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Social and Emotional Learning and Complex Skills Assessment

ADV ANLYTCS LRNG TCHNG: SOC EMTN LRNG CMPLX SKLLS ASSMT

Educational Technology

Education & Professional Development

Gt Product Group

Binding Format

Marketing Imprint Name

B2B GT

CL Carton Count

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B2B & B2C

<P>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).</P>

PROFESSIONAL & REFERENCE

Duration

Duration Unit Of Measure

Transaction Type

Front Cover.
Other Frontmatter.
Other Frontmatter.
Title Page.
Copyright Page.
Contents.
Contributors.
1: Re-contextualizing Inclusiveness &#x0026; SEL in Learning Analytics.
2: State of the Science on Social and Emotional Learning: Frameworks, Assessment, and Developing Skills.
3: Mapping the Landscape of Social and Emotional Learning Analytics.
4: Key SEL Attributes.
5: Empathy: How Can Technology Help Foster Its Increase Rather Than Decline in the 21st Century?.
6: The Role of Learning Analytics in Developing Creativity.
7: Using Learning Analytics to Measure Motivational and Affective Processes During Self-Regulated Learning with Advanced Learning Technologies.
8: SR-WMS: A Typology of Self-Regulation in Writing from Multiple Sources.
9: Identifying Tertiary Level Educators&#x2019; Needs and Understanding of the Collaboration Process Analytics.
10: Applications in K-12.
11: Augmented Reality (AR) for Biology Learning: A Quasi-Experiment Study with High School Students.
12: Struggling Readers Smiling on the Inside and Getting Correct Answers.
13: Exploring Selective College Attendance and Middle School Cognitive and Non-cognitive Factors Within Computer-Based Math Learning.
14: Applications in Adult and Professional Education.
15: Single-Case Learning Analytics to Support Social-Emotional Learning: The Case of Doctoral Education.
16: Investigating the Potential of AI-Based Social Matching Systems to Facilitate Social Interaction Among Online Learners.
17: Developing Social Interaction Metrics for an Active, Social, and Case-Based Online Learning Platform.
18: Network Climate Action Through MOOCs.
Index.

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Social and Emotional Learning and Complex Skills Assessment