Depleting the curriculum: teaching digital platforms and curricular impoverishment

The paper aims at showing how curricular complexity tends to be depleted by the use of digital platforms based on the SCORM (Sharable Content Object Reference Model) standard, which was created with the main purpose of recycling content as it is supposed to be independent both from the context of learning and the supporting technology also deemed to be neutral, all surrounded by a rhetoric of innovation and “pedagogical” innovation. The starting point of the discussion is García Perez’s model of Traditional Didactics as a simple tool to show almost graphically that any ancient didactic model is far richer in terms of complexity than the linearity, in disguise most of the times but still visible under a not so sophisticated critical lens, of the interaction human-(reusable) content that is the basis of the SCORM standard. The paper also addresses some of the more common deliberate mix-ups related to those digital platforms, such as learning and teaching, content and learning object, systems of automatic teaching and learning management systems.

Using Neo4J geospatial data storage and integration

Online geographic-databases have been growing increasingly as they have become a crucial source of information for both social networks and safety-critical systems. Since the quality of such applications is largely related to the richness and completeness of their data, it becomes imperative to develop adaptable and persistent storage systems, able to make use of several sources of information as well as enabling the fastest possible response from them. This work will create a shared and extensible geographic model, able to retrieve and store information from the major spatial sources available. A geographic-based system also has very high requirements in terms of scalability, computational power and domain complexity, causing several difficulties for a traditional relational database as the number of results increases. NoSQL systems provide valuable advantages for this scenario, in particular graph databases which are capable of modeling vast amounts of inter-connected data while providing a very substantial increase of performance for several spatial requests, such as finding shortestpath routes and performing relationship lookups with high concurrency. In this work, we will analyze the current state of geographic information systems and develop a unified geographic model, named GeoPlace Explorer (GE). GE is able to import and store spatial data from several online sources at a symbolic level in both a relational and a graph databases, where several stress tests were performed in order to find the advantages and disadvantages of each database paradigm.