Sprints are often associated with sports and agile methodology. You may have asked, what does it mean to use this strategy in my Bootcamp or online course? Learning Sprint helps teams to learn faster while not compromising the quality of learning. Because technology is moving fast, we should also learn faster to keep up. Let’s explore how you can use Learning Sprint in designing your Bootcamp, online courses, training, etc.
What is a Learning Sprint?
First, let’s define the word sprint. Google says it’s an act or short spell of running, cycling, or swim Telegraph Number Data ming at full speed. It’s a quick and fast activity where we aim to be at the end goal for a short period. Nowadays, Sprints are often associated with scrum or agile. Atlassian defined Scrum sprints as a short, time-boxed period when a scrum team works to complete a set amount of work. Since tech is moving so fast, tech teams should move and iterate faster too. Although learning sprints are related to Scrum sprints, we won’t dwell so much on that. Apparently, different industries–not just in tech–have to use the sprint model to perform and execute better. After defining sprints in two different contexts, let’s now define what Learning Sprint is. Data Central defines it as a collaborative, short, fast-paced learning endeavor as part of a greater, agile-oriented team effort.
Where Learning Sprint is mostly used?
Tech Bootcamps use Learning Sprints to prepare students on how tech teams work in the real world. These Boot Country List camps include coding, data science, machine learning, UX design, artificial intelligence, and even cybersecurity that works with Scrum, agile methodology, and technologies.Agile companies use learning sprints in their training. It’s very handy since they already know the concept of Scrum sprints. They also used Learning Sprints to train new employees to adapt to the concept of agile work. The three processes they used are Prepare-Sprint-Review. So far, it works well. It helps overloaded educators to still enhance their expertise despite the amount of work given to them.
