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Educational Data Mining and Learning Analytics in Higher Education


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1 P.E.S's Modern College of Engineering, Pune, India
     

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The emerging fields of academic analytics also the educational data mining are rapidly producing new hypothesis for gathering, analyzing, and presenting student data. Different Area of Computer applications and also business administrations have addition significant standing value in higher education. Thus the kind of education, students turn in these areas depends on the geo-economical and the social demography. Thus the decision making of an institution in these area of higher education dependent on several factors like economic condition of students, geographical area of the institution, quality of educational organizations etc. To have a strategic move for the development of importing knowledge in this area requires understanding the behavior aspect of these parameters. Thus the scientific apprehension of these can be had from obtaining patterns or recognizing the attribute behavior from early academic years. Farther, applying data mining tool to the preceding data on the attributes known will throw better light on the behavioral view of identified patterns.


Keywords

Data Mining, Decision Tree Classification, Educational Data Mining.
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Abstract Views: 475

PDF Views: 9




  • Educational Data Mining and Learning Analytics in Higher Education

Abstract Views: 475  |  PDF Views: 9

Authors

Padma Mishra
P.E.S's Modern College of Engineering, Pune, India
Vaishali B.
P.E.S's Modern College of Engineering, Pune, India

Abstract


The emerging fields of academic analytics also the educational data mining are rapidly producing new hypothesis for gathering, analyzing, and presenting student data. Different Area of Computer applications and also business administrations have addition significant standing value in higher education. Thus the kind of education, students turn in these areas depends on the geo-economical and the social demography. Thus the decision making of an institution in these area of higher education dependent on several factors like economic condition of students, geographical area of the institution, quality of educational organizations etc. To have a strategic move for the development of importing knowledge in this area requires understanding the behavior aspect of these parameters. Thus the scientific apprehension of these can be had from obtaining patterns or recognizing the attribute behavior from early academic years. Farther, applying data mining tool to the preceding data on the attributes known will throw better light on the behavioral view of identified patterns.


Keywords


Data Mining, Decision Tree Classification, Educational Data Mining.

References





DOI: https://doi.org/10.25089/MERI%2F2018%2Fv12%2Fi1%2F180120