1st Edition

Handbook of Research on Science Learning Progressions

Edited By Hui Jin, Duanli Yan, Joseph Krajcik Copyright 2025
    552 Pages 5 Color & 68 B/W Illustrations
    by Routledge

    552 Pages 5 Color & 68 B/W Illustrations
    by Routledge

    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                 

     

    Biography

    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.