System Architecture of Big Data in Massive Open Online Courses (BD-MOOCs System Architecture)


  •  Withamon Khajonmote    
  •  Kittipong Chinsook    
  •  Sununta Klintawon    
  •  Chaiyan Sakulthai    
  •  Wicha Leamsakul    
  •  Natchanok Jansawang    
  •  Thada Jantakoon    

Abstract

The system architecture of big data in massive open online courses (BD-MOOCs System Architecture) is composed of six components. The first component was comprised of big data tools and technologies such as Hadoop, YARN, HDFS, Spark, Hive, Sqoop, and Flume. The second component was educational data science, which is composed of the following four parts: EDM, ERS, AA, and S/II. The third component was a description of three basic elements of a big data system: data capture, management, and analysis. The fourth component was that MOOCs were classified as cMOOCs, xMOOCs, quasi-MOOCs, hMOOCs, and other related. The fifth component included the steps of MOOC development: design, delivery, and assessment. Finally, MOOCs present educational data science challenges such as analyzing student interactions, estimating dropout risk, grading, and making recommendations. Overall, the BD-MOOCs system architecture design was suitable at the highest level.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1927-5250
  • ISSN(Online): 1927-5269
  • Started: 2012
  • Frequency: bimonthly

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