TLDR;
This TEDx talk explores the concept of "productive failure" as a powerful tool for learning. It challenges the traditional approach of direct instruction, where concepts are taught before problem-solving, and advocates for allowing learners to struggle with problems first, enabling them to better understand and apply new knowledge. The speaker shares personal anecdotes and scientific evidence to support the idea that failure, when intentionally designed, can significantly enhance learning outcomes.
- Failure, when designed productively, enhances learning.
- Productive failure involves problem-solving before instruction.
- This approach fosters deeper understanding and knowledge transfer.
Introduction: The Power of Designing for Failure [0:12]
The speaker begins by highlighting the common experience of failure and its potential as a teacher. He questions why failure is typically waited for rather than intentionally designed into learning processes. He proposes that designing for failure can unlock powerful learning opportunities and that there is a science behind making failure productive.
First Love: Training to the Limit [1:04]
The speaker shares a personal story about his teenage years and his passion for football. He describes the rigorous training regimen that involved pushing the body to its limits and beyond. This experience taught him that significant mental and physical growth occurs on the other side of failure, where the mind and body work together to optimize performance.
Twenties: A Series of Failures [3:20]
The speaker recounts his series of failures in his twenties, including struggles with engineering, a failed startup, a hated consulting job, and ultimately, unsuccessful teaching. Despite his initial passion for teaching, he couldn't understand why his students weren't grasping the concepts he was trying to convey, leading him to feel like a failure. This prompted him to transition into academia to investigate why his students weren't learning.
The Director's Eye: Seeing Beyond the Surface [5:15]
The speaker uses a thought experiment involving watching a movie with an acclaimed director to illustrate the difference between expert and novice perspectives. Experts see deeper structures and critical features that novices often miss because seeing is a cognitive exercise, not just a perceptual one. This realization led him to understand that his first job as a teacher was to prepare students to see before showing them.
Productive Failure vs. Direct Instruction [7:31]
The speaker introduces two methods for teaching a new math concept: direct instruction (teaching the concept first, then solving problems) and productive failure (solving problems first, then receiving instruction). He questions the logic of asking students to solve problems they don't yet have the concepts for, acknowledging that they will likely fail. However, he posits that this failure can be productive if intentionally designed to enhance learning from subsequent instruction.
The Science Behind Productive Failure [9:25]
The speaker discusses experiments comparing productive failure and direct instruction. While both methods are equally effective at developing basic knowledge (the kind tested on exams), productive failure significantly outperforms direct instruction when it comes to understanding and transferring knowledge to solve novel problems. Students learning through productive failure perform one to two academic years ahead of those under direct instruction. The more students fail and produce non-working solutions, the better prepared they are to learn.
Replication and the Pursuit of Failure [11:10]
The speaker emphasizes the importance of replication in science, noting that the scientific community seeks to disprove novel findings. The logic of replication is a pursuit of failure; if repeated attempts to disprove a work fail, then the work has merit. Productive failure has been replicated and extended globally, demonstrating the robustness of the findings. Making initial learning harder prepares learners to see and learn from instruction later.
The Four A's of Deep Learning [13:05]
The speaker explains why productive failure works by creating four conditions of deep learning: Activation (activating prior knowledge), Awareness (understanding what you know and don't know), Affect (positive motivation to bridge the gap), and Assembly (experts explain and build knowledge). These conditions facilitate powerful and deep learning experiences.
Playing with Toys: Inventiveness and Creativity [14:33]
The speaker uses a thought experiment involving children playing with toys to illustrate the importance of exploration and tinkering in learning. Children who are allowed to play freely with a toy are more inventive and creative than those who are first shown how to play with it. He argues that knowledge and concepts are like mental toys that require exploration, tinkering, and even failure to achieve deep learning.
Conclusion: Learn to Fail [17:00]
The speaker concludes by emphasizing that the message is based on science, not opinion or motivation. He asserts that if you don't learn to fail, you will fail to learn, underscoring the critical role of productive failure in the learning process.
