Training Reinforcement: The 7 Principles to Create Measurable Behavior Change and Make Learning Stick

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· Gildan Media · 내레이터: Danny Campbell
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Training Reinforcement offers expert guidance for more effective training outcomes. Last year, US companies spent over $165 Billon on training; while many training programs themselves provide valuable skills and concepts, even the best-designed programs are ineffective because the learned behaviors are not reinforced. Without reinforcement, learned information gets shuffled to the back of the mind in the "nice to know" file, never again to see the light of day. This book bridges the canyon between learning and doing by providing solid reinforcement strategies. Written by a former Olympic athlete and corporate training guru, this methodology works with human behavior rather than against it; you'll learn where traditional training methods fail, and how to fill those gaps with proven techniques that help training "stick."



There's a difference between "telling" and "teaching," and that difference is reinforcement. Learned skills and behaviors cannot be truly effective until they are engrained, and they can only become engrained through use, encouragement, and measureable progress. This book provides a robust reinforcement framework that adds long-term value to any training program.

저자 정보

Anthonie Wurth is Dutch and the founder of Mindmarker, the world leader in training reinforcement. He won the European Judo championship in 1991 and competed in the 1992 Olympics in Barcelona. Since 1993 he has become active and well known in the learning industry. He is the author of Locked in Shanghai. Kees Wurth is CEO of Mindmarker. A former national Judo champion in the Netherlands, he immigrated to the United States in 1993 and has since become an entrepreneur who has successfully started and sold numerous companies. A classically trained actor, director, and teacher with many regional Shakespeare plays to his credit, Danny Campbell has narrated over 150 titles and directed at least that many. He is a multiple AudioFile Earphones Award winner and was named one of AudioFile's Best of the Year 2017.

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나레이터: Danny Campbell