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Fuzzy Prediction: An Accurate Approach of Performance Prediction in Present Scenario of Higher Education


Affiliations
1 Department of Computer Science, BMM, Bhilai, Chhattisgarh, India
2 Department of IT, Rabindranath Tagore University, Bhopal., India
     

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Due to ease of application and capability to provide accurate and gradual responses, neural networks have become very popular over the recent past when it comes to classification problems. Also, data mining has been used extensively with good effect for decision making in educational system. Improved assessment technique is of paramount importance in understanding, analysing and assessing the progress in performance of the candidates in higher education sectors. Availability of a prediction tool to asses such progression accurately can be boon to organisations. In our work we proposed a model called Fuzzy decision tree model which uses the data of the student to analyse and evaluate their performance. The data include various factors such as previous year results, academic performance, sports interest, social activities etc. to predict their success rate. Use of such model will enable the organisation to identify students who are at potential risk and help them to develop best course of action which would eventually enhance the performance of the whole organisation.


Keywords

Fuzzy Decision Tree, Prediction, Higher Education.
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  • Fuzzy Prediction: An Accurate Approach of Performance Prediction in Present Scenario of Higher Education

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Authors

Jyoti Upadhyay
Department of Computer Science, BMM, Bhilai, Chhattisgarh, India
Pratima Gautam
Department of IT, Rabindranath Tagore University, Bhopal., India

Abstract


Due to ease of application and capability to provide accurate and gradual responses, neural networks have become very popular over the recent past when it comes to classification problems. Also, data mining has been used extensively with good effect for decision making in educational system. Improved assessment technique is of paramount importance in understanding, analysing and assessing the progress in performance of the candidates in higher education sectors. Availability of a prediction tool to asses such progression accurately can be boon to organisations. In our work we proposed a model called Fuzzy decision tree model which uses the data of the student to analyse and evaluate their performance. The data include various factors such as previous year results, academic performance, sports interest, social activities etc. to predict their success rate. Use of such model will enable the organisation to identify students who are at potential risk and help them to develop best course of action which would eventually enhance the performance of the whole organisation.


Keywords


Fuzzy Decision Tree, Prediction, Higher Education.

References