Anna-Marie Burnett-Hughes – A1158003
Project Schedule
Research Purpose
The purpose of the research is to explore a system architecture that incorporates a NoSQL database to support the back-end function of an e-learning platform. This will contribute to the knowledge of overcoming problems with scalability and unstructured data within e-learning, as there is minimal documented evidence of such instantiations.
The aim of the research is to compare the effectiveness of a NoSQL database to that of the traditional RDBMS, within the system architecture of an e-learning platform.
The research question is:
How can a NoSQL database improve the function and scalability of an e-learning platform?
Evaluation Methodology
Primary evaluation of the end-product will be determined through the analysis of descriptive statistics. Further third-party data generation and evaluation will take place from three database experts within the university. This will be in the form of trial and qualitative interview, to gain feedback on the database and system architecture’s effectiveness as a solution to unstructured data and scalability for an e-learning platform.
Background
Dahdouh et al, (2019) successfully implemented a NoSQL database into their system architecture for e-learning, however primarily focused on Big Data analysis to learn the preference and direction of online learners, as oppose to the improvement of function or scalability. Similarly, Benito et al, (2014) deployed a cloud computing architecture for e-learning concentrating on data analytics to determine the learners’ skills, knowledge and behaviours. Alternatively, Saraubon, (2016) have successfully implemented cloud computing to stream content for the e-learning platform, which does reduce storage within the database, however a traditional RDBMS was implemented within their architecture.
The systematic literature review associated with this proposal indicated a gap in the published knowledge associated with NoSQL databases, in association with e-learning platforms to support standard function and scalability issues. NoSQL databases have been recognised to omit the ACID requirements of consistency (Vokorokos et al, 2016), which is a key factor as to why this approach may not have been implemented in research to date. However, NoSQL databases are evolving over time and certain systems now testify to being ACID compliant (Storey & Song, 2017).
Research Methodology
This research will implement a design and creation strategy to develop a NoSQL instantiation which supports the back-end function of an e-learning platform. The NoSQL product within an e-learning system architecture will be the main focus, to demonstrate a model developed using OrientDB, to compare to the traditional RDBMS with regards to function and effectiveness in terms of unstructured data and scalability.
Data will be collected with a quantitative approach, to measure the success of function and managing unstructured data and scalability, compared to documented evidence of RDBMS. Quantitative data will be analysed using descriptive statistics in Microsoft Excel for Office 365. Data will be presented in tables and charts to further support analysis and evaluation.
Professional, Legal & Ethical Issues
Within this research there are no significant ethical issues, as primary development includes no human participants. Evaluation includes only participants who are internal to the university. Therefore, a Block Ethical Release will be requested.
All systems, software and literature used within the research will be recognised in line with the Copywrite, Designs and Patents act 1988.
References: Benito, J. C., et al. (2014). ‘Using software architectures to retrieve interaction information in eLearning environments’, 2014 International Symposium on Computers in Education (SIIE), pp. 117-120.; Dahdouh, K. et al. (2019). ‘Large-scale e-learning recommender system based on Spark and Hadoop’, Journal of Big Data, 6(1).; Saraubon, K., Nilsook, P. and Wannapiroon, P. (2016). ‘System design of mobile augmented book’, International Journal of Interactive Mobile Technologies, 10(1), pp. 52-59.; Storey, V.C., Song, I. (2017). ‘Big data technologies and management: What conceptual modelling can do’, Data & Knowledge Engineering, 108, pp. 50-67.; Vokorokos, L., Uchnár, M., Lešcišin, L. (2016). ‘Performance optimization of applications based on non-relational databases’, 2016 International Conference on Emerging eLearning Technologies and Applications (ICETA), pp. 371-376.
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