Metadata as an Aggregation Final Model in Learning Environments: A New Perspective of Acquiring Knowledge in the New Millennium

Metadata as an Aggregation Final Model in Learning Environments: A New Perspective of Acquiring Knowledge in the New Millennium

Jorge Manuel Pires (University of Vigo, Vigo, Spain) and Manuel Pérez Cota (University of Vigo, Vigo, Spain)
Copyright: © 2016 |Pages: 24
DOI: 10.4018/IJTD.2016100103
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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.
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1. Introduction

Cognition has grown as a doctrine based on the various time-empirical observations, and hard data of field research evidence proof, that are mental structures underlying not only thought, but also emotion, as well as the very perception and interpretation of both, inner/internal and outer/external source information (Gardner, 1993). (Feuerstein, 1990) Whose multiple intelligence theory is based on cognitivism, asserts that mind consists of numerous fairly specific and independent computational mechanisms, and it is in this context that research on learning styles has also been promoted. Based on cognitive learning theory, the structure of content of the cognitive matter should be organized hierarchically. Relevant research (Gardner, 1993) has surely led to the conclusion that students learn mainly from the progressive and relation-linked construction of knowledge. This approach may well find applications in a Learning Management System (LMS) with a psycho-pedagogically driven learning path creation module (Gardner, 1993).

From constructivist point of view, the knowledge “built” by an individual and not broadcasted, is itself both a reflective and active process. The interpretation that the individual performs of the new experience is influenced by their prior knowledge introducing in social interaction, multiple perspectives of learning. Learning requires understanding of the whole and the parts, and should be understood in a global context. In this perspective, (Feuerstein, 1990) introduces one new dynamic, co-constructivism.

The theory of Structural Cognitive Modifiability (SCM) (Feuerstein, 1990), far transcends the purely cognitivist approach, and advocates that every individual is modifiable, a process that is inherent to the human species.

The knowledge creation and management have recently been seen as a means for enduring a sustainable competitive advantage. However, there is little known about knowledge or how it can be measure. Also, knowledge when used in research is rarely explicitly defined (Russ & Fineman, 1999). In spite of its being inaccessible for direct measurement, its power of influence over performance can be overwhelming (Hunt, 2003).

Assessing knowledge prior to testing performance of a complex task has the advantage of detecting and identifying deficiencies before they are revealed by errors in performance or other near-accident incidents. To be useful to a person, knowledge must not only be acquired, but also retained or remembered. It is not enough for teachers, instructors and trainers to be concerned only with the acquisition of knowledge by trainees or students. They must also be concerned with the retention of knowledge so that learners will have the knowledge available to them at later times. If the knowledge is acquired but does not influence behavior and cannot be retrieved from memory, e.g. is forgotten prior to its intended later use, then the earlier learning has failed to attain its instructional purposes.

The process of acquiring and retaining knowledge in memory is called learning and is a product of all the experiences of a person from the beginning of his/her life to the moment at hand. A computer analysis of the person’s answers and self-assessment certainly responses provide multidimensional scores about a person’s knowledge that remedy some deficiencies of knowledge assessment and achievement tests now employed (Hunt, 2003).

In addition, acquisition of new skills and knowledge is not only affected by an individual’s mental schemes or beliefs, but also by their interaction, cooperation and collaboration with others (Buzzi, 2012). By that, along with interaction, cooperation and collaboration has another important issue related to adaptability. In an e-Learning System it is primordial to predict and adapt to new situations and subjects, according to their cognitive capacities (Hunt, 2003). This perspective fits e.g. in teaching blind and deaf people alongside children with special educational needs.

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