Skills Culture SM is a growth mindset to learning, first introduced in 2016. The mindset is based on getting learners and practitioners to rally around learning and practicing skills properly. Perhaps the central ethos of the concept is: “Every experience is an opportunity to apply skills”. The mindset fits well with a suite of applications: Skills Based Approach (a methodology) and Skill Label (a system). All together, the applications and mindset create an effective platform for lifelong learning.
To understand Skills Culture, you must agree to three premises: 1) consider a broad interpretation of skills not limited to technical ones; 2) agree it is possible to define all learning in skills, their underlying methods and applications, and competencies; and 3) acquiring skills is for not only job or career preparedness, but also to make life more meaningful. So, a person builds a strong foundation in thinking skills and other transferable skills which serves as the basis for learning technical skills. And tracks soft skills like any other skill; their importance cannot be understated as they are applied in our every interaction and cannot be easily automated.
When you create an original concept, you think how it solves a specific problem – on a micro level. But later, as it gains momentum, you start to see how it solves bigger problems – on a macro level. The idea of learning labels is intriguing.
The genesis idea of learning labels was based on trying to reduce the amount of typing in a tasking application (Skills Based Approach). But the learning labels solve a bigger problem. There is not a standardized display (representation) of learning expectations. (For a point of reference, examples of standardized displays include a nutritional label for food or resume for professional evaluations.) There is no basis of comparison between traditional and emerging learning resources. Over the past couple of years, I realized these learning labels have even more potential.
I am creating new personalized grading with the learning labels technology. It is easy to think of new features for a product, the difficult part is narrowing the list and focusing on ones that add the most value. There are clear reasons why this feature adds value.
With learning labels, I work to convince practitioners we need to track learning on a discrete level – a task level. To accomplish this, there needs to be a mechanism and navigation to connect learning labels into a series – so they represent a project, learning plan, or course. I think this was the biggest influence in adding personalized grading into the platform. It is possible to create a series of labels, connect them based on performance, and grade each learner. Then, a learner navigates through the series based on their achievements.