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Technology for training military teams has evolved through a convergence of advances in simulation technology for individual and collective training, methods for analyzing teamwork and designing training solutions, and intelligent tutoring technologies that adapt training to the student, to accelerate learning. A number of factors have slowed this evolution toward intelligent team tutoring systems (ITTS), including the challenges of processing communications data, which are the currency of teamwork, and the paucity of automated and generalizable measures of team work. Several systems fulfill a subset of the features required of an ITTS, namely the use of team training objectives, teamwork models, measures of teamwork, diagnostic capability, instructional strategies, and adaptation of training to team needs. We describe these systems: the Advanced Embedded Training System (AETS), Synthetic Cognition for Operational Team Training (SCOTT), the AWO Trainer, the Benchmarked Experiential System for Training (BEST), and the Cross-Platform Mission Visualization Tool. We close this chapter with recommendations for future research.

Fostered by technological developments and globalization, culturally diverse teams are becoming a mainstay of organizational strategy. As the use of multi-cultural teams continues to increase, it becomes paramount to understand the mechanism(s) by which leaders can promote effectiveness within these teams. Despite this need, there are numerous challenges facing those who seek to understand these phenomena and move science and practice forward. The purpose of this chapter is to present a few of these challenges and approaches which can assist in mitigating these challenges. Finally, we identify what we see as key research needs within this area.

Teams focus on a common and valued goal, and effective teams are able to alter their behaviors in pursuit of this goal. When teams are viewed in the context of a dynamic environment, they must adapt to challenges in the environment in order to maintain team effectiveness. In this light, we describe various sources of team variation and how they combine with individual-level, team-level, and dynamical mechanisms for maintaining team effectiveness in a dynamic environment. The combination of these elements produces a systems view of team effectiveness. Our goals are to begin to define, both in words and in operational terms, team effectiveness from this perspective and to evaluate this definition in the context of team training using intelligent tutoring systems (team ITS). In addressing these goals, we present an example of real-time analysis of team effectiveness and some challenges for team ITS training based on a dynamical systems view of team effectiveness.

Health-care professionals undergo numerous training programs each year in order to fulfill licensure requirements and organizational obligations. However, evidence suggests that a substantial amount of what is taught during training is never learned or transferred back to routine work. A major contributor to this issue is low training motivation. Prior conceptual models on training transfer in the organizational sciences literature consider this deficit, yet do not account for the unique conditions of the hospital setting. This chapter seeks to close this gap by adapting conceptual models of training transfer to this setting that are grounded in organizational science. Based on theory and supplemented by semistructured key informant interviews (i.e., organizational leaders and program directors), we introduce an applied model of training motivation to facilitate training transfer in the hospital setting. In this model, training needs analysis is positioned as a key antecedent to ensure support for training, relevant content, and perceived utility of training. We posit that these factors, along with training design and logistics, enhance training motivation in hospital environments. Further, we suggest that training motivation subsequently impacts learning and transfer, with elements of the work environment also serving as moderators of the learning-transfer relationship. Factors such as external support for training content (e.g., from accrediting bodies) and allocation of time for training are emphasized as facilitators. The proposed model suggests there are factors unique to the hospital work setting that impact training motivation and transfer that should be considered when developing and implementing training initiatives in this setting.

Technology is changing more rapidly than most companies can implement it. This chapter presents a digitized Human Resource Development (dHRD) Framework Model that organizational leaders can use to meet the needs of current and future workforces via avatar-mediated learning in 3D virtual learning environments (VLEs). The dHRD Framework Model leverages 3D VLE technology as a tool to engage employees and achieve strategic objectives in an efficient and cost-effective manner for managing people. The dHRD Framework Model can inform practice and advance employee engagement outcomes for effective HR decision-making, which includes legal and ethical considerations for mitigating risks in the 3D VLE. The Theory of Gamification, including psychological theories, provides the lens to explain dynamic learning and relationship building using the dHRD Framework Model to engage employees in the 3D VLE.

Team cognition research continues to evolve as the need for understanding and improving complex problem solving itself grows. Complex problem solving requires members to engage in a number of complicated collaborative processes to generate solutions. This chapter illustrates how the Macrocognition in Teams model, developed to guide research on these processes, can be utilized to propose how intelligent tutoring systems (ITSs) could be developed to train collaborative problem solving. Metacognitive prompting, based upon macrocognitive processes, was offered as an intervention to scaffold learning these complex processes. Our objective is to provide a theoretically grounded approach for linking intelligent tutoring research and development with team cognition. In this way, team members are more likely to learn how to identify and integrate relevant knowledge, as well as plan, monitor, and reflect on their problem-solving performance as it evolves. We argue that ITSs that utilize metacognitive prompting that promotes team planning during the preparation stage, team knowledge building during the execution stage, and team reflexivity and team knowledge sharing interventions during the reflection stage can improve collaborative problem solving.

Adaptive capacity has commonly been defined as the “general ability of institutions, systems, and individuals to adjust to potential damage, to take advantage of opportunities, or to cope with the consequences” (http://www.greenfacts.org). Adaptive capacity is herein described as the ability to facilitate the process of adaptive team performance and the resulting outcome of team adaptation (see Stagl, Burke, Salas, & Pierce, this volume). More specifically, although often spoken of with regard to environmental and global changes, it is spoken of here with regard to the ability of individuals (and correspondingly teams) to recognize and understand contextual changes, dynamically revise and implement plans accordingly, and learn from each implementation so as to be better prepared in the future.

Intercultural interactions, in domains such as civil aviation and international peacekeeping, expand awareness of national differences in cognition. At the same time, experience with national differences in natural settings provides a more complex picture of cognition. The Cultural Lens Model captures the nature and origin of the cognitive differences. This paper reviews cognitive dimensions that vary over national groups. It uses the Cultural Lens Model to describe the implications of these cognitive differences for five intercultural challenges: problem definition, planning, coordination, prediction, and training. Finally, the paper suggests mechanisms for increasing international effectiveness in the face of cognitive differences.

Team errors may be relatively costly, particularly in fields such as medicine and the military, where poor outcome may very well lead to loss of life. By contrast, exceptional team performance – an apparently mundane, smooth flow of events – may barely capture the notice of any but the most astute observer. The question that naturally follows is: What specific factors and variables can be used to distinguish or predict effective (versus ineffective) team performance?