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Title:
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BIG DATA & LEARNING ANALYTICS: A POTENTIAL WAY TO OPTIMIZE ELEARNING TECHNOLOGICAL TOOLS |
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Author(s):
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Olga Arranz García, Vidal Alonso Secades |
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ISBN:
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978-972-8939-88-5 |
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Editors:
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Miguel Baptista Nunes and Maggie McPherson |
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Year:
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2013 |
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Edition:
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Single |
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Keywords:
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Learning Analytics, Big Data, Technological Elearning Tools, Learning Management System, Educational Data Mining |
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Type:
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Short Paper |
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First Page:
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313 |
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Last Page:
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317 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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In the information age, one of the most influential institutions is education. The recent emergence of MOOCS is a sample of the new expectations that are offered to university students. Basing decisions on data and evidence seems obvious, and indeed, research indicates that data-driven decision-making improves organizational productivity. The most dramatic factor shaping the future of higher education is Big Data and analytics. Big Data emphasizes that the data itself is a path to value generation in organizations and it is, also, a critical value for higher education institutions. The emerging practice of academic analytics is likely to become a new useful tool for a new era. Analytics and big data have a significant role to play in the future of higher education. This paper attempts an analytical practice about the use of e-learning technological tools to generate relevant information, for the teacher and the students who try to optimize their learning process.This combination of data-processing and analytical learning is an aid to improve significantly higher education and mark the path to follow in the new educational era. |
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