Explanation Effect: Why You Should Always Teach What You Learn

Explanation Effect: Why You Should Always Teach What You Learn

In the strange realm of learning, there exists a peculiar paradox: the fastest and most effective way to truly grasp a subject is to teach it to others as soon as you acquire knowledge. It may seem counterintuitive, as one might think that holding onto newfound knowledge would solidify understanding. However, knowledge yearns to be shared, to connect with other minds, and to expand its reach. Learning is not a solitary act of absorbing information; it is a social process that thrives on interaction and dissemination.

Throughout my experience coaching numerous individuals on the art of learning, I've discovered that very few have a systematic approach to processing information. It's a common oversight that often hampers the ability to fully comprehend and retain knowledge. However, there is a simple yet transformative solution: starting a daily learning journal.

According to a study conducted at Harvard, employees who dedicated the last 15 minutes of each training day to writing and reflecting on what they had learned performed 23% better in the final training test compared to their counterparts. Remarkably, these 15 minutes accounted for a mere fraction of the total training time, yet they yielded a significant learning gain. This highlights the power of reflection and sharing in solidifying knowledge.

The concept of the "Explanation Effect" is rooted in the idea that teaching others enhances one's own understanding of a subject. When we are forced to articulate our knowledge to someone else, we are compelled to organize our thoughts, fill in gaps in our understanding, and clarify concepts. It is through this process that we truly internalize information and develop a profound mastery of the subject matter.

But why does this phenomenon occur? The answer lies in the power laws that govern our cultural landscape. Networks, whether social or informational, are subject to potent positive feedback loops. These loops create a heightened emphasis on popular choices and amplify their influence. Two key mechanisms drive this phenomenon: information cascades and reputational cascades.

Information cascades occur when individuals base their decisions on the choices made by others. It is a rational choice to rely on the collective wisdom of the network when confronted with high search and opportunity costs. When many people consecutively make decisions based on others' choices, it creates a feedback loop that propels certain choices to the forefront, leading to an "information cascade."

Similarly, reputational cascades arise from social conformity. Humans possess an inherent inclination to conform, as evidenced by famous social science experiments conducted in the mid-20th century. When faced with a plethora of choices and easy observability of others' decisions, we are more prone to conform consciously or subconsciously. This conformity further amplifies the influence of certain choices within the network.

As the availability of content continues to explode, search costs skyrocket, and opportunity costs increase. Consequently, many individuals outsource their content curation to friends, experts, celebrities, or recommendation algorithms. These external sources serve as social signals that guide decision-making, shaping the distribution of popularity within the network.

While the concentration of attention on a select few choices may seem inevitable, it is essential to recognize that luck plays a significant role in this process. In a networked environment, hits are highly sensitive to initial conditions. Those choices that happen to gain traction early on have a higher likelihood of dominating the field. This element of chance underscores the importance of timing and seizing opportunities within the networked landscape.

Quality remains a crucial factor in determining popularity, as complete mediocrity is destined to fail. However, beyond a certain threshold of quality, network dynamics assume a prominent role in driving popularity. Understanding and harnessing these dynamics become imperative for content creators and marketers seeking to navigate the ever-evolving digital landscape.

Paid media, once a reliable avenue for exposure, faces dilution in value as more content discovery occurs through network-driven mechanisms. Marketers must adapt and comprehend the emerging organic signals within the network, employing both paid and earned media to amplify or counter these signals strategically.

In conclusion, the Explanation Effect serves as a powerful reminder of the social nature of learning and the interconnectedness of knowledge. By teaching what we learn, we not only solidify our understanding but also contribute to the growth and dissemination of knowledge within the network. To leverage this effect, consider implementing the following actionable advice:

1. Embrace the power of reflection: Dedicate a portion of your learning journey to writing and reflecting on what you have learned. By articulating your knowledge, you enhance your understanding and create a stronger foundation for future learning.

2. Seek opportunities to teach: Don't hoard your knowledge; share it with others. Whether through mentoring, writing, or public speaking, teaching what you learn not only benefits others but also deepens your own comprehension.

3. Understand network dynamics: Familiarize yourself with the principles of information cascades, reputational cascades, and power laws. By understanding how choices gain popularity within networks, you can navigate the digital landscape more effectively and tailor your content or marketing strategies accordingly.

Remember, knowledge is not meant to be confined within individual minds but to flourish through connection and sharing. Embrace the Explanation Effect and embark on a journey of continuous learning, teaching, and growth.