Big Data Collection in Real Time and Improved Assessment System

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Big Data Collection in Real Time and Improved Assessment System

The National Open University of Nigeria (NOUN), an open and distance learning institution, and the largest in the West African Sub-region examination system was hitherto challenged by an era of missing scripts cum missing results. This challenge emanates from generation of Big Data from assessment of students learning outcomes which was too cumbersome to manage effectively. To handle the malaise an automation process was introduced to generate and collate the assessment Big Data in real time as a response to this major challenge and to improve the institutions effectiveness. Therefore, this paper explored the different sources and nature of collection of Big Data in NOUN students’ learning assessment in real time, discussed how the Big Data were integrated and utilized in real time to form a meaningful whole leading to eradication of the era of missing scripts/results and entrenchment of the institution’s effectiveness. It gave an overview of the issues involved, described the challenges, strategies and applications deployed to curb the challenges and to make the strategies more concrete. The paper employed exploratory research design and was guided by two research questions which were analyzed qualitatively. The result showed that the emerging sources of Big Data collection in real time emanating from NOUN departure from the traditional assessment approaches to the automated approaches have significant implications for the improved efficiency in assessment outcomes in NOUN. Moreover, for educational researchers, these Big Data were in some senses quite different from traditional evidence sources. It calls for new direction in research relating to assessment in the institution especially for participation in an emerging field of Education Data Science.

Keywords:      Assessment, Students’ learning, Automation, Big Data, Collection in real time

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Okonkwo Charity Akuadi - NOUN - The 44th IAEA Oxford UK 2018 - Full paper.docxDownload