Adaptation of Academic Knowledge Representation from Heterogeneous Educational Data Sources
DOI:
https://doi.org/10.25098/7.2.34Keywords:
Knowledge Representation, Decision Support Systems, Data Collection and ProcessingAbstract
Data in the modern era is diverse and always changeable. As a result of the accumulation of data from diverse systems has developed into a major issue or a hot topic in the process of adapting knowledge bases from various systems (i.e., Medical, Architectural and Educational systems, etc.). Furthermore, there are many academics who attempted to present a unified perspective of the information that is kept within any organization's relational, Extended Markup Language (XML), and Lightweight Directory Access Protocol (LDAP) data sources. Because of this, innovative approaches are required in order to collect, store, and analyze data from a wide variety of data sources in the most effective way that is feasible. Also, if the majority of data sources have already been included into the system that manages the data warehouse, there is still a demand for automated solutions that can generate a knowledge base for those responsible for making decisions in such fields. The primary objective of this research is to suggest a solution namely adapt academic knowledge representation from diverse educational data sources within a university and/or among other universities. This is done with the intention of sharing and making it easier for academic staff and students to gain access to knowledge that is helpful to them. The proposed system is developed using the V-model software development methodology, and research methodology used was mixed-methodology method. The proposed system was evaluated and proved to be a robust system that helped immensely with the tasks of Quality Assurance (QA) departments and also helped decision makers for universities to track the performance of their establishments.
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