Search results

Purpose
This paper aims to use a data-driven approach to identify the factors and metrics that provide the best indicators of academic attrition in the Korean language program at the Defense Language Institute Foreign Language Center.


Design methodology approach
This research develops logistic regression models to aid in the identification of at-risk students in the Defense Language Institute's Korean language school.


Findings
The results from this research demonstrates that this methodology can detect significant factors and metrics that identify students at-risk. Additionally, this research shows that school policy changes can be detected using logistic regression models and stepwise regression.


Originality value
This research represents a real-world application of logistic regression modeling methods applied to the problem of identifying at-risk students for the purpose of academic intervention or other negative outcomes. By using logistic regression, the authors are able to gain a greater understanding of the problem and identify statistically significant predictors of student attrition that they believe can be converted into meaningful policy change.

The representation of violent extremist networks (VENs) and their behaviors within social simulation is required in order to leverage models and simulations for use to attack the networks course of action analysis. VENs appear throughout the world in multiple forms with varying objectives and behaviors. They exist as a subset of society, nested within and leveraging the underlying social network of a culture to further their own ends. The interdiction of these networks to presents a challenging task for law enforcement and military organizations due to their ability to change and adapt to the situation at hand. The use of social simulation with VEN representations and designed simulation experiments can provide decision makers with insights into the potential impact of their action to attack the threat network to include the likely manner in which the VEN might adapt to counter the attack. This paper discusses the requirements to represent VENs within simultions,provides an overview of the current VEN representationwithin the Current Geography model, and provides a case study analysis of the use of social simulations for the explporation of posssible futures in support of course of action analysis.

Purpose
This research develops a data-driven statistical model capable of predicting a US Army Reserve (USAR) unit staffing levels based on unit location demographics. This model provides decision makers an assessment of a proposed station location's ability to support a unit's personnel requirements from the local population.


Design/methodology/approach
This research first develops an allocation method to overcome challenges caused by overlapping unit boundaries to prevent over-counting the population. Once populations are accurately allocated to each location, we then then develop and compare the performance of statistical models to estimate a location's likelihood of meeting staffing requirements.


Findings
This research finds that local demographic factors prove essential to a location's ability to meet staffing requirements. We recommend that the USAR and US Army Recruiting Command (USAREC) use the logistic regression model developed here to support USAR unit stationing decisions; this should improve the ability of units to achieve required staffing levels.


Originality/value
This research meets a direct request from the USAREC, in conjunction with the USAR, for assistance in developing models to aid decision makers during the unit stationing process.

Purpose
Current Army doctrine stresses a need for military leaders to have the capability to make flexible and adaptive decisions based on a future unknown environment, location and enemy. To assess a military decision maker's ability in this context, this paper aims to modify the Wisconsin Card Sorting Test which assesses cognitive flexibility, into a military relevant map task. Thirty-four military officers from all service branches completed the map task.


Design/methodology/approach
The purpose of this study was to modify a current psychological task that measures cognitive flexibility into a military relevant task that includes the challenge of overcoming experiential bias, and understand underlying causes of individual variability in the decision-making and cognitive flexibility behavior of active duty military officers on this task.


Findings
Results indicated that non-perseverative errors were a strong predictor of cognitive flexibility performance on the map task. Decomposition of non-perseverative error into efficient errors and random errors revealed that participants who did not complete the map task changed their sorting strategy too soon within a series, resulting in a high quantity of random errors.


Originality/value
This study serves as the first step in customizing cognitive psychological tests for a military purpose and understanding why some military participants show poor cognitive flexibility.

The article of record as published may be found at http://dx.doi.org/10.1108/JDAL-05-2017-0007 ; Purpose Current Army doctrine stresses a need for military leaders to have the capability to make flexible and adaptive decisions based on a future unknown environment, location and enemy. To assess a military decision maker's ability in this context, this paper aims to modify the Wisconsin Card Sorting Test which assesses cognitive flexibility, into a military relevant map task. Thirty-four military officers from all service branches completed the map task. Design/methodology/approach The purpose of this study was to modify a current psychological task that measures cognitive flexibility into a military relevant task that includes the challenge of overcoming experiential bias, and understand underlying causes of individual variability in the decision-making and cognitive flexibility behavior of active duty military officers on this task. Findings Results indicated that non-perseverative errors were a strong predictor of cognitive flexibility performance on the map task. Decomposition of non-perseverative error into efficient errors and random errors revealed that participants who did not complete the map task changed their sorting strategy too soon within a series, resulting in a high quantity of random errors. Originality/value This study serves as the first step in customizing cognitive psychological tests for a military purpose and understanding why some military participants show poor cognitive flexibility.

The article of record as published may be found at http://dx.doi.org/10.1037/mil0000080 ; One key component of optimal military decision making is that the decision maker demonstrates reinforcement learning. The modification of psychological tasks gives insight into understanding how to effectively train military decision makers and how experienced decision makers arrive at optimal or near optimal decisions. We developed a task modeled after the Iowa Gambling Task (IGT) to measure military decision making performance. This new task focuses on high stakes and uncertain environments particular to military decision making conditions. Thirty-four U.S. military officers from all branches of service completed the tasks yielding decision data for validation. The new task retains essential characteristics of the founda- tional task and gives insight into reinforcement learning of military decision makers. Results indicate that the additional metric of regret defines higher perfor- mance at a trial-by-trial level, and clustering by multiple metrics defines high performance groups.

Based on information gathered from the United States armed services, the Royal Navy and the Australian Defence Force, best practices in corporate America, and the academic literature, this report provides forward leaning practices and actionable recommendations to Commander, Navy Recruiting Command (CNRC). The goal is to improve and best align Navy Recruiting practices for the Millennial and post-Millennial generations. To achieve this, we: (1) identified and evaluated past alternative recruiting efforts, (2) assessed the literature on trends in the Millennial and post-Millennial generations, and (3) synthesized this information to pose future Navy recruiting strategies. Ultimately, this report concludes that the military recruiting community must establish a program of research and experimentation in order to learn how to improve military recruiting. ; Navy Recruiting Command ; OPNAV N1 ; Approved for public release; distribution is unlimited.

from Scythe : Proceedings and Bulletin of the International Data Farming Community, Issue 6 Workshop 18 ; Armed forces across the globe are conducting stability operations to establish enduring political systems in former crisis regions. A goal of stability operations is to influence civilian attitudes in favor of the host nation (HN) government and the stabilization forces. To better understand the dynamics of civilian attitudes, experts have developed analytic models to represent civilian behaviors and reactions to changes in the cultural and societal landscape. Further research is required to integrate concepts from various analytic models to explore the complexity of civilian behaviors. Our team's goal for IDFW 15 was to develop rudimentary agent-based simulation models of civilian behaviors that integrate concepts from selected analytic models.

from Scythe : Proceedings and Bulletin of the International Data Farming Community, Issue 2 Workshop 14 ; The U.S. Army is undertaking its most significant transformation in decades. Leveraging new technologies, the evolving Future Force is characterized by a lighter, more agile, soldier centric force. The military operations research community is working on ways to better analyze soldier capabilities and systems of systems. This team will explore the use of IWARS in a high performance computing environment, building on previous and ongoing work done at TRAC-MTYRY and NPS. The team will build appropriate squad and platoon level scenarios and designs of experiments to examine a variety of issues of interest to the FFW program. The results of this analysis will impact ongoing testing during the current fiscal year.

This research aims to gain insight into optimal wargaming decision-making mechanisms using neurophysiological measures by investigating whether brain activation and visual scan patterns predict attention, perception, and/or decision-making errors through human-in-the-loop wargaming simulation experiments. We investigate whether brain activity and visual scan patterns can explain optimal wargaming decision making and its development with a within-person design; i.e., the transition from exploring the environment to exploiting the environment. We describe ongoing research that uses neurophysiological predictors in two military decision making tasks that tap reinforcement learning and cognitive flexibility. ; Army Research Office (ARO), PO Box 1221, Research ; Approved for public release; distribution is unlimited.