In this book, we primarily focus on studies that provide objective, unobtrusive, and innovative measures (e.g., indirect measures, content analysis, or analysis of trace data) of SEL skills (e.g., collaboration, creativity, persistence), relying primarily on learning analytics methods and approaches that would potentially allow for expanding the assessment of SEL skills and competencies at scale. Learning analytics are pivotal in this endeavor to redefine measurement of SEL skills because of constant changes and advancements in learning environments and the quality and quantity of data collected about learners and the process of learning. Contemporary learning environments that utilize virtual and augmented reality to enhance learning opportunities accommodate for designing tasks and activities that allow learners to elicit behaviors (either face-to-face or online) not being captured in traditional educational settings. Novel insights in this book span across diverse types of learning contexts and learner populations. It addresses relevant and emerging theories and frameworks (in disciplines such as education, psychology, or workforce) that inform assessments of SEL skills and competencies, and maps the landscape of the novel learning analytics methods and approaches, along with their application in the SEL assessment for K-12 and adult learners. Critical to the SEL assessment are data sources, and the book outlines where and how data related to learners' 21st century skills and competencies can be measured and collected. Linking theory to data, the book further discusses tools and methods used to operationalize SEL and link relevant skills and competencies with cognitive assessment. Finally, the book addresses aspects of generalizability and applicability, showing promising approaches for translating research findings into actionable insights that would inform various stakeholders (e.g., learners, instructors, administrators, policy makers).