Cognitive Load Measurement and Application provides up-to-date research and theory on the functional role of cognitive load measurement and its application in multimedia and visual learning. Grounded in a sound theoretical framework, this edited volume introduces methodologies and strategies that effect high-quality cognitive load measurement in learning. Case studies are provided to aid readers in comprehension and application within various learning situations, and the book concludes with a review of the possible future directions of the discipline.

This book explores robust multimodal cognitive load measurement with physiological and behavioural modalities, which involve the eye, Galvanic Skin Response, speech, language, pen input, mouse movement and multimodality fusions. Factors including stress, trust, and environmental factors such as illumination are discussed regarding their implications for cognitive load measurement. Furthermore, dynamic workload adjustment and real-time cognitive load measurement with data streaming are presented in order to make cognitive load measurement accessible by more widespread applications and users. Finally, application examples are reviewed demonstrating the feasibility of multimodal cognitive load measurement in practical applications. This is the first book of its kind to systematically introduce various computational methods for automatic and real-time cognitive load measurement and by doing so moves the practical application of cognitive load measurement from the domain of the computer scientist and psychologist to more general end-users, ready for widespread implementation. Robust Multimodal Cognitive Load Measurement is intended for researchers and practitioners involved with cognitive load studies and communities within the computer, cognitive, and social sciences. The book will especially benefit researchers in areas like behaviour analysis, social analytics, human-computer interaction (HCI), intelligent information processing, and decision support systems.

Cognitive load theory (CLT) is one of the most important theories in educational psychology, a highly effective guide for the design of multimedia and other learning materials. This edited volume brings together the most prolific researchers from around the world who study various aspects of cognitive load to discuss its current theoretical as well as practical issues. The book is divided into three parts. The first part describes the theoretical foundations and assumptions of CLT, the second discusses the empirical findings about the application of CLT to the design of learning environments, and the third part concludes the book with discussions and suggestions for new directions for future research. It aims to become the standard handbook in CLT for researchers and graduate students in psychology, education, and educational technology.

Proposes computational models of human memory and learning using a brain-computer interfacing (BCI) approach Human memory modeling is important from two perspectives. First, the precise fitting of the model to an individual's short-term or working memory may help in predicting memory performance of the subject in future. Second, memory models provide a biological insight to the encoding and recall mechanisms undertaken by the neurons present in active brain lobes, participating in the memorization process. This book models human memory from a cognitive standpoint by utilizing brain activations acquired from the cortex by electroencephalographic (EEG) and functional near-infrared-spectroscopic (f-NIRs) means. Cognitive Modeling of Human Memory and Learning A Non-invasive Brain-Computer Interfacing Approach begins with an overview of the early models of memory. The authors then propose a simplistic model of Working Memory (WM) built with fuzzy Hebbian learning. A second perspective of memory models is concerned with Short-Term Memory (STM)-modeling in the context of 2-dimensional object-shape reconstruction from visually examined memorized instances. A third model assesses the subjective motor learning skill in driving from erroneous motor actions. Other models introduce a novel strategy of designing a two-layered deep Long Short-Term Memory (LSTM) classifier network and also deal with cognitive load assessment in motor learning tasks associated with driving. The book ends with concluding remarks based on principles and experimental results acquired in previous chapters. Examines the scope of computational models of memory and learning with special emphasis on classification of memory tasks by deep learning-based models Proposes two algorithms of type-2 fuzzy reasoning: Interval Type-2 fuzzy reasoning (IT2FR) and General Type-2 Fuzzy Sets (GT2FS) Considers three classes of cognitive loads in the motor learning tasks for driving learners Cognitive Modeling of Human Memory and Learning A Non-invasive Brain-Computer Interfacing Approach will appeal to researchers in cognitive neuro-science and human/brain-computer interfaces. It is also beneficial to graduate students of computer science/electrical/electronic engineering.

This book examines the human factors issues associated with the development, testing, and implementation of helmet-mounted display technology in the 21st Century Land Warrior System. Because the framework of analysis is soldier performance with the system in the full range of environments and missions, the book discusses both the military context and the characteristics of the infantry soldiers who will use the system. The major issues covered include the positive and negative effects of such a display on the local and global situation awareness of the individual soldier, an analysis of the visual and psychomotor factors associated with each design feature, design considerations for auditory displays, and physical sources of stress and the implications of the display for affecting the soldier's workload. The book proposes an innovative approach to research and testing based on a three-stage strategy that begins in the laboratory, moves to controlled field studies, and culminates in operational testing.