Learning object technology is viewed as a method for fast retrieval. This effort is on developing unique schemas for a targeted group to aid efficient retrieval. In this article, I study a user-centric model for developing tags for K-12 educators that is based on user needs, expectations, and problems. I use a combination of techniques from human performance technology and Sensemaking[R] to gather and analyze data from potential users. The resultant tag set is simple enough that researchers may envision a performance support system where users may quickly and easily tag and add objects to the system. This opens the door to the creation of systems designed for groups with homogeneous information needs, with unique metatags, populated largely with objects and information brought into the system by the users.