While traditional training methods have remained mostly unchanged, training needs continue to grow in complexity. Currently, training methods are simply not meeting the needs of military agencies. As such, the Department of Defense (DoD) has looked to industry and academia for training solutions that incorporate new technological advancements to achieve high velocity training and improve training effectiveness.
In fact, the Army Research Lab recently issued a call for whitepapers to industry, seeking input on data and automation capabilities to improve its current Synthetic Training Environment. The request looks specifically at artificial intelligence (AI) capabilities, data analytics, machine learning, augmented reality, and distributed computing for simulated training.
With the military training industry beginning to embrace these new technologies to improve training effectiveness, we sat down with Amy Dideriksen, a Lead Researcher with Mission Systems Advanced Technologies at Collins Aerospace, to get more insights. Dideriksen is an expert in the training industry, playing an active role in collaborating with DoD, industry, and academia to remain current in the fast-changing training environment and customer needs.
Modern Military Training (MMT) Editors: How do you envision data analytics capabilities affecting the future of training?
Amy Dideriksen, a Lead Researcher with Mission Systems Advanced Technologies at Collins Aerospace
Amy Dideriksen: Data analytics has produced many successes with machine learning and deep learning technologies in other industries, such as finance, advertising, and robotics. There is a lot of hype around AI and how it can be applied to the training industry. One of the popular applications frequently discussed is adaptive learning systems to enhance training. By using formative assessment techniques, instructors can assess student performance throughout the training exercise, and personalize the learning progression to meet the needs of the student.
MMT Editors: How are other industries using data analytics capabilities today and what can the military training industry learn from them?
Dideriksen: There are lessons to be learned from other industries that leverage data analytics capabilities. One specific lesson comes from the healthcare industry in their recommendation of the 5 rights model for clinical decision support (CDS); the right information, the right person, the right CDS intervention format, through the right channel and at the right time in workflow (American Health Information Management Association). As the military training industry designs an adaptive learning system, this same model must be applied. First, we must understand the information we are seeking, have the right data set, and the right resources in place, with the right channel in the right workflow.
Jumping onto the AI hype bandwagon without understanding the outcome you wish to see, or the data that you have available, will impact the success of the solution.
MMT Editors: How do you see the military training industry evolving with respect to leveraging data analytics capabilities?
Dideriksen: Many researchers in the industry are focused on overcoming the challenges of implementing machine learning and deep learning techniques, such as the need for access to large amounts of data, and how to mitigate that need. Other researchers are focused on analyzing the data and which algorithm will solve the desired problem. At the same time, industry is trying to provide solutions, the Advanced Distributed Learning Initiative is working to establish a Total Learning Architecture including a framework of specifications, standards and technical guidelines for enabling interoperability.
It’s also important not to overlook the cultural implications. Society will need to accept this new technology and trust that it can support existing processes and performance improvement to have a successful implementation into operations.
Yet, with so many researchers working on how to integrate AI into training solutions, I have no doubt that we’ll get there.
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