vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff6c153100000018d6100001000300 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.
Ritesh Kumar Pandey, Janhavi Obhan, Radhika Kotecha
K. J. Somaiya Institute of Technology, India
Data Analytics, Graduate Attributes, Management Systems, Outcome-based Education, Prediction and Recommendation
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| Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 13 , Issue: 2 , Pages: 2863 - 2871 )
Date of Publication :
January 2023
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296
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