Metadata as an Aggregation Final Model in Learning Environments

Abstract

Knowledge is a concept - like gravity. You cannot see it, but you can observe its effects. Minimize knowledge is an invisible, intangible asset and cannot be directly observed. Many people and organizations do not explicitly recognize the importance of knowledge, in contrast to their more visible financial and capital assets (Pires, 2016). To measure in a proper and impartial way it is necessary to teach in an imaginative and diverse way providing students with the maximum amount of information on a given problem, by means of multiple paths (Pires, 2016). Measuring knowledge or academic performance changing the learning curves of different cognitive functions it would be something that would change completely the learning/study methods and the ways of monitoring the progression of any student. More, it would be possible to achieve individually objectives for certain cognitive functions, through a learning curve less extensive because we would focus the attention in the fundamental details (Pires, 2016). The computer analysis of the answers and self-assessment provides multidimensional scores about the subject knowledge (Hunt, 2003). As intelligent living creatures that we are, we are not isolated from the surround space. We live on it, breath from it and have influence on us in many ways. For a correct evaluation of our behavior's we need to include in the equation all the possible factors that have the condition to affect us. That is only possible if we are always connected to everything and everything is connected to us. (Chen, 2002) defines the generic metadata attributes as a tight relation of: space, time, contents persons, events and objects related between them. (Chen, 2002) also use a layer description to establish from the ground up the structure of a lesson and a course. If we can establish links between all the subjects above we will achieve the ultimate learning experience. This is the objective of this paper, demonstrate that it is possible based in a ten years research - phase I.

Semantically Enriching the Knowledge Payload of Knowledge Objects Through the Utilization of Knowledge Object Wrappers

“…It also provides the opportunity to discover and create connections or patterns between various KOs (Hodgins, 2002) and KOWs in relation to the different questions and meta-data relating to the questions that it encapsulates. It furthermore means that having such data available in conjunction with the utilisation of KOs in the organisation, should provide a competitive advantage to the members (Jing Cao et al, 2016;Mentzas, 2004;Pires & Cota, 2016) and the respective knowledge workers as part of the network of knowledge. It would also improve the knowledge workers' capacity to gain access to knowledge, solve problems and provide answers to questions (Al-Omari et al, 2016).…”