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El. knyga: Handbook of Research on Science Learning Progressions [Taylor & Francis e-book]

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  • Formatas: 532 pages, 42 Tables, black and white; 64 Line drawings, black and white; 5 Halftones, color; 4 Halftones, black and white; 5 Illustrations, color; 68 Illustrations, black and white
  • Išleidimo metai: 30-Jul-2024
  • Leidėjas: Routledge
  • ISBN-13: 9781003170785
  • Taylor & Francis e-book
  • Kaina: 290,82 €*
  • * this price gives unlimited concurrent access for unlimited time
  • Standartinė kaina: 415,45 €
  • Sutaupote 30%
  • Formatas: 532 pages, 42 Tables, black and white; 64 Line drawings, black and white; 5 Halftones, color; 4 Halftones, black and white; 5 Illustrations, color; 68 Illustrations, black and white
  • Išleidimo metai: 30-Jul-2024
  • Leidėjas: Routledge
  • ISBN-13: 9781003170785

Gathering contributions from leading scholars around the world, this handbook offers a comprehensive resource on the most recent advances in research surrounding the theories, methodologies, and applications of science learning progressions.



Gathering contributions from leading scholars around the world, this handbook offers a comprehensive resource on the most recent advances in research surrounding the theories, methodologies, and applications of science learning progressions.

Researchers and educators have used learning progressions to guide the design and alignment of curriculum, instruction, and assessment, and to help students learn scientific knowledge and practices in a coherent and connected way across multiple years. This handbook lays out the development and current state of research in this field across four sections: learning progression theories and methodologies; learning progressions to promote student learning; teachers’ learning and use of learning progressions; and new technology in learning progression research.

Featuring internationally-recognized experts in learning progression research as well as up-and-coming voices, the Handbook of Research on Science Learning Progressions offers a defining new resource for researchers, teachers and teacher educators, and curriculum and assessment developers in science education.

1. An Introduction to Science Learning Progression Research Section 1:
Learning Progression Theories and Methodologies
2. Cognitive Foundations of
Science Learning Progressions
3. On the Critiques of the Learning Progression
Research
4. Validity of learning progressions
5. Development and Validation
of Knowledge-In-Use Learning Progressions
6. Coordinating Assessments with a
Learning Progression
7. Learning Progression Approaches Used in Germany
8.
Learning Progression Approaches Used in China
9. Implications of Mathematics
Learning Trajectories for Science Education
10. Commentary: Perspectives on
Learning Progression Theories and Methodologies Section 2: Learning
Progressions to Promote Student Learning
11. Learning Progressions in
Genetics
12. Developing Three-Dimensional Learning Progressions of Energy,
Interaction, and Matter at Middle School Level: A Design-Based Research
13.
Rethinking Learning Progression for Energy
14. Geology & Earth Systems
Sciences Learning Progressions
15. Supporting Curriculum Development with a
Learning Progression for Matter-tracing Investigations
16. Using a Learning
Progression to Assess and Scaffold Students Explanations of
Carbon-transforming Processes
17. Commentary: Reflection on the Learning
Progression Approach to Promoting Student Learning Section 3: Curriculum,
Instruction, and Teacher Learning
18. Key Components of Learning
Progression-Based Educative Curriculum Materials Designed to Support Teachers
and Their Diverse Students
19. Crosscutting Concepts and Learning
Progressions
20. Science Teacher Educators and Science Teacher Learning
Progressions: Resource, Roadmap, and Representation
21. Learning progressions
as supports for teachers' formative assessment practices
22. Using learning
progressions in professional development programs
23. Learning Progressions
and Youths Rightful Presence in Science
24. Commentary: Implications of
Teachers Learning and Use of Learning Progressions Section 4: Applications
of Innovative Technology and Artificial Intelligence to Support Learning
Progressions
25. Dynamic Bayesian Models for Learning Progressions
26. The
Application of Automated Scoring Technology in Learning Progression
Assessment
27. Integrating Artificial Intelligence into Learning Progression
to Support Student Knowledge-in-Use: Opportunities and Challenges
28. Using
an AI-based dashboard to help teachers support students learning
progressions for science practices
29. Commentary: The role of technology in
science learning progression
Hui Jin is an associate professor of science education at Georgia Southern University, USA.

Duanli Yan is the Director of Computational Research at ETS and adjunct professor at Fordham University, USA.

Joseph Krajcik directs the CREATE for STEM Institute and is a University Distinguished Professor at Michigan State University, USA.