Simulations, games, and real or virtual apprenticeships are the kinds of context-rich learning environments that leverage the power of episodic memory, boost student motivation, and create the conditions that make learning transfer more likely. Context-rich learning embodies the answer to the question, “Why do we need to learn this?” Many students, especially those who have dyslexia or otherwise neurodivergent brains, require the kind of context that is lacking in education. Designing Cont...

As artificial intelligence becomes embedded in everything from healthcare diagnostics to financial systems and autonomous vehicles, the stakes for AI security have never been higher. Adversarial AI Threat Response and Secure Model Design is your essential guide to understanding, defending against, and designing resilient machine learning systems in the face of growing adversarial threats.Written by a leading expert in AI security and policy, this book delivers a combinatio...

This book explores the transformative role of artificial intelligence in educational assessment, catering to researchers, educators, administrators, policymakers, and technologists involved in shaping the future of education. It delves into the foundations of AI-assisted assessment, innovative question types and formats, data analysis techniques, and the practical implementation of AI tools in various educational settings. The book addresses the pressing need for more efficient, personaliz...

Agent technologies and multi-agent systems is an emerging field of study that is unique in the sense that all efforts to build this discipline unite knowledge from different areas of study. Developments in Intelligent Agent Technologies and Multi-Agent Systems: Concepts and Applications discusses research on emerging technologies and systems based on agent and multi-agent paradigms across various fields of science, engineering and technology. This book is a collection of work that covers c...

Research in the domains of learning analytics and educational data mining has prototyped an approach where methodologies from data science and machine learning are used to gain insights into the learning process by using large amounts of data. As many training and academic institutions are maturing in their data-driven decision making, useful, scalable, and interesting trends are emerging. Organizations can benefit from sharing information on those efforts. Applying Data Science and Learni...

In the modern data-driven era, artificial intelligence (AI) and machine learning (ML) technologies that allow a computer to mimic intelligent human behavior are essential for organizations to achieve business excellence and assist organizations in extracting useful information from raw data. AI and ML have existed for decades, but in the age of big data, this sort of analysis is in higher demand than ever, especially for customer support and analytics. The Handbook of Research on AI and Ma...

The ego-net approach to social network analysis, which takes discrete individual actors and their contacts as its starting point, is one of the most widely used approaches in the field. This is the first textbook to take readers through each stage of ego-net research, from conception, through research design and data gathering to analysis.It starts with the basics, assuming no prior knowledge of social network analysis, but then moves on to introduce cutting edge innovations, cover...

An introduction to statistical data mining, Data Analysis and Data Mining is both textbook and professional resource. Assuming only a basic knowledge of statistical reasoning, it presents core concepts in data mining and exploratory statistical models to students and professional statisticians-both those working in communications and those working in a technological or scientific capacity-who have a limited knowledge of data mining. This book presents key statistical concepts by w...

Exponential random graph models (ERGMs) are increasingly applied to observed network data and are central to understanding social structure and network processes. The chapters in this edited volume provide a self-contained, exhaustive account of the theoretical and methodological underpinnings of ERGMs, including models for univariate, multivariate, bipartite, longitudinal and social-influence type ERGMs. Each method is applied in individual case studies illustrating how social science the...

This accessible, practice-oriented and compact text provides a hands-on introduction to the principles of market research. Using the market research process as a framework, the authors explain how to collect and describe the necessary data and present the most important and frequently used quantitative analysis techniques, such as ANOVA, regression analysis, factor analysis, and cluster analysis. An explanation is provided of the theoretical choices a market researcher has to make with reg...

"Covers a broad range of subjects that undergraduates in the discipline should be familiar and comfortable with upon graduation. From chapters on the scientific method and fundamental research concepts, to experimental design, sampling and statistical analysis, the text offers an excellent introduction to the key concepts of geographical research. The content is applicable for students at the beginning of their studies right through to planning and conducting dissertations. The book has al...

Human-Computer Interaction: An Empirical Research Perspective is the definitive guide to empirical research in HCI. The book begins with foundational topics including historical context, the human factor, interaction elements, and the fundamentals of science and research. From there, you'll progress to learning about the methods for conducting an experiment to evaluate a new computer interface or interaction technique. There are detailed discussions and how-to analyses on models of interac...