🔖 Most Likely to Succeed: Preparing Our Kids for the Innovation Era by Tony Wagner and Ted Dintersmith

Bookmarked Most Likely to Succeed: Preparing Our Kids for the Innovation Era by Tony Wagner, Ted Dintersmith (Scribner)

From two leading experts in education and entrepreneurship, an urgent call for the radical re-imagining of American education so that we better equip students for the realities of the twenty-first century economy.

Today more than ever, we prize academic achievement, pressuring our children to get into the “right” colleges, have the highest GPAs, and pursue advanced degrees. But while students may graduate with credentials, by and large they lack the competencies needed to be thoughtful, engaged citizens and to get good jobs in our rapidly evolving economy. Our school system was engineered a century ago to produce a work force for a world that no longer exists. Alarmingly, our methods of schooling crush the creativity and initiative young people need to thrive in the twenty-first century.

In Most Likely to Succeed, bestselling author and education expert Tony Wagner and venture capitalist Ted Dintersmith call for a complete overhaul of the function and focus of American schools, sharing insights and stories from the front lines, including profiles of successful students, teachers, parents, and business leaders.

Most Likely to Succeed presents a new vision of American education, one that puts wonder, creativity, and initiative at the very heart of the learning process and prepares students for today’s economy. This book offers parents and educators a crucial guide to getting the best for their children and a roadmap for policymakers and opinion leaders.

Marked to read after seeing reference in Venture capitalist visits 200 schools in 50 states and says DeVos is wrong: ‘If choice and competition improve schools, I found no sign of it.’ by Valerie Strauss.

Published by

Chris Aldrich

I'm a biomedical and electrical engineer with interests in information theory, complexity, evolution, genetics, signal processing, IndieWeb, theoretical mathematics, and big history. I'm also a talent manager-producer-publisher in the entertainment industry with expertise in representation, distribution, finance, production, content delivery, and new media.

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