Visible Learning for Mathematics, Grades K-12

  • Title:Visible Learning for Mathematics, Grades K-12: What Works Best to Optimize Student Learning
  • Author:John Hattie, Douglas Fisher, Nancy Frey, Linda Gojak, Sara Delano Moore, William Mellman
  • Publication Date:October 2016
  • Grade Level:K-12
  • ISBN:9781506362946
  • Publisher:Corwin Press

Rich tasks, collaborative work, number talks, problem-based learning, direct instruction…with so many possible approaches, how do we know which ones work the best? In Visible Learning for Math, six acclaimed educators assert it’s not about which one—it’s about when—and show you how to design high-impact instruction so all students demonstrate more than a year’s worth of mathematics learning for a year spent in school.

That’s a high bar, but with the amazing K-12 framework here, you choose the right approach at the right time, depending upon where learners are within three phases of learning: surface, deep, and transfer. This results in “visible” learning because the  effect is tangible. The framework is forged out of current research in mathematics combined with John Hattie’s synthesis of more than 15 years of education research involving 300 million students.

Chapter by chapter, and equipped with video clips, planning tools, rubrics, and templates, you get the inside track on which instructional strategies to use at each phase of the learning cycle:

  • Surface learning phase: When—through carefully constructed experiences—students explore new concepts and make connections to procedural skills and vocabulary that give shape to developing conceptual understandings.
  • Deep learning phase: When—through the solving of rich high-cognitive tasks and rigorous discussion—students make connections among conceptual ideas, form mathematical generalizations, and apply and practice procedural skills with fluency.
  • Transfer phase: When students can independently think through more complex mathematics, and can plan, investigate, and elaborate as they apply what they know to new mathematical situations.

To equip students for higher-level mathematics learning, we have to be clear about where students are, where they need to go, and what it looks like when they get there. Visible Learning for Math brings about powerful, precision teaching for K-12 through intentionally designed guided, collaborative, and independent learning.

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Author Bio

John Hattie is an award-winning education researcher and best-selling author. His research, better known as Visible Learning, is a culmination of nearly 30 years synthesizing more than 1,500 meta-analyses comprising more than 90,000 studies involving over 300 million students around the world.

Douglas Fisher is a professor of educational leadership at San Diego State University and a teacher leader at Health Sciences High & Middle College. He is a member of the California Reading Hall of Fame and was honored as an exemplary leader by the Conference on English Leadership. He has published numerous articles on improving student achievement.

Nancy Frey is a professor of educational leadership at San Diego State University. Frey also teaches classes at Health Sciences High and Middle College in San Diego. She is a recipient of the Christa McAuliffe Award for Excellence in Teacher Education from the American Association of State Colleges and Universities and the Early Career Award from the Literacy Research Association. She has published many articles and books on literacy and instruction.

Linda M. Gojak has spent 28 years teaching elementary and middle school mathematics, and has served as the president of the National Council of Teachers of Mathematics (NCTM) and the National Council of Supervisors of Mathematics (NCSM). Building conceptual understanding of mathematical ideas and problem solving sit at the core of her expertise.

Sara Delano Moore is an independent mathematics education consultant at SDM Learning.  Her work focuses on helping teachers and students understand mathematics as a coherent and connected discipline through the power of deep understanding and multiple representations for learning.

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