How to learn effectively?

Back in my school days, teachers, parents, and grandparents dished out advice about how to study and pass all exams. Their main message was to study on a regular basis. Problem was, they didn’t specify what "regular" meant, how long I should study for, or the best way to go about it. I followed their advice for a bit, but gradually, I found myself studying less and less. Weirdly, my grades didn't change much between my full-on and half-hearted study periods. This made me think regular study was pointless. Why not spend more time on fun stuff rather than slog through boring material, right? So, that's what I did for a good part of my school life, learning just enough to move from one grade to the next.?

After years of pretty much not caring about school, I hit high school and had to start thinking about my future job. I chose medicine, a field usually picked by top students, not average ones like me. Not to be put off, I looked into what it'd take to get into med school. The requirements were simple enough: you had to do really well in biology, chemistry, and maths in your final exams (or "matura" as we call them in Poland). This was a bit scary, because these subjects weren't my strongest, but I began to research how to reach this goal. The internet was a massive help, offering loads of tips about effective study techniques. Before I even started revising the subjects, I delved into these learning techniques. Given my average skills in these subjects and the sheer volume of stuff to learn, this was my entry point into the world of efficient learning, which has had a major impact on my life ever since. This journey helped me reach several milestones: passing those important exams, acing a stockbroker's exam, and learning how to code. In this article, I'll share my favourite learning techniques and give some real-life examples. Stick around to the end of the article, and I'll let you know if I got into med school or not.?

Don’t watch tutorials like a fool, do it yourself?

The concepts of Subject-Performed Tasks (SPTs) and Self-Performed Tasks (SPTs) pivot on specific methodologies of learning and memory recall. This approach is particularly helpful for learners in understanding and remembering complex ideas, procedures, and processes. The Subject-Performed Task (SPT) technique is based on the principle that individuals remember actions better when they perform them as opposed to simply observing or reading about them. Take, for example, a software developer who might recall a coding technique they've used more effectively than one they just read about in a tutorial. During my early days of learning Power BI, I found this technique handy. I watched tutorials and mimicked tasks performed by the instructor. This helped me understand the Power BI interface, how to get the results I wanted, and it spurred me to explore this tool more deeply. This method also came in handy when learning about Azure Data Factory and Azure Synapse.?

In contrast, a Self-Performed Task (SPT) goes a step beyond. It involves an individual not just performing an action but also inventing or tailoring it. A data analyst, for instance, could better remember a statistical analysis method if they developed their unique way of executing it. Circling back to the Power BI topic, I began modifying tasks performed by the instructor to achieve the outcome I was interested in, whether it was a different action of a chart, filter or DAX function, etc.?

A research paper by Lars Nyberg dives into the science underpinning these techniques. Nyberg's study shows that both SPTs and self-performed tasks encourage better memory recall than tasks described verbally, with self-performed tasks leading to even more remarkable memory retention. This is due to the cognitive processes engaged during task performance, which create more resilient and multifaceted memory imprints. In simpler terms, doing and creating result in stronger memories than just observing or reading. So, here's the main takeaway for learners: to boost learning and memory recall, try to perform tasks yourself whenever feasible, and better yet, try to customize or innovate how you execute these tasks. Not only will you learn more, but you'll remember it more vividly.?

Test yourself!?

Evaluation methods are key in measuring the effectiveness of a learning approach. Various assessment techniques serve distinctive purposes, and understanding how to effectively use them can significantly improve one's learning process.?

Elizabeth Marsh and Andrew Butler spearheaded research that highlighted two distinct types of assessments: summative and formative. Summative assessments quantify what learners know at the end of a specified learning period, while formative assessments offer ongoing feedback to help learners enhance their understanding throughout the learning process.?

The findings from Marsh and Butler's research indicate that formative assessments can notably improve long-term learning and retention. This is because formative assessments provide learners with regular feedback, which enables them to spot weaknesses and correct them before they become habits. Also, the continuous nature of formative assessments promotes regular recall and use of information, which is known to fortify memory.?

Applying this to software development, a formative assessment could be in the form of routine code reviews or pair programming sessions. These would enable developers to receive feedback on their coding techniques, comprehend their errors, and make improvements. In the realm of data analysis, formative assessments could include routine review meetings where analysts present their findings and get feedback on their analytical methods. I found this approach helpful when learning Python, SQL, and DAX – I started to answer questions posted on StackOverflow and the Power BI community. My initial attempts led to downsides on StackOverflow and corrective feedback from more experienced users. It was a bit harsh, but incredibly valuable.?

Conversely, summative assessments in software development could involve final project reviews or exams to test knowledge of a specific programming language or technology. For data analysis, it could be a final project report that requires the analyst to utilize a range of techniques learned throughout the project. I found this method helpful when prepping for interviews – I bought several courses on Udemy like "100 SQL Interview Questions," "Top Python Interview Questions," etc., and started working through them. Another case for this method was my learning journey with the Azure platform – I decided to pass all data-related exams from Microsoft, which was a great supplement to my day-to-day learning and work. I also used this technique during my prep for the final biology and chemistry exams – I invested a lot of time in solving final exams from previous years and pinpointing gaps in my knowledge. Same story for my stockbroker’s exam – I spent many hours solving exams from previous years.?

Marsh and Butler's research implies that while both formative and summative assessments have their roles, a larger focus on formative assessments can be more advantageous for long-term learning. This strategy can be especially helpful for software developers and data analysts, who frequently need to learn and remember a vast amount of complex, quickly evolving information. By integrating formative assessments into your learning approach, you can speed up your progress and reinforce your understanding in a way that leads to better retention and application of knowledge.?

Explain it to a child?

Named after the esteemed physicist Richard Feynman, the Feynman Technique is an effective method for learning and mastering intricate concepts. This approach is predicated on the idea that teaching or explaining a concept in straightforward language can significantly enhance understanding.?

The Feynman Technique is comprised of four steps:?

Choose a Concept: Pick the concept or topic you want to understand. This could be anything from object-oriented programming, unit tests, context transition in DAX, to stages of logical processing in SQL, and so on.?

Teach it to a Child: Attempt to explain the concept in a manner that a child could comprehend. This forces you to deconstruct the topic into its simplest components and strip away any jargon or complicated language.?

Identify Gaps and Return to The Source Material: While explaining, you might encounter areas that you can't express simply. These indicate gaps in your understanding. Revisit the source material to learn more about these areas until you can easily articulate them.?

Review and Simplify: Lastly, review your explanation and strive to simplify it further. Utilize analogies, diagrams, or other aids to make the concept as uncomplicated as possible.?

No specific scientific research zeroes in exclusively on the Feynman Technique. However, numerous studies have demonstrated that teaching others is an incredibly effective way to learn, a principle central to the Feynman Technique. For example, the 'Protégé Effect' suggests that people tend to augment their effort and comprehension of a subject when they teach it to others. It's the first learning technique I used during my preparation for biology and chemistry final exams. Explaining the subject first to myself and then to my schoolmates helped me memorize complex information from those areas. Much of this I remember to this day, even if I don't use it in my daily life and work. The Feynman Technique, with its emphasis on simplicity, comprehension, and teaching, is a potent tool for mastering complex concepts. By adopting this technique, learners can deepen their understanding and become more proficient in their respective fields. The effectiveness of this technique prompted me to publish articles about the technical stuff I work with. Initially, I was apprehensive because I am not a very seasoned programmer, but eventually, I realized that writing articles would afford me a better understanding of the topics I tackle daily.?

Mix it up?

Random practice, also known as interleaved practice, is a learning technique where varying skills or types of information are combined, or interleaved, during study or practice. This strategy diverges from blocked practice, which concentrates on one kind of skill or information at a time.?

Interleaved practice builds on the idea that blending different types of problems or diversifying the skills being cultivated can bolster learning and retention. Scientific research backs the efficacy of interleaved practice for long-term learning and transfer of skills. Compared to blocked practice, which might yield immediate performance improvements, interleaved practice has been found to lead to superior performance in the long run. This phenomenon, known as the "spacing effect," posits that information learned over multiple, spaced-out sessions is retained more effectively than information crammed into a single session.?

Interleaved practice also mirrors the variability and unpredictability of real-world scenarios more accurately, making it a more efficient strategy for preparing for these situations. I found this technique beneficial in all areas I needed to learn – I often intertwined chemistry exercises with biology theory or blended writing SQL queries with Power BI training. I genuinely like this method, simply due to its non-monotonous nature. I also used this method preparing for my stockbroker’s exam – mixing different topics like financial math and law. ?

While interleaved practice can be more demanding and might feel slower than blocked practice, this struggle often signifies more profound learning. The effort needed to recall and apply different skills can fortify memory and understanding, leading to more enduring and adaptable knowledge.?

Interleaved practice is a potent learning strategy that can augment the retention and transfer of skills. While it may feel more challenging in the short term, the long-term benefits for learners make it a worthy approach.?

Wrap it all up?

In conclusion, learning is a lifelong journey, and the techniques we choose to employ can significantly impact our rate of progress and retention. From the Subject and Self-Performed Tasks that enhance memory recall, the regular feedback cycle of formative assessments, the simple language technique of the Feynman Method, to the random practice of interleaved learning - each approach offers unique benefits.?

While there's no one-size-fits-all solution to learning, these techniques have proven effective across various fields and contexts, including in my personal experience with subjects like biology, chemistry, Python, SQL, DAX, Power BI, stockbroker’s stuff and many more. It's not about finding the 'perfect' method, but rather about exploring different techniques, understanding how they work, and then applying them to your specific learning needs. There are lots of different learning techniques which are not described in this article just due to the fact I decided to describe my favourites. I have proven track record of using them so it’s quite good reference.?

Learning is often a trial-and-error process, and it's important to remain patient with oneself, to not be afraid of making mistakes, and to consistently seek out opportunities for growth. By embracing these learning techniques, not only can we enhance our understanding and retention, but we can also transform the way we approach learning, making it a more enjoyable and fruitful experience. I encourage you to explore different techniques, because we're all different so methods good for me could be not relevant for you. I hope that by sharing these techniques, you too will find ways to enhance your learning experience and achieve your goals. After all, in the pursuit of knowledge, the journey is just as important as the destination.?

So, to circle back to the initial question - did I gain admission to medical school? The answer is yes, I did, but not for medicine, instead for pharmacy. I fell just a few points short of the admission requirement for medicine. During my year in pharmacy studies, I realized that the medical field wasn't for me, leading me to switch to finance where I became a stockbroker. After spending a few years in brokerage, I decided to transition into data analysis and began my career in business intelligence, which has been the best professional decision I've made to date. The common thread throughout all my career pivots has been the need for continual learning. Effective learning techniques have enabled me to achieve desired (or almost desired) results. Who knows what the future holds??