Social and Emotional Learning and Complex Skills Assessment - An Inclusive Learning Analytics Perspective (Hardcover, 1st ed. 2022)

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. What makes the position of learning analytics pivotal in this endeavor to redefine measurement of SEL skills are 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 in face-to-face or online context) not being captured in traditional educational settings. Novel insights provided in the book span across diverse types of learning contexts and learner populations. Specifically, the book addresses relevant and emerging theories and frameworks (in various disciplines such as education, psychology, or workforce) that inform assessments of SEL skills and competencies. In so doing, the book maps the landscape of the novel learning analytics methods and approaches, along with their application in the SEL assessment for K-12 learners as well as adult learners. Critical to the notion of the SEL assessment are data sources. In that sense, 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 that are being 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).

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Advances in Analytics for Learning and Teaching
Release date:	August 2022
First published:	2022
Editors:	Yuan 'Elle' Wang • Srecko Joksimovic • Maria Ofelia Z. San Pedro • Jason D. Way • John Whitmer
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	335
Edition:	1st ed. 2022
ISBN-13:	978-3-03-106332-9
Categories:	Books > Social sciences > Education > Educational resources & technology > General Books > Computing & IT > Applications of computing > Databases > Data mining
LSN:	3-03-106332-5
Barcode:	9783031063329

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