Training volunteer firefighters in remote areas on major transport incidents, such as train derailments containing dangerous goods, is challenging on many levels. Even though these incidents are rare, their consequences can be damaging for local communities, the environment, and the transportation supply chain. A report (Transport Canada, 2015) indicates that firefighters are not adequately trained for large scale train incidents involving dangerous goods, that they do not have the necessary skills to use specialized equipment, and that small and remote communities have limited capacities to respond to these incidents. A main issue is that the training expertise is often located in urban areas, which suggests that a technology-based approach could offer an essential element to increase first respondents’ awareness, operation, and command knowledge and skills. In this respect, Virtual Reality (VR) offers a potential alternative to training methods such as web-based e-learning solutions, allowing for realistic and safe simulation of a wide range of dangerous fire scenarios. In addition, the capability to bring multiusers into a shared VR space enables team training, and remote instructor feedback and support. The paper reports on our progress in the development of a VR training environment where a novice first respondent is acquiring situational awareness of a train derailment while interacting with an intelligent tutoring system. The system is being developed with off-the-shelf and open source components including Oculus Rift S, Unity, and the Generalized Intelligent Framework for Tutoring (GIFT) (ARL-HRED, 2012). The paper also presents how the different elements of the adaptive instructional system are implemented in the GIFT architecture including the user interface, domain knowledge, learner, and pedagogical models.
Transport Canada. (2015). Emergency Response Task Force Second Quarterly Report and Recommendations. Retrieved February 24, 2020, from https://www.tc.gc.ca/media/documents/tdg-eng/ERTF_SECOND_QUARTERLY_REPORT_ENG-A.pdf
ARL-HRED. (2012). Generalized Intelligent Framework for Tutoring (GIFT). Retrieved February 24, 2020, from https://www.gifttutoring.org