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Social and Emotional Learning and Complex Skills Assessment

An Inclusive Learning Analytics Perspective
Langbeschreibung
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.
Inhaltsverzeichnis
Re-contextualizing inclusiveness & SEL in Learning Analytics.- State of the science on social and emotional learning: Frameworks, assessment, and developing Skills.- Mapping the landscape of social and emotional learning analytics.- Empathy: Is Technology Strengthening or Fostering its Decline in the 21st Century?.- Creativity and Industry 4.0.- Using Learning Analytics to Measure Motivational and Affective Processes in SRL.- A typology of self-regulation in writing from multiple sources.- Investigating the educators' needs and interpretations of the collaboration process analytics.- Augmented Reality (AR) for Biology Learning: A Quasi-experiment Study with High School Students.- Struggling Readers Smiling on the Inside and Getting Correct Answers.- Exploring Selective College Attendance and Middle School Cognitive and Non-Cognitive Factors within Computer-Based Math Learning.- Supporting Doctoral Student Social-Emotional LearningUsing Single-Case Learning Analytics.- Investigating the Potential of AI-based Social Matching Systems to Facilitate Social Interaction Among Online Learners.- Developing Social Interaction Metrics for an Active, Social, and Case-Based Online Learning Platform.- Network Climate Action through MOOCs Cornell (Environmental education).
Dr. Elle Yuan Wang is a Lead Research and Data Scientist at ASU EdPlus Action Lab and the National AI Institute of Adult Learning and Online Education (AI-ALOE). Her current projects center on assessing social and emotional leaning skillsets and predicting learner longitudinal career development in large-scale online learning environments in AI-augmented learning environments. Specifically, her projects take a comprehensive approach by linking three sources of learner data: pre-course learner motivation, within-course learner engagement, as well as post-course development. She obtained a Ph.D in Cognitive Sciences from Columbia University and has led various projects funded by the National Science Foundation (NSF), America's Seed Fund by NSF, and the Bill & Melinda Gates Foundation. She has served leadership positions in professional communities such as the Industry and Innovation Chair for the International Conference on Artificial Intelligence in Education (AIED). Previously, she hasheld fellowship and positions with Mayor Bloomberg's Office in New York, the Office of the President at Columbia University, Columbia Technology Ventures, and MTV Networks.
ISBN-13:
9783031063336
Veröffentl:
2022
Seiten:
335
Autor:
Yuan ’Elle’ Wang
Serie:
Advances in Analytics for Learning and Teaching
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch

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