There is now Learning Labels Search in the portfolio of apps on Google Android. The application accepts a search term and returns learning and jobs labels as a SERP. There is functionality for a valid, logged in user to also clone and peer review labels in the SERP and navigate between the different apps.

The search is an algorithm to accept any set of search terms – skills, fields, disciplines, job track, degrees, traits, etc. – and returns the labels. (Like on the web application, a later version will also include an advanced skills-based search with skills matching.)

A value proposition with the learning and job labels is a representation to make quick basis of comparison decisions (by rendering them in a common format). Each label fits ideally on the screen, no need to scroll up/down or left/right.

A label is meant to define a unit of learning, so there should only be a single label per task or experience. Cloning a label means to add a label into a collection, so a practitioner gets all the features of the label (assigning into pathways, users, projects, etc.) but cannot change the actual definition. (This is less stringent with job labels because how fast the requirements change and are different among employers.)

A strong feature of the Learning Labels Search app is to do a peer review. A practitioner accesses the map interface (to conduct the review) by clicking on a button on the label. Then, in a matter of seconds, verifies the review on a skill-by-skill basis. (Alternatively, the practitioner does the review while doing the resource. The application collects the data.)

One objective with the adoption of the learning labels application is sharing them among learning practitioners (peer to peer), publishers of learning resources with learners and practitioners, and practitioners with learners. Learning Labels Search gets the labels on mobile devices to share with intended audiences.

There are not enough labels in the system to search and get a qualified result at this stage. Though, the search algorithm, framework, and design all work with a sample data set. Two reasons why we are releasing at this stage:

1) incentivize the adoption of the technology

2) already have the system designed and built (indexing the labels should be a quick process)

If your organization /  team like what they see with learning and job labels, contact our team (info@skillslabel.com) to learn how to get learning and/or job labels referencing your resources and content.

Access Learning Labels Search app in Google Play or contact us to request by email.