Computer-based collaborative training for transportation security and emergency response

Velásquez, Juan D.; Yoon, Sang Won; Nof, Shimon Y.

doi:10.1016/j.compind.2009.12.007

Cited by 17 publications

(11 citation statements)

References 18 publications

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“…The first case discusses computer-based collaborative eTraining for enhancing security awareness, alertness, and emergency responsiveness in the State Departments of Transportation (DOT) (Velasquez et al, 2010). The second case introduces an e-Training program for manufacturing managers based on kaizen (continuous improvement) knowhow in Japanese manufacturing industry (Ishii and Tamaki, 2009).…”

Section: Collaborative E-training Design and Applicationsmentioning

confidence: 98%

“…It receives all the decisions and actions made by each team and combines the emergency events, decisions, and actions together, and transmits them to the CBCT clients after streamlining the information. This global view provides the system with some experiential learning since each team can observe the performance of other teams and learn from their actions and decisions (Velasquez et al, 2010). On the CBCT client side, the participants have multiple-function windows for decision-making and access to decision support system tools ( Figure 10.14).…”

Section: Collaborative E-training In State Dotsmentioning

confidence: 99%

“…A Computer-Based Collaborative Training (CBCT) prototype is designed for the Indiana Department of Transportation (INDOT) for better preparation of their staff on emergency response in a safe, low-cost environment (Velasquez et al, 2010). The CBCT prototype functions are identified using field observations and interviews with members from both INDOT Operation and Research Department and the Indiana Department of Homeland Security.…”

Section: Collaborative E-training In State Dotsmentioning

confidence: 99%

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e-Learning and e-Training

Nof

Ceroni

Jeong

et al. 2015

Automation, Collaboration, &Amp; E-Services

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Abstract. Advances in ICT (Information and Communication Technologies), automation, and collaboration engineering have significantly revolutionized education and training over the past decades. The distributed and ubiquitous nature of Internet-based education and training, as remarkable instances of e-Service (Chapter 9), has transformed the emphasis of conventional education and training systems, from the transmission and acquisition to creation of knowledge, leading to further customized education and training. The emerging education and training systems are then more learner-oriented than instructororiented, i.e., concentrating more on the learning than the education aspect. The ever-increasing needs for knowledge update due to rapid advances in technology, the rising demand for postgraduate/continuing professional education of working adults, and limited capacities of educational institutions, along with high expenses of traditional education further justify the need for emerging e-Learning and e-Training systems. A major benefit of e-Learning and e-Training is the participative and collaborative infrastructure, as well as enabling engineered CCT aspects and functions of the learning process itself; just as in formation transfer in Internet 1.0 was mostly one-directional (from providers to users), Internet 2.0 enables bi-directional and multi-directional interaction and collaboration.

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Section: Collaborative E-training Design and Applicationsmentioning

confidence: 98%

Section: Collaborative E-training In State Dotsmentioning

confidence: 99%

Section: Collaborative E-training In State Dotsmentioning

confidence: 99%

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e-Learning and e-Training

Nof

Ceroni

Jeong

et al. 2015

Automation, Collaboration, &Amp; E-Services

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“…Computerized decision training approaches involve immersive virtual reality scenarios [25] [26], which put the player into a realistically modelled situation or agent-based approaches, which aim to model co-player behaviour [27]. While these developments deliver single user games, first prototypes have been successfully created towards decision training using collaborative games [11] and multi-user mixed-reality scenarios [12]. While at first sight the latter looks similar to the approach reported here, it does not rely on a re-usable platform for serious games.…”

Section: Related Workmentioning

confidence: 99%

“…Multi-stakeholder decision situations confronted with time restrictions and incomplete information such as emergencies have been recognised as a relevant field for specific training approaches involving tabletop exercises [9] or (non-computerized) tactical decision training games [10]. 2 First prototypes towards the use of collaborative computer games are also reported [11] [12]. The systematic use of game platforms is still in its infancies.…”

Section: Introductionmentioning

confidence: 99%

Immersive Multi-user Decision Training Games with ARLearn

Klemke

Ternier

Kalz

et al. 2014

Open Learning and Teaching in Educational Communities

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Abstract. Serious gaming approaches so far focus mainly on skill development, motivational aspects or providing immersive learning situations. Little work has been reported to foster awareness and decision competencies in complex decision situations involving incomplete information and multiple stakeholders. We address this issue exploring the technical requirements and possibilities to design games for such situations in three case studies: a hostage taking situation, a multi-stakeholder logistics case, and a health-care related emergency case. To implement the games, we use a multi-user enabled mobile game development platform (ARLearn). We describe the underlying real world situations and educational challenges and analyse how these are reflected in the ARLearn games realized. Based on these cases we propose a way to increase the immersiveness of mobile learning games.

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Development of an educational virtual reality training system for marine engineers

Shen

Zhang

Bai

et al. 2019

Comp Applic In Engineering

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In this study, an educational virtual reality training system named “DMS‐VLCC3D” has been developed to help students or marine engineers learn the working principle of the marine engineering system and improve their ability of practical operation in a more efficient and vivid way. During the stage of establishing the geometric model of the virtual marine engine room, optimization methods including instantiation modeling, functional nodes optimization, level of detail, and texture mapping optimization are adopted to improve the fluency of the virtual marine engine room and the loading speed of geometric model resource. Reasonable human‐machine interactive mechanism is designed to promote the development efficiency and simulation efficiency. Several auxiliary learning and training tools are designed to make the DMS‐VLCC3D become a self‐learning and training platform for the trainees. Additionally, to fit different training purposes, the system provides three training mode: standalone and multi‐user collaborative training and evaluation. At last, 60 seniors majored in marine engineering from Dalian Maritime University are selected to carry out an assessment experiment to study the learning effectiveness of DMS‐VLCC3D, which shows a promising result. This training system is currently used to train thousands of students majored in marine engineering in about 20 maritime universities in China.

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Computer-based collaborative training for transportation security and emergency response

Cited by 17 publications

References 18 publications

e-Learning and e-Training

e-Learning and e-Training

Immersive Multi-user Decision Training Games with ARLearn

Development of an educational virtual reality training system for marine engineers

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