keyword><style  face="normal" font="default" size="100%">Interactive Electronic Technical Manuals (IETMs)</style></keyword><keyword><style  face="normal" font="default" size="100%">S1000D</style></keyword><keyword><style  face="normal" font="default" size="100%">SCORM</style></keyword><keyword><style  face="normal" font="default" size="100%">SCORM-conformance</style></keyword><keyword><style  face="normal" font="default" size="100%">technical manuals</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2004</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">71-80</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Individually, three standards—the Sharable Content Object Reference Model (SCORM), the High Level Architecture (HLA), and S1000D—provide vital standardization to their respective areas of coverage. The SCORM provides standardization to e-learning content, HLA provides standardization to simulations, and S1000D to Interactive Electronic Technical Manuals (IETMs). Talks and Memorandums of Understanding (MOUs) are under way among the various groups responsible for these standards to find areas of overlap that might make good candidates for collaboration. For instance, recent collaboration between the Advanced Distributed Learning initiative (ADL) and the Defense Modeling and Simulation Office (DMSO) focused on finding ways to use the SCORM data model to assess and record performance within an HLA-based simulation. Similarly, ongoing research between ADL and the European Association of Aerospace Industries (AECMA) recently looked at ways to integrate SCORM-conformant training material into S1000D-based IETMs.
Beyond MOUs and general research and talks about collaboration, the standards bodies involved should consider undertaking collaborative projects that target actual operations and training needs. Solving real-world problems based on end-user needs and input can help illuminate portions of each standard that are the strongest candidates for joint and collaborative coverage.</style></abstract></record></records></xml>