Assessing Model-Based Reasoning using Evidence- Centered Design (eBook)

A Suite of Research-Based Design Patterns
eBook Download: PDF
2017 | 1st ed. 2017
XVII, 130 Seiten
Springer International Publishing (Verlag)
978-3-319-52246-3 (ISBN)

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Assessing Model-Based Reasoning using Evidence- Centered Design - Robert J Mislevy, Geneva Haertel, Michelle Riconscente, Daisy Wise Rutstein, Cindy Ziker
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This Springer Brief provides theory, practical guidance, and support tools to help designers create complex, valid assessment tasks for hard-to-measure, yet crucial, science education standards. Understanding, exploring, and interacting with the world through models characterizes science in all its branches and at all levels of education. Model-based reasoning is central to science education and thus science assessment. Current interest in developing and using models has increased with the release of the Next Generation Science Standards, which identified this as one of the eight practices of science and engineering. However, the interactive, complex, and often technology-based tasks that are needed to assess model-based reasoning in its fullest forms are difficult to develop.  

Building on research in assessment, science education, and learning science, this Brief describes a suite of design patterns that can help assessment designers, researchers, and teachers create tasks for assessing aspects of model-based reasoning: Model Formation, Model Use, Model Elaboration, Model Articulation, Model Evaluation, Model Revision, and Model-Based Inquiry. Each design pattern lays out considerations concerning targeted knowledge and ways of capturing and evaluating students' work. These design patterns are available at http://design-drk.padi.sri.com/padi/do/NodeAction?state=listNodes&NODE_TYPE=PARADIGM_TYPE. The ideas are illustrated with examples from existing assessments and the research literature.



Robert J. Mislevy, PhD, is Frederic M. Lord Chair in Measurement and Statistics at the Educational Testing Service in Princeton, New Jersey, and Professor Emeritus at the University of Maryland.

Geneva D. Haertel, PhD, is Director of Assessment Research and Design at the Center for Technology in Learning, SRI International.

Michelle M. Riconscente, PhD, is Director of Learning and Assessment at GlassLab in California.

Daisy Wise Rutstein, PhD, is Education Researcher in the Education Division at SRI International.

Cindy S. Ziker, PhD, MPH, is Senior Researcher for Assessment in the Education Division of the Center for Technology and Learning at SRI International.


Robert J. Mislevy, PhD, is Frederic M. Lord Chair in Measurement and Statistics at the Educational Testing Service in Princeton, New Jersey, and Professor Emeritus at the University of Maryland.Geneva D. Haertel, PhD, is Director of Assessment Research and Design at the Center for Technology in Learning, SRI International.Michelle M. Riconscente, PhD, is Director of Learning and Assessment at GlassLab in California.Daisy Wise Rutstein, PhD, is Education Researcher in the Education Division at SRI International.Cindy S. Ziker, PhD, MPH, is Senior Researcher for Assessment in the Education Division of the Center for Technology and Learning at SRI International.

Preface 7
Acknowledgements 10
Contents 11
About the Authors 13
1 Introduction 16
Abstract 16
2 Model-Based Reasoning 24
Abstract 24
2.1 Scientific Models 24
2.2 The Inquiry Cycle 27
2.3 Some Relevant Results from Psychology 29
2.3.1 Experiential Aspects of Model-Based Reasoning 29
2.3.2 Reflective Aspects of Model-Based Reasoning 30
2.3.3 Higher-Level Skills 31
2.3.4 Implications for Assessment Use Cases 32
3 Evidence-Centered Assessment Design 34
Abstract 34
3.1 Assessment Arguments 35
3.2 Design Patterns 37
4 Design Patterns for Model-Based Reasoning 40
Abstract 40
5 Model Formation 45
Abstract 45
5.1 Rationale, Focal KSAs, and Characteristic Task Features 45
5.2 Additional KSAs 50
5.3 Variable Task Features 53
5.4 Potential Work Products and Potential Observations 56
5.5 Considerations for Larger Investigations 60
5.6 Some Connections to Other Design Patterns 61
6 Model Use 63
Abstract 63
6.1 Rationale, Focal KSAs, and Characteristic Task Features 63
6.2 Additional KSAs 67
6.3 Variable Task Features 69
6.4 Potential Work Products and Potential Observations 69
6.5 Some Connections with Other Design Patterns 71
7 Model Elaboration 72
Abstract 72
7.1 Rationale, Focal KSAs, and Characteristic Task Features 72
7.2 Additional KSAs 74
7.3 Variable Task Features 74
7.4 Potential Work Products and Potential Observations 76
7.5 Some Connections with Other Design Patterns 77
8 Model Articulation 78
Abstract 78
8.1 Rationale, Focal KSAs, and Characteristic Task Features 79
8.2 Additional KSAs 80
8.3 Variable Task Features 80
8.4 Potential Work Products and Potential Observations 81
8.5 Some Connections with Other Design Patterns 82
9 Model Evaluation 84
Abstract 84
9.1 Rationale, Focal KSAs, and Characteristic Task Features 84
9.2 Additional KSAs 89
9.3 Variable Task Features 90
9.4 Potential Work Products and Potential Observations 91
9.5 Some Connections with Other Design Patterns 92
10 Model Revision 93
Abstract 93
10.1 Rationale, Focal KSAs, and Characteristic Task Features 93
10.2 Additional KSAs 96
10.3 Variable Task Features 97
10.4 Potential Work Products and Potential Observations 98
10.5 Some Connections with Other Design Patterns 98
11 Model-Based Inquiry 100
Abstract 100
11.1 Rationale, Focal KSAs, and Characteristic Task Features 101
11.2 Additional KSAs 103
11.3 Variable Task Features 103
11.4 Potential Work Products and Potential Observations 105
11.5 Some Connections with Other Design Patterns 108
12 Conclusion 109
Abstract 109
12.1 Standards-Based Assessment 109
12.2 Classroom Assessment 110
12.3 Large-Scale Accountability Testing 111
12.4 Simulation- and Game-Based Assessment 112
12.5 Closing Comments 113
Appendix: Summary Form of Design Patterns for Model-Based Reasoning 114
References 129
Index 136

Erscheint lt. Verlag 25.7.2017
Reihe/Serie SpringerBriefs in Statistics
SpringerBriefs in Statistics
Zusatzinfo XVII, 130 p. 23 illus., 9 illus. in color.
Verlagsort Cham
Sprache englisch
Themenwelt Mathematik / Informatik Mathematik Statistik
Sozialwissenschaften Pädagogik
Sozialwissenschaften Soziologie Empirische Sozialforschung
Schlagworte Assessment • Bayesian • Design Patterns • Evidence-Centered Design • inference • Learning and Instruction • learning science • model articulation • model-based inquiry • Model-Based Reasoning • model elaboration • Model Evaluation • model formation • model revision • model use • Next Generation Science Framework • science education
ISBN-10 3-319-52246-9 / 3319522469
ISBN-13 978-3-319-52246-3 / 9783319522463
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