Imagined a smart, dashboard to manage learning labels early in the development of the system. First designed and built the standalone learning label to set the standard as the uniform representation for a single unit of learning, then, got to think how to manage collections of them: a tiled draggable dashboard. An early version of the dashboard appears as a graphic in the 2016 patent application (currently under review by the USPTO).

A quote from IBM’s CEO saying we are “experiencing the ‘net flixifcation’ of learning” and the company adopts a “skills culture” motivated me to dramatically improve the learning labels dashboard (and build awareness of the Skills Culture growth mindset). It is unclear whether she was referring to Neflix’s suggestive AI algorithm or interface for quick decision making of a user. Either way works with the learning labels technology.

The basic foundation, database and user interfaces, is effectively built. The next step is getting content providers using learning labels to express learning expectations for their resources: books (print, online, or interactive), games (online, console, or gamification), activities (online, classroom, or other), projects (series of tasks), virtual reality, etc. This increases the value of an online search for education and training resources.

There are three separate versions of the dashboard (each includes functionality targeting the user):

  1. Teacher (Administrator). Recently covered this in admin version of the dashboard.
  2. Learner. Will update the dashboard version for learners, this is in queue. (Learners get free use of the application.)
  3. Search (SERP). This is an online, workable version: (Not meant to showcase the content at this stage, but the platform.)

An online search takes the results of a search and provides the dashboard as a SERP. From the dashboard, a user toggles between tiles (a ROI for a task), labels (expectations and links to resources), and credentials (reward) by double-clicking on elements – smart way to work with the learning process of a resource. Much of the dashboard functionality is a drag and drop interface; users drag items to initiate functions (some currently being built) or sort the items in a dashboard. Why the latter? This is an ideal way to make line-by-line comparisons between different learning resources. Finally, a user might also change from this tiled dashboard to a traditional text list.

The current search algorithm returns searches based on the information collected in a learning label: fields / subjects, skills, standards, audience, etc. (Give this a try, go to the search on the website. Use the search terms: ‘business’, ‘economics’, and ‘critical thinking’.) Needs to be more content providers using the system for effective searches. With content in place, ranking, suggestive AI, and personalized functionality gets added to the algorithm.

See this short video on how searches work with the learning labels system. If you think this platform might work with your learning content, contact: for a free consultation.