Handbook of automated scoring theory into practice
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| Format: | Buch |
| Sprache: | English |
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Boca Raton ; London ; New York
CRC Press
2021
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| Schriftenreihe: | Chapman & Hall/CRC statistics in the social and behavioral sciences series
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| 245 | 1 | 0 | |a Handbook of automated scoring |b theory into practice |c edited by Duanli Yan, André A. Rupp, Peter W. Foltz |
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Datensatz im Suchindex
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| adam_text | Contents Foreword............................................................................................................................xi Editors................................................................................................................................ xv List of Contributors......................................................................................................xvii 1 The Past, Present, and Future of Automated Scoring......................... 1 Peter W. Foltz, Duanli Yon, and André A. Rupp Part I: Theoretical Foundations 2 Cognitive Foundations of Automated Scoring.................................. 13 Malcolm I. Bauer and Diego Zapata-Rivera 3 Assessment Design with Automated Scoring in Mind..................... 29 Kristen DiCerbo, Emily Lai, and Matthew Ventura 4 Human Scoring with Automated Scoring in Mind............................49 Edward W. Wolfe 5 Natural Language Processing for Writing and Speaking..................69 Aoife Cahill and Keelan Evanini 6 Multimodal Analytics for Automated Assessment............................93 Sidney K. D Mello 7 International Applications of Automated Scoring........................... 113 Mark D. Shermis 8 Public Perception and Communication around Automated Essay Scoring......................................................................................133 Scott W. Wood 9 An Evidentiary-Reasoning Perspective on Automated Scoring: Commentary on Part I........................................................................151 Robert}. Mislevy Part II: Operational Methodologies 10
Operational Human Scoring at Scale................................................171 Kathryn L. Ricker-Pedley, Susan Hines, and Carolyn Connelly vii
Contents viii 11 System Architecture Design for Scoring and Delivery................... 195 Sue Lottridge and Nick Hoefer 12 Design and Implementation for Automated Scoring Systems..................................................................................217 Christina Schneider and Michelle Boyer 13 Quality Control for Automated Scoring in Large-Scale Assessment..........................................................................................241 Dan Shaw, Brad Bolender, and Rick Meisner 14 A Seamless Integration of Human and Automated Scoring............263 Kyle Habermehl, Aditya Nagarajan, and Scott Dooley 15 Deep Learning Networks for Automated Scoring Applications.... 283 Saad M. Khan and Yuchi Huang 16 Validation of Automated Scoring Systems...................................... 297 Duanli Yan and Brent Bridgeman 17 Operational Considerations for Automated Scoring Systems: Commentary on Part II......................................................................319 David M. Williamson Part III: Practical Illustrations 18 Expanding Automated Writing Evaluation...................................... 329 Jill Burstein, Brian Riordan, and Daniel McCaffrey 19 Automated Writing Process Analysis............................................... 347 Paul Deane and Mo Zhang 20 Automated Scoring of Extended Spontaneous Speech.................... 365 Klaus Zechner and Anastassia Lonkina 21 Conversation-Based Learning and Assessment Environments...... 383 Arthur C. Graesser, Xiangen Hu, Vasile Rus, and Zhiqiang Cai 22 Automated Scoring in Intelligent Tutoring
Systems.......................403 Robert J. Mislevy, Duanli Yan, Janice Gobert, and Michael Sao Pedro 23 Scoring of Streaming Data in Game-Based Assessments................423 Russell G. Almond
Contents ix 24 Automated Scoring in Medical Licensing...........................................445 Melissa J. Margolis and Brian E. Clauser 25 At the Birth of the Future: Commentary on Part III...........................469 John T. Behrens 26 Theory into Practice: Reflections on the Handbook.......................... 475 André A. Rupp, Peter W. Foltz, and Duanli Yan Glossary.......................................................................................................... 489 References...................................................................................................... 501 Index................................................................................................................553
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| adam_txt |
Contents Foreword.xi Editors. xv List of Contributors.xvii 1 The Past, Present, and Future of Automated Scoring. 1 Peter W. Foltz, Duanli Yon, and André A. Rupp Part I: Theoretical Foundations 2 Cognitive Foundations of Automated Scoring. 13 Malcolm I. Bauer and Diego Zapata-Rivera 3 Assessment Design with Automated Scoring in Mind. 29 Kristen DiCerbo, Emily Lai, and Matthew Ventura 4 Human Scoring with Automated Scoring in Mind.49 Edward W. Wolfe 5 Natural Language Processing for Writing and Speaking.69 Aoife Cahill and Keelan Evanini 6 Multimodal Analytics for Automated Assessment.93 Sidney K. D'Mello 7 International Applications of Automated Scoring. 113 Mark D. Shermis 8 Public Perception and Communication around Automated Essay Scoring.133 Scott W. Wood 9 An Evidentiary-Reasoning Perspective on Automated Scoring: Commentary on Part I.151 Robert}. Mislevy Part II: Operational Methodologies 10
Operational Human Scoring at Scale.171 Kathryn L. Ricker-Pedley, Susan Hines, and Carolyn Connelly vii
Contents viii 11 System Architecture Design for Scoring and Delivery. 195 Sue Lottridge and Nick Hoefer 12 Design and Implementation for Automated Scoring Systems.217 Christina Schneider and Michelle Boyer 13 Quality Control for Automated Scoring in Large-Scale Assessment.241 Dan Shaw, Brad Bolender, and Rick Meisner 14 A Seamless Integration of Human and Automated Scoring.263 Kyle Habermehl, Aditya Nagarajan, and Scott Dooley 15 Deep Learning Networks for Automated Scoring Applications. 283 Saad M. Khan and Yuchi Huang 16 Validation of Automated Scoring Systems. 297 Duanli Yan and Brent Bridgeman 17 Operational Considerations for Automated Scoring Systems: Commentary on Part II.319 David M. Williamson Part III: Practical Illustrations 18 Expanding Automated Writing Evaluation. 329 Jill Burstein, Brian Riordan, and Daniel McCaffrey 19 Automated Writing Process Analysis. 347 Paul Deane and Mo Zhang 20 Automated Scoring of Extended Spontaneous Speech. 365 Klaus Zechner and Anastassia Lonkina 21 Conversation-Based Learning and Assessment Environments. 383 Arthur C. Graesser, Xiangen Hu, Vasile Rus, and Zhiqiang Cai 22 Automated Scoring in Intelligent Tutoring
Systems.403 Robert J. Mislevy, Duanli Yan, Janice Gobert, and Michael Sao Pedro 23 Scoring of Streaming Data in Game-Based Assessments.423 Russell G. Almond
Contents ix 24 Automated Scoring in Medical Licensing.445 Melissa J. Margolis and Brian E. Clauser 25 At the Birth of the Future: Commentary on Part III.469 John T. Behrens 26 Theory into Practice: Reflections on the Handbook. 475 André A. Rupp, Peter W. Foltz, and Duanli Yan Glossary. 489 References. 501 Index.553 |
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| spelling | Handbook of automated scoring theory into practice edited by Duanli Yan, André A. Rupp, Peter W. Foltz Boca Raton ; London ; New York CRC Press 2021 580 Seiten Illustrationen, Diagramme 24 cm txt rdacontent n rdamedia nc rdacarrier Chapman & Hall/CRC statistics in the social and behavioral sciences series Grading and marking (Students) / Data processing Educational tests and measurements / Data processing Natural language processing (Computer science) Educational tests and measurements / Data processing fast Grading and marking (Students) / Data processing fast Natural language processing (Computer science) fast Testauswertung (DE-588)4124305-5 gnd rswk-swf Data Science (DE-588)1140936166 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Testauswertung (DE-588)4124305-5 s Maschinelles Lernen (DE-588)4193754-5 s Data Science (DE-588)1140936166 s DE-604 Yan, Duanli (DE-588)121353061X edt Rupp, André A. (DE-588)1251563457 edt Foltz, Peter W. (DE-588)1251563473 edt Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=033043125&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Handbook of automated scoring theory into practice |
| title_auth | Handbook of automated scoring theory into practice |
| title_exact_search | Handbook of automated scoring theory into practice |
| title_exact_search_txtP | Handbook of automated scoring theory into practice |
| title_full | Handbook of automated scoring theory into practice edited by Duanli Yan, André A. Rupp, Peter W. Foltz |
| title_fullStr | Handbook of automated scoring theory into practice edited by Duanli Yan, André A. Rupp, Peter W. Foltz |
| title_full_unstemmed | Handbook of automated scoring theory into practice edited by Duanli Yan, André A. Rupp, Peter W. Foltz |
| title_short | Handbook of automated scoring |
| title_sort | handbook of automated scoring theory into practice |
| title_sub | theory into practice |
| topic | Grading and marking (Students) / Data processing Educational tests and measurements / Data processing Natural language processing (Computer science) Educational tests and measurements / Data processing fast Grading and marking (Students) / Data processing fast Natural language processing (Computer science) fast Testauswertung (DE-588)4124305-5 gnd Data Science (DE-588)1140936166 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
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