TOWARDS THE ENHANCEMENT OF AGLOS WITH SCORM AND XAPI

Generative learning objects (GLO) are considered the second generation learning objects. They represent reusable pedagogical patterns instantiable with different content. Auto-generative learning objects (AGLOs) are reusable patterns filled in with generated content obtained by meta‑programing and the use of random numbers to enable content diversity. Static content currently present in most of the Learning Management Systems (LMS), MOOCs etc. and there is the time for dynamic content models due to the web technology present in almost all gadgets the student use: laptops, tablets, mobile phones, watches etc. SCORM is a set of interoperability standards for the e‑learning objects in the context of LMSs. It is not related to instructional design or pedagogical concerns. Nowadays SCORM is considered obsolete because of the new standards of xAPI a.k.a. Tin Can API. With xAPI the learning experience is stored based on the "I did this" paradigm. So the student will not get a consolidated final mark where you will not be able to see its components but will have individual subject-action-object based records where its progress can be monitored and learning adjusted according to needs. In this context the AGLOs will be able to adopt this standard based on the competence tree model used in their organization. Recipes have been created for the organization and redundancy avoidance reasons of subjects, actions and objects. We will extract the verbs and objects from the competence tree model and to research the potential for the automation of the process. The approach will be experimented on the data structures and algorithms discipline competence tree developed in earlier research projects.