Open AccessMathematical Modelling and Big-Data Analytics for Student Performance
Author(s) -
K Purna Prakash,
K. Selvakumari
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1850/1/012017
Subject(s) - big data , computer science , data science , analytics , data analysis , enabling , learning analytics , mathematical model , data mining , mathematics , psychology , psychotherapist , statistics
Mathematical Modelling and Big-data Analytics are playing a vital role in educational databases. The result of integrating technology to predict student performance along with Mathematical Modelling and Big-Data Analytics helps us to make better decisions about teaching and learning. Modelling involves formulating real-life situations or to convert the problems in mathematical explanations to a real or believable situation. However, Mathematical modelling are an essential enabler in Big-data and Developments in Big-data analytics require not only more computing, but also new advanced mathematical approaches. In this paper, our main aim to see how Mathematical Modelling and Big-Data analytics help in students’ learning and how they relate to each other.