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This chapter outlines potential steps to take in designing active learning experiences based on several theories underlying the learning process. The chapter examines theories of learning and instruction including information processing, schema acquisition, and cognitive load theory. Next follows an explanation of how these theories support problem-centered learning as well as a rationale for the need to help learners develop domain-general, flexible problem-solving skills that will transfer to future needs and contexts. The second half of the chapter focuses on designing active learning experiences based on the selection of real-world problems as the foundation for learning, activating prior knowledge, demonstration of the process or concept, multiple opportunities for practice with relevant scaffolding, and the chance to integrate that knowledge into the learners’ own context based on M. D. Merrill’s (2002) First Principles of Instruction. Examples of assessments, strategies, and activities to foster active, problem-centered learning drawn from the literature are also provided.

Cognitive Load Theory (CLT) is the product of over a decade of research in the instructional science domain (Chandler & Sweller, 1991; Sweller & Chandler, 1994), and its applications to other areas of inquiry continues to expand (see Cuevas, Fiore, & Oser, 2002; Paas, Renkl, & Sweller, 2003a; Paas, Tuovinen, Tabbers, & Van Gerven, 2003b; Scielzo, Fiore, Cuevas, & Salas, 2004). The core of CLT is based on two sets of what are termed cognitive load factors that are either endogenous or exogenous from the viewpoint of an operator interacting with the environment. Endogenous (or intrinsic) factors are sources of cognitive load in terms of the general amount and complexity of information with which the operator has to interact. In training environments, intrinsic load is directly proportional to the amount of materials that trainees need to acquire. As such, the more complex the information is in terms of volume and conceptual interactivity, the higher the cognitive load will be. In operational settings, high intrinsic load can occur whenever informational demands that need to be processed are high. Within the context of human–robot team environments, there is likely to be unique intrinsic load factors emerging from this hybrid teamwork interaction (e.g., information produced by synthetic team members). Another source of cognitive load comes from exogenous or extraneous factors. In training and operational settings alike, extraneous cognitive load may occur dependent upon the manner in which information needing attention is presented. Specifically, the more complex the human–robot team interface is in relation to the process by which information is displayed and/or communicated, the more extraneous cognitive load can be present. For example, the technological tools involved in the communication of information, and the associated modalities used to process information may inadvertently result in cognitive load. Simply put, high extraneous cognitive load can be produced as a result of using sub-optimal information presentation and communication. Overall, exogenous factors can stem from the added complexity of human–robot operations in terms of distinct command-and-control systems that emerge from using novel technology. Within such operations, it is particularly important to control sources of extraneous cognitive load that have been shown to produce two distinct negative effects on information processing – redundancy of information and split-attention. These have been shown to attenuate processing capacity thereby minimizing optimal information processing (e.g., Sweller, 1994; Mayer, 1999).

Organizations may fail to innovate because receivers exhibit bias against adopting creative ideas. This paper explores many motivational, cognitive, and affective factors that can cause receivers to hinder the creativity–innovation process. In particular, receivers may engage in motivated reasoning and skepticism against creative ideas, face barriers to recognizing creative value, and experience negative affect when receiving creative ideas. Each creative adoption decision point during the creativity–innovation process is an opportunity for bias to derail progress. This helps explain why innovation can be so difficult. Understanding the biases that hinder the creativity–innovation process allows individuals and organizations to take action to mitigate them.

This chapter overviews organizational neuroscience (ON), covering the past, present, and future of this growing field of inquiry. First, we define ON and clarify the boundaries of the field. Second, we describe the evolution of ON by starting with early papers that tended to discuss the potential of ON to benefit both research and practice. Throughout its development, debates have abounded about the value of ON. Such debates are often related to challenges in collecting, integrating, interpreting, and using information from the brain-level of analysis. It is time for the field to move beyond these debates to focus on applying neuroscience to further theory development and reveal more comprehensive answers to research questions of importance to both academics and practitioners. Third, we propose and describe future research directions for ON. The research directions that we propose are merely a sample of the many paths along which ON inquiry can move forward. Fourth, we outline potential practical implications of ON, including: training and development, job design, high-performance assessment, motivating communications, and conflict prevention. Finally, we draw conclusions about ON as it stands today, address challenges in developing ON, and point out opportunities. We conclude with takeaways and highlight the importance of ON for both academics and practitioners.

Teams in extreme and disruptive contexts face unique challenges that can undermine coordination and decision-making. In this study, we evaluated how affective differences between team members and team process norms affected the team's decision-making effectiveness.

Teams were placed in a survival simulation where they evaluated how best to maximize the team's survival prospects given scarce resources. We incorporated multisource and multirater (i.e., team, observer, and archival) data to ascertain the impacts of affect asymmetry and team process norms on decision-making effectiveness.

Results suggest that teams with low positive affect asymmetry and low process norms generate the most effective decisions. The least effective team decision performance occurred in teams characterized by high variance in team positive affectivity (high positive affect asymmetry) and low process norms. We found no similar effect for teams with high process norms and no effect for negative affect asymmetry, however, irrespective of team process norms.

These findings support the affect infusion model and extend cognitive resource theory, by highlighting how affect infusion processes and situational constraints influence team decision-making in extreme and disruptive contexts.

Multiple intelligence, cognitive thinking, and sensory theories provide the framework for understanding how to improve learning and learning environments for students. Research involving the use of a multimodal video game to enhance student learning is discussed. It is proposed in the chapter that multimodal and multiplayer video games make use of sensory-rich interactions to engage users, create meaningful experiences, and often facilitate communication between people located all over the world. Multiple learning theories are addressed and evaluated in order to bring to light issues and areas for investigation when designing technology-rich learning environments. Implications of the findings in relation to connections with gaming technologies, capacity for community building, and next steps for investigating ideal designs for 21st century learning environments are discussed.

With growing interest in the uses of hedonic technologies and gamification in system design, the concept of cognitive absorption (CA) has become increasingly salient in the information systems literature. However, little effort has been made to evaluate the research status and consolidate the current literature findings. To fill these research gaps, the authors conducted a literature review on CA. The authors then proposed an integrative framework that summarises the key elements of and variables related to CA and their relationships. The major findings of the study are discussed, and an agenda for future research is proposed.

This chapter provides an overview of two generally applicable frameworks relating to the use of technology-enhanced learning – ‘affordances’ and multimedia learning effects. First, the concept of ‘affordances’ as action potentials of technologies is identified as a way to think through technology-enhanced learning design possibilities, so as to help make technology selection decisions. Second, multimedia learning effects including the multimedia effect, the modality effect, the redundancy effect, the split-attention effect, and the personalization effect are presented as a scientific basis for understanding how to create cognitively effective learning experiences using text, images, sound, and video. Both affordances and multimedia learning effects are characterized as ongoing areas of research that are somewhat related, with the successful utilization of each depending on critical application by the designer.