Systematic mapping review on student’s performance analysis using big data predictive model

  • S. M. Muthukrishnan
  • M. K. Govindasamy
  • M. N. Mustapha
Keywords: predictive analysis, student’s performance, big data, big data analytics, data mining, systematic mapping study.


This paper classify the various existing predicting models that are used for monitoring and
improving students’ performance at schools and higher learning institutions. It analyses all the
areas within the educational data mining methodology. Two databases were chosen for this
study and a systematic mapping study was performed. Due to the very infant stage of this
research area, only 114 articles published from 2012 till 2016 were identified. Within this, a
total of 59 articles were reviewed and classified. There is an increased interest and research in
the area of educational data mining, particularly in improving students’ performance with
various predictive and prescriptive models. Most of the models are devised for pedagogical
improvements ultimately. It is a huge scarcity in producing portable predictive models that fits
into any educational environment. There is more research needed in the educational big data.

Keywords: predictive analysis; student’s performance; big data; big data analytics; data
mining; systematic mapping study.

Journal Identifiers

eISSN: 1112-9867