IoTs for Data Collection and Trends Prediction of Online Learning Courses

IF 1.1 Q2 MATHEMATICS, APPLIED Mathematics in Computer Science Pub Date : 2020-09-15 DOI:10.11648/J.MCS.20200504.11
A. Njeru
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Abstract

The rapid growth of educational data mining (EDM) is an emerging field in the academic world of research and studies focusing on collection, archiving, and analysis of data related to delivery methodology, quality of materials and student learning and assessment. The information analyzed informs the learning institution on how to improve learning experiences and how to run the institutional effectively. The people responsible for making decisions in the learning institution will able to make informed data-driven decisions. This paper explores the value of the Internet of Things (IoT) in capturing and mastering massive data for online courses to assess and identify typical learning scenarios for learners. We hope this would be a useful instrumental tool for the range of approaches in education institutions to help their struggling learners to succeed in the academic field.
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物联网用于在线学习课程的数据收集和趋势预测
教育数据挖掘(EDM)是学术界研究和研究的一个新兴领域,其重点是与交付方法、材料质量和学生学习和评估相关的数据的收集、存档和分析。所分析的信息为学习机构提供了如何改善学习体验和如何有效经营机构的信息。在学习机构中负责决策的人将能够做出明智的数据驱动决策。本文探讨了物联网(IoT)在捕获和掌握在线课程的海量数据方面的价值,以评估和识别学习者的典型学习场景。我们希望这将是一个有用的工具,为教育机构的一系列方法,以帮助他们苦苦挣扎的学习者在学术领域取得成功。
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来源期刊
Mathematics in Computer Science
Mathematics in Computer Science MATHEMATICS, APPLIED-
CiteScore
1.40
自引率
12.50%
发文量
23
期刊介绍: Mathematics in Computer Science publishes high-quality original research papers on the development of theories and methods for computer and information sciences, the design, implementation, and analysis of algorithms and software tools for mathematical computation and reasoning, and the integration of mathematics and computer science for scientific and engineering applications. Insightful survey articles may be submitted for publication by invitation. As one of its distinct features, the journal publishes mainly special issues on carefully selected topics, reflecting the trends of research and development in the broad area of mathematics in computer science. Submission of proposals for special issues is welcome.
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