Everyone’s interested in priming their habits. Self-help books and motivational manuscripts line e-bookstore shelves, giving eager readers advice on changing harmful habits or starting healthy ones. The market for these tips is huge for a simple reason: changing your habits can be really hard.
Habits are the building blocks of our lives, tiny patterns that make up how we move through the world as a person. Some of these patterns, like eating meals at regular intervals, serve us really well. Other patterns, like smoking when stressed, are less helpful.
Not everything a person regularly does can be called a “habit”. We call an activity a habit when it becomes less of a conscious effort. A habit is something so ingrained in your life that it’s almost unconscious.
Because of how deeply ingrained habits are, they can be really difficult to change. But on the other hand, the payoff can be substantial. When learning a complicated skill, it’s valuable to turn your practice into a habit.
This is one of the central principles behind the 21-Day Data Challenge. Data science is a complex skill, but it’s way easier to learn it when you turn your data practice into a regular habit.
There are a few tips that can help you a lot when you’re trying to learn a new habit. We’re here to provide you with that advice.
Here’s a brief overview of the principles we’ll be talking about in the article:
- Frequency over duration: it can be more effective to prioritize how often you practice something, rather than focusing on how long each practice session is.
- Growth mindset: try and remember to see slip-ups and failures as part of the learning process, and not as events that reflect your character or abilities.
- Find accountability buddies: trying to form habits alongside mutually supportive people can be easier than going it alone.
- Find ways to approach learning as a game: use fun apps, contests with friends, and mindsets to make habit-forming engaging and fun.
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Prioritize Frequency Over Duration for Habit-Forming
There’s no doubt that immersion in a subject will help you learn it on a deeper level, the level where it becomes a habit. That’s why it’s best for language-learners to travel to a country full of native speakers, for example. Or why Lighthouse Labs structures its web & data bootcamps in such an intensive way.
But when we’re not in school, and we’re going about our lives balancing other interests and responsibilities, time may be of the essence. Unless you have an empty schedule, you’ll probably need to make some decisions around when the best times to practice your new habit are.
When planning out your learning schedule, you should keep in mind the principle of frequency over duration. Let’s say you only have 3 and a half hours of the week to spare. Instead of organizing it so you spend all 3.5 hours learning one day a week, it’ll be more beneficial to spend half an hour seven days a week.
Keeping your practice regular will help you make it a habit. That’s why our Data Challenge is structured according to 15-30 minutes a day for 21 days, instead of 12 hours of challenges in one day.
Developing a Growth Mindset When Learning
According to game theorists, mindset plays an important role when it comes to learning new skills and building habits. There are two key mindsets:
- Fixed Mindset, in which a person considers their key characteristics, attributes, and habits largely stable and unchanging
- Growth Mindset, in which a person considers their characteristics, attributes, and habits mutable and influenced by the environment/choices they make
You can see where this is going. A person who approaches things from the perspective of a growth mindset will have a much more effective experience when trying to learn their new habits.
One place where a person’s mindset surfaces a lot is when the person experiences failure. For a person embodying a fixed mindset, failure will cause them to lose faith in themselves, and maybe give up. For a person with growth mindset, failure will be a part of the learning process, and a step along the path to growth.
If you fail at some points when trying to learn a new habit, try not to beat yourself up about it. Just think about how it’s a part of learning, rather than a barrier to learning. We can learn from our failures as much as, or more than, we can learn from our successes.
We’ve structured the 21-Day Data Challenge with growth mindset in mind (pun intended). Even if you miss some of the challenges, you’re encouraged to continue progressing through and trying to learn. It doesn’t matter if you don’t succeed at all 21 days, so long as you’re present and genuinely interested in building a data habit.
Creating Habits is Easier with Others
Everyone wants to be the hero, the person who climbs the mountain all by themselves. Fantasies of rugged victory aside, it should be understood that human beings are social creatures. We developed as a species that relies on a wide community for survival, splendour, and abundance.
A lot of things we do are much more effective when done as a group, and habit-forming is no exception. We can learn to build habits much more efficiently when we do it alongside others. There’s a reason why smokers choose accountability buddies when trying to quit!
When you’re trying to build a habit out of something complicated, your chances for success will be much higher if you find other like-minded people. That way you can all mutually cheer each other on, coax each other through mistakes, and praise each other through successes. You’ll be able to share tips and resources and keep each other accountable.
We were definitely aware of the social aspect of learning when we built the 21-Day Data Challenge. That’s why we put effort into creating a community forum, where participants can chat and help one another. It’s also why we encourage 21DDC participants to join or form teams.
Learn About the Gamification Learning Style
Gamification is a big word for a simple concept. It leans into the idea of “play”. People are, obviously, much more likely to participate in activities where they feel like they’re playing a game. Everyone would much rather play video games than go to work in an office, right?
Here’s where gamification comes into play: what if we took things commonly thought of as “work”, and made them more game-like? Encouraging people to work at things or learn by making things more game-like is at the heart of what gamification is about.
For a good representation of this, think about the popular app Duolingo. They take something commonly thought of as “work” (learning a language), and engage their audience through interactive, competitive challenges. They make learning a game.
There are ways you can integrate the idea of gamification into your own habit-learning. You’re probably already familiar with one of these ways: friendly competition with friends. This is a great way to combine the social aspect of learning with gamification.
There are also helpful tech tools that you can use to try and gamify your habits. One is called Habitica. This free app applies the fundamentals of RPGs to habit-forming methodologies. Input the habits you want to make or break, and earn points as you progress that you can put towards equipment for your character.
Gamification is the fundamental principle behind why the 21-Day Data Challenge is so fun and engaging. We take data science, a field of study that’s complex and often frustrating, and make it exciting through competitive and playful games. That’s why this year’s 21DDC is seeing over 9,000 participants try their hands at building data science habits.
Ready to build your own data science habit?