LEADER 05750nam 22006375 450 001 9910736996403321 005 20240117121750.0 010 $a3-031-06333-3 024 7 $a10.1007/978-3-031-06333-6 035 $a(MiAaPQ)EBC7077597 035 $a(Au-PeEL)EBL7077597 035 $a(CKB)24739754500041 035 $a(DE-He213)978-3-031-06333-6 035 $a(EXLCZ)9924739754500041 100 $a20220824d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSocial and Emotional Learning and Complex Skills Assessment $eAn Inclusive Learning Analytics Perspective /$fedited by Yuan 'Elle' Wang, Sre?ko Joksimovi?, Maria Ofelia Z. San Pedro, Jason D. Way, John Whitmer 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (341 pages) 225 1 $aAdvances in Analytics for Learning and Teaching,$x2662-2130 311 08$aPrint version: Wang, Yuan 'Elle' Social and Emotional Learning and Complex Skills Assessment Cham : Springer International Publishing AG,c2022 9783031063329 327 $aRe-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 Learning Using 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). 330 $aIn 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). 410 0$aAdvances in Analytics for Learning and Teaching,$x2662-2130 606 $aEducational technology 606 $aData mining 606 $aEducation$xData processing 606 $aDigital Education and Educational Technology 606 $aData Mining and Knowledge Discovery 606 $aComputers and Education 606 $aAprenentatge social$2thub 606 $aIntel·ligència emocional$2thub 608 $aLlibres electrònics$2thub 615 0$aEducational technology. 615 0$aData mining. 615 0$aEducation$xData processing. 615 14$aDigital Education and Educational Technology. 615 24$aData Mining and Knowledge Discovery. 615 24$aComputers and Education. 615 7$aAprenentatge social 615 7$aIntel·ligència emocional 676 $a152.4 676 $a370.153 700 $aWang$b Yuan$0603894 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910736996403321 996 $aSocial and emotional learning and complex skills assessment$93427807 997 $aUNINA