During the last few months, I went through each of the seven Learning Label Android apps and made them faster, and more secure and intuitive. I completed a new release for the Learning Labels Search app. This app effectively bridges practitioners with learners and workers in the suite of Learning Label apps. In addition, the app allows producers of learning resources to get them to appear in a SERP, indexed as learning and job labels - each provides a full ROI (cost, time, and Skill Points).
As introduced in the original version, the app supports context and skill set searches and returns learning and job labels respectively. A SERP of these labels accentuates their huge value proposition: a succinct, sharp representation. Both labels fit on a smartphone without requiring scrolling left / right or up / down. On a dashboard, the labels fit side by side to aid a reviewer making line by line comparisons.
Skill Matching (part of the original app) takes the SERP and changes the order of skills appearing on the learning and job labels based on the results. This aids a reviewer in making line by line comparisons. A good example of the versatility in the learning and job labels format.
There is a new search log, where users access and submit previous searches. There is also an updated interface. Processing a search result is quicker.
The app includes functionality for logged-in users. Learners add learning labels (in a search result) to their collections, then access them from the Learning Labels Collections and web tasking app. Practitioners ‘clone’ or peer review the results.
Cloning a label means adding learning labels to a practitioner's workflow. The actual definition cannot be changed. But the practitioner uses the label for his own purposes (series, grading, lesson plans, training module, etc.).
A peer review is an effective skill by skill check of skills represented on a learning label. Many of the variables in the Skill Points algorithm get verified, with an opportunity to provide added context (a comment). The process is quick and accessible right from the search result.
At this stage, there is a sample data set. We are not selling SERPs (content), but a patent pending framework and system that is fully constructed. We are looking for publishers and creators of education and training resources and teachers, professors, and trainers to begin indexing resources to populate the search results.
If you feel this might be a fit, my team is more than willing to help with the process. It is possible to index many labels at once through a bulk upload or creating them one at a time. The latter is supported by a Skills Parser, which reads a block of content and produces a rank list of skills.
Contact my team at: partner@skillslabel.com