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E-raamat: Age of Inference

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  • Formaat: 487 pages
  • Ilmumisaeg: 01-Dec-2021
  • Kirjastus: Information Age Publishing
  • ISBN-13: 9781648027994
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  • Formaat: 487 pages
  • Ilmumisaeg: 01-Dec-2021
  • Kirjastus: Information Age Publishing
  • ISBN-13: 9781648027994

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In an age where we are inundated with information, the ability to discern verifiable information to make proper decisions and solve problems is ever more critical. Modern science, which espouses a systematic approach to making 'inferences,' requires a certain mindset that allows for a degree of comfort with uncertainty.

This book offers inspirations and ideas for cultivating the proper mindset for the studying, teaching, and practicing of science that will be useful for those new to as well as familiar with the field. Although a paradigm shift from traditional instruction is suggested in the National Framework for K-12 science, this volume is intended to help educators develop a personal mental framework in which to transition from a teacher-centered, didactical approach to a student-centered, evidence-guided curriculum.

While the topics of the book derive from currently published literature on STEM education as they relate to the National Framework for K-12 Science and the Three-Dimensional science instruction embedded in the Next Generation Science Standards, this book also examines these topics in the context of a new societal age posited as the 'Age of Inference' and addresses how to make sense of the ever-increasing deluge of information that we are experiencing by having a scientific and properly discerning mindset.



This book explores cultivating a scientific mindset for critical thinking and informed decision-making. It guides educators in shifting to student-centered, evidence-based STEM instruction, aligning with modern educational frameworks in the “Age of Inference.”

Arvustused

This volume takes on one of the thorniest existential problems of our time, the contradiction between the exponentially growing amount of information that individuals have access to, and the diminished capacity of those individuals to understand it. Its chapters provide the reader with an introduction to the relationship between knowledge, science, and inference; needed new approaches to learning science in our new data rich world; and a discussion of what we can and must do to reduce or eliminate the growing gap between the inference have's and have nots. It is not too much to say that how we resolve the issues outlined in this volume will determine the future of our species on this planet."" Joseph L. Graves Jr., Professor of Biological Sciences North Carolina A&T State University, Fellow, American Association for the Advancement of Science: Biological Sciences, Author of: The Emperor's New Clothes: Biological Theories of Race at the Millennium

""Big data is not enough for addressing dangers to the environment or tackling threats to democracy; we need the ability to draw sound inferences from the data. Cultivating a scientific mindset requires fundamental changes to the way we teach and learn. This important and well -written volume shows how."" Ashok Goel, Professor of Computer Science and Human Centered Computing, Georgia Institute of Technology. Editor of AI Magazine Founding Editor of AAAI's Interactive AI Magazine

""If you are a science teacher concerned about the implications of information overload, analysis paralysis, and intellectual complacency on our health, economic future, and democracy, then I recommend this book."" Michael Svec, Professor for Physics and Astronomy Education, Furman University, Fulbright Scholar to Czech Republic

Foreword ix
Miranda Feliciano Tyson
Acknowledgments and Dedication xi
Section I Introduction: The Nature Of Knowledge, Science, And Inference
1 The Age of Inference
3(14)
John R. McConnell
Sarah B. Dugger
Philip C. Short
2 Nature of the Scientific Enterprise
17(22)
Harvey Henson
3 The Nature of Science Education: Relativity of Theory
39(20)
Philip C. Short
4 Mathematics: Language, Modeling, and Comparison Assisting Inference
59(16)
Mary Barone Martin
Tammy Jones
Dovie Kimmins
Teresa Schmidt
5 Statistics: Developing Impactful Teaching and Learning
75(16)
Mary Barone Martin
Tammy Jones
Teresa Schmidt
6 Statistics: Assessing Success in the Inference Process
91(18)
Mary Barone Martin
Tammy Jones
Teresa Schmidt
Section II Application: Framework For Science In A Data-Rich World
7 Children's Literature Resources to Support Authentic Science Practices and Environmental Decision-Making: The Conservation Tales Series
109(22)
Tom J. McConnell
Barbara Giorgio-Booher
8 Supporting Statistical Literacies in the Context of a Data Visualization Project With Elementary Students
131(10)
Lynn Hodge
Joy Bertling
Shande King
9 Green Literacy K-5: Nurturing a Scientific Mindset
141(16)
Jennifer Cullerton Johnson
Mary K. Gove
10 Complex Multimodal Text Sets to Support Science Literacy
157(26)
William Romine
Amy Lannin
Torrey Palmer
Delinda van Garderen
Rachel Juergensen
Cassandra M. Smith
William Folk
11 Power Up or Put Away? Using Mobile Phones for Authentic Student Investigations
183(12)
Kristin T. Rearden
Blanche O'Bannon
12 Self-Regulated Learning Theory to Build Scientific Mindsets for Diversity in STEM
195(18)
Giuseppina Mattietti
Erin E. Peters-Burton
13 A Case for the Model-Based Reasoning Classroom
213(10)
Arthur Beauchamp
Cynthia Passmore
14 Cultivating a Scientific Mindset Through Inquiry-Based Science Learning Utilizing Nasa Resources for Educators
223(16)
Leslie Huling
Virginia Resta
15 Bridging the Disconnect Between How We Do and Teach Science: Cultivating a Scientific Mindset in an Era of Data-Driven Education
239(26)
Jana Bouwma-Gearhart
16 The Scientific Method Card Game: Applications for Any Educational Context
265(14)
Kallina M. Dunkle
17 Toward a Design-Centered Scientific Mindset: Closing the Opportunity Gaps via 3D Design and Printing in STEM Teacher Education
279(20)
Lingguo Bu
Harvey Henson
Euginia Nyirenda
Section III Conclusion: The Future For Inferences And Actions
18 Developing Critical Literacy Skills Among Diverse Learners During the Age of Inference
299(18)
Laveria F. Hutchison
19 Content and Pedagogical Knowledge for Teaching Confidence Intervals in a Post p < 0.05. World
317(30)
Jennifer J. Kaplan
Kristen E. Roland
20 The Multidimensional Learning Goals for Making Inferences With Data
347(8)
Ryan Seth Jones
Anna Strimaitis Grinath
Fonya Scott
21 Expectations and Disciplinary Blends
355(14)
L. Jeneva Clark
R. Alexander Bentley
Nicholas N. Nagle
Vasileios Maroulas
22 Machine Learning: A New Lens for Integrating Computational Thinking and Science in the High School Classroom
369(16)
Michael Daley
Zhen Bai
Raffaella Borasi
Dave Miller
23 Becoming a Postmodern STEM Teacher Leader in the Age of Inference
385(8)
Rebekah Hammack
24 Seeking Homeostasis in a Heteroscedastic World: A Sense of the Stakes in the Age of Inference
393(18)
Philip C. Short
Donna F. Short
John R. McConnell
References 411(50)
About the Editors 461(2)
About the Contributors 463
Philip C. Short, Austin Peay State University

Harvey Henson, Southern Illinois University

John R. McConnell, Austin Peay State University