ICTACT Journal on Soft Computing

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Data Mining for Enhancement of Graduate Attributes


Affiliations
1 Department of Information Technology, K. J. Somaiya Institute of Technology, India
     

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Analysing students’ progress and performance throughout their academic career is critical for boosting their employability. The required skillset and abilities to deal with the ever-changing workplace are increasingly demanded by employers. Graduates must be able to solve problems, communicate well, interact successfully, and think creatively, in addition to possessing good technological talents. Outcome-based education (OBE), which underlines these essential skills, are widely adopted by various educational institutions. Standard assessment measures of OBE have been defined by the Washington Accord as the 12 Graduate Attributes (GA) that can be utilized as relevant benchmarks. Therefore, it is impertinent to formulate an approach which provides a useful system for assessing, projecting, and improving a student’s overall academic and extracurricular progress using these Graduate Attributes. The system proposed in this paper applies Data Analytics to predict the progress of the students’ skillset and provide them with recommendations to adequately make them the best prospect for any engineering career. Components of the proposed approach have been compared with several baseline approaches and the experimental results demonstrate its efficacy.

Keywords

Data Analytics, Graduate Attributes, Management Systems, Outcome-based Education, Prediction and Recommendation
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Abstract Views: 72

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  • Data Mining for Enhancement of Graduate Attributes

Abstract Views: 72  |  PDF Views: 2

Authors

Ritesh Kumar Pandey
Department of Information Technology, K. J. Somaiya Institute of Technology, India
Janhavi Obhan
Department of Information Technology, K. J. Somaiya Institute of Technology, India
Radhika Kotecha
Department of Information Technology, K. J. Somaiya Institute of Technology, India

Abstract


Analysing students’ progress and performance throughout their academic career is critical for boosting their employability. The required skillset and abilities to deal with the ever-changing workplace are increasingly demanded by employers. Graduates must be able to solve problems, communicate well, interact successfully, and think creatively, in addition to possessing good technological talents. Outcome-based education (OBE), which underlines these essential skills, are widely adopted by various educational institutions. Standard assessment measures of OBE have been defined by the Washington Accord as the 12 Graduate Attributes (GA) that can be utilized as relevant benchmarks. Therefore, it is impertinent to formulate an approach which provides a useful system for assessing, projecting, and improving a student’s overall academic and extracurricular progress using these Graduate Attributes. The system proposed in this paper applies Data Analytics to predict the progress of the students’ skillset and provide them with recommendations to adequately make them the best prospect for any engineering career. Components of the proposed approach have been compared with several baseline approaches and the experimental results demonstrate its efficacy.

Keywords


Data Analytics, Graduate Attributes, Management Systems, Outcome-based Education, Prediction and Recommendation

References