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One of the significant hurdles of semantic SEO is it’s complicated and often inaccessible. Much of our understanding of it is derived from Google’s patent papers.
Understanding these papers requires a wide range of skills, a grasp of natural language processing (NLP), search engines, and, occasionally, programming languages.
Despite this complexity, grasping the key takeaways from semantic SEO is crucial for formulating the best plans to drive SEO results.
In this two-part series, I’m taking a different approach. Instead of further exploring the direct changes in semantic SEO, I’ll discuss the most effective ways to learn and stay at the forefront of understanding.
The field of learning research has introduced various tools that, although sometimes counterintuitive, can significantly ease the learning of advanced concepts when used effectively.
In this first article, I will explore active recall and cognitive load theory and share ways to leverage cutting-edge tools like ChatGPT to elevate your SEO game.
Why learning about learning strategies is worth your time as an SEO
Unlike many other fields, SEO is in a state of flux. Consider semantic SEO, one of the many significant shifts in recent years. These changes require agility and continuous acquisition of new skills and knowledge.
Swift and effective learning is not just an advantage; it’s a necessity. It paves the way for efficient problem-solving and achieving ambitious goals.
When it comes to learning, it’s common to attribute people’s learning abilities to natural talents. While innate abilities play a role, a substantial body of research highlights the profound impact of effective learning strategies on learning outcomes.
Imagine choosing a strategy that doubles your learning efficiency (one study I’ll share below saw a 50% improvement in performance between these new approaches vs. most people’s default strategies).
Over time, these enhanced skills compound, resulting in a significant disparity of hundreds of percent in ability and knowledge.
Regardless of our natural abilities and inclinations, employing sound strategies can substantially elevate our trajectories as learners.
Understanding active recall
First on the agenda is a deep dive into a popular and effective learning concept called “active recall.”
This method’s power is illuminated through an illustrative study from the domain of learning research, which we’ll explore below.
Consider the following real-world scenario. In a notable learning research study (referenced in the following meta-analysis), researchers divided learners into three distinct groups.
Each group employed a unique strategy to engage with a passage of text, shedding light on the diverse approaches and their varied outcomes.
Passive learning group: Participants read and reread the text.
Active learning group: Participants tested themselves by answering multiple-choice questions about the text.
Elaborative learning group: Participants generated their own explanations of the passage.
Following these exercises, all groups were surveyed to gauge their confidence in the knowledge they had acquired, and subsequently, they were assessed through a test.
The findings unveiled a seemingly paradoxical outcome: the groups exuding the highest confidence fared the worst in the subsequent test.
On the flip side, the group embracing what researchers term as active strategies, in particular “elaborative learning” (a.k.a., active recall), exhibited lower confidence levels but outperformed the other groups in the test.
So, what is active recall?
Active recall is a learning strategy that actively stimulates memory recall during the learning process.
Suppose you are studying for a history test. Instead of simply reading the textbook or highlighting important dates (strategies shown to be ineffective despite their popularity), you close the book and quiz yourself on the material.
You might write down everything you remember about a specific event or use flashcards with questions on one side and answers on the other to quiz yourself. By actively engaging your brain to recall the information, you are strengthening your memory of the material, which is the essence of active recall.
Recognition vs. understanding
This study, among others, underscores a common problem: confusing simple recognition with genuine understanding.
Let’s take an example. Imagine reading an article about SEO or watching a video from your favorite YouTuber. Often, it might feel like you’ve grasped the content, convincing you that you’ve mastered the topic.
However, the real test of understanding comes when you try to explain these concepts in your own words. Suddenly, the clarity you previously felt vanishes, revealing significant gaps in your knowledge.
Here are some important points to consider:
Illusion of understanding
We often believe we understand information because we recognize it from reading or hearing it before. However, we don’t always have visual cues or context to jog our memory in real-world situations.
True understanding is accessing and using this information without these aids. Neuroscientists note that our thoughts often exist in fragments, providing a vague and incomplete picture.
Only when we attempt to articulate ideas in complete sentences do our knowledge gaps become glaringly apparent.
Personal integration
True learning is not just about memorizing information. It involves integrating this information into your mental framework, understanding it on a deeper level, and using it effectively in different contexts.
The “active recall” exercise forces us to transform information by fitting it into our current understanding.
Using ChatGPT and active learning to solve the 2 sigma problem
Before we cover our last learning tool, I’d like to share how introducing tools like ChatGPT can enable motivated learners to take the concept of active recall to the next level.
To understand why, let’s tackle one of the largest problems in learning science and how ChatGPT presents a solution that wasn’t imaginable in the past.
The 2 sigma problem
Identified by educational researcher Benjamin Bloom, the 2 sigma problem highlights a significant disparity in student performance between instructional techniques.
According to Bloom’s findings, students who receive one-on-one tutoring perform two standard deviations (or “two sigma”) better than those learning via traditional instructional methods.
For long, researchers have known that one-on-one tutoring is far superior. Given the resource intensity of personal tutoring, the problem lies in replicating these results on a larger scale.
So, how can you use ChatGPT?
Start your active recall exercise by:
Express your understanding of a semantic SEO concept in your own words.
Submitting this to ChatGPT with the prompt: “Read through my explanation and highlight the key areas where I either misunderstand the content or where there is key information I am missing.”
Receiving and reviewing detailed feedback to evaluate and enhance your comprehension.
By integrating ChatGPT into your learning regimen, you not only tackle the issue outlined in the 2 sigma problem but also harness the potent benefits of active recall.
This combined approach empowers you with a robust, comprehensive learning experience, refining your understanding and ensuring the retention of critical information.
Disclaimer: Despite the usefulness of large language models, I recommend verifying the outputs due to issues such as hallucinations. While the AI generally provides reliable guidance, it may falter when dealing with particularly niche subjects.
Understanding cognitive load theory
Now, let’s delve into one of the most profound insights from learning research. Grasping this model proves beneficial for learning, teaching, and even enhancing communication.
Cognitive load theory has gained prominence due to its effective and accurate representation of various learning challenges and its predictability for successful strategies.
So, what is cognitive load theory?
Cognitive load theory (CLT) explores how the use of working memory, the mental space where new information is processed, affects our ability to learn.
It posits that our working memory has limited capacity (on average 3-5 items), and understanding this can help us manage cognitive load effectively, leading to more efficient and effective learning.
Learning fails when working memory is not properly managed.
Let me introduce you to the main ideas of CLT by telling a fictional story about a newcomer to the SEO world, Alex.
Remember what it was like when you were starting to learn SEO?
Meet Alex, a newcomer to the industry, eager to understand its various aspects, including keyword research, backlink strategies, and on-page optimization.
Entering this field without prior knowledge, each new concept competes for space in his limited working memory. This intrinsic load, or the inherent complexity of SEO itself, can overwhelm Alex’s cognitive capacity, making learning inefficient and stressful.
As Alex delves deeper into his learning journey, external distractions or unclear instructional materials contribute additional load, known as extraneous load. This doesn’t aid his learning but rather consumes valuable cognitive space, exacerbating the learning challenges.
However, by understanding CLT, Alex finds strategies to enhance his learning experience. Focusing on mastering one SEO aspect at a time enables his working memory to efficiently process and retain each concept, minimizing overload. Seeking well-organized and clear instructional materials further reduces extraneous load, offering Alex a smoother learning curve.
Over time, as Alex forms “chunks” of SEO knowledge, his cognitive load for these topics diminishes. For instance, grasping the essence of keyword research becomes a single chunk in his working memory, freeing up cognitive resources for other SEO components.
This process, known as germane load, optimizes his cognitive capacity for effective learning and understanding, forming a robust knowledge base.
In essence, Alex’s journey highlights the practical application of cognitive load theory in learning SEO. By managing the different types of cognitive load effectively, Alex ensures a more effective and less overwhelming learning experience. His deeper understanding and proficient application of SEO principles pave the way for continued growth and success in the dynamic field of SEO.
Understanding and applying CLT principles, like Alex, can empower you in your learning endeavors, providing a structured and efficient pathway to mastering new and complex subjects.
Practical takeaways for SEO professionals
Understanding the principles of working memory and cognitive load theory can yield practical, actionable strategies for SEO professionals seeking to enhance their skills and efficiency.
Here are some tailored takeaways for SEOs:
Simplify new learning tasks
Rationale: Aligning with the principles of working memory, breaking down new tasks into simpler, more manageable components prevents cognitive overload and facilitates better understanding and mastery.
Example: Start small if you are learning to use a web crawler like Screaming Frog. Instead of attempting to analyze a 500-page website, begin with a 1-2 page website. This approach allows you to focus on understanding the tool’s functionalities without the overwhelm of excessive data, enhancing your learning efficiency and effectiveness. Additionally, if you want to write a Python script that evaluates your website against the competition, instead of starting with 10 competitors, start by getting your script to compare your site to just one competitor. Once you’ve completed that step then proceed to expand the tool.
Break down complex tasks
Rationale: In line with reducing extraneous and managing intrinsic cognitive load, dissecting a large, complex task into smaller parts aids in effective comprehension and execution.
Example: When analyzing a large website’s SEO strategy, deconstruct the task. Tackle one aspect at a time, such as examining backlink profiles, analyzing on-page SEO, or evaluating site structure. This segmented approach prevents overwhelm and cognitive overload, allowing for a clearer, more comprehensive understanding of the larger SEO strategy. Remember, feeling overwhelmed not only demotivates but also clouds your understanding, leading to a less precise and effective SEO analysis.
Pre-expose yourself to new ideas before watching complicated videos or articles
Before diving into new ideas in a lecture or YouTube video, pre-expose yourself to snippets of relevant information.
This approach makes the new information less unfamiliar when you encounter it during the lecture or video, reducing the cognitive load and making the learning process more efficient and effective.
Key takeaways for teaching and communication
Simplify and structure information
When teaching how to conduct keyword research, use clear, concise language and visuals, breaking down the complex steps. This approach makes it easier for learners to grasp and retain the information, ensuring the cognitive load is manageable and focused on the essential material.
Use real-world, relatable examples
Utilize actual case studies to demonstrate the impact of SEO strategies on search engine rankings and website traffic. These real-world examples help make abstract concepts concrete, aiding in comprehension and retention.
Incorporate visuals and interactive elements
Enhance learning by including visuals like infographics to represent the factors affecting SEO and interactive tasks such as SEO audits. These elements provide multiple ways for learners to engage with the material, boosting understanding and recall.
Be cautious of the curse of knowledge
As an expert, it’s easy to forget the challenges faced by beginners. Be careful not to skip basic but important information. For example, ensure learners have a solid understanding of basic SEO principles before diving into advanced topics like semantic search.
Build knowledge sequentially
Certain topics must be learned sequentially to ensure a solid foundation for more advanced concepts. For instance, learners should thoroughly understand on-page and off-page SEO before exploring more complex subjects like structured data.
Think of it like building a house. One cannot install windows and doors without first building the walls. Similarly, basic SEO concepts are the walls that support the more complex strategies and techniques.
A new approach to learning complex SEO concepts
Sometimes, the best way to advance one field is to cross-pollinate ideas gleaned from other fields. The field of learning research is a perfect example, offering groundbreaking insights that are highly practical and easy to implement for SEOs.
Embracing these proven learning strategies has revolutionized my approach to learning semantic SEO and staying current on what is working. While I’m still learning daily, these tools have enhanced my understanding.
By simplifying and structuring information, providing real-world examples, incorporating interactive elements, and building knowledge sequentially, these strategies can facilitate better understanding, retention, and application of SEO concepts.
The post How research on learning can help you understand advanced SEO concepts appeared first on Search Engine Land.
