Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/351945
Title: | A Classification And Prediction Algorithm In Data Mining To Predict Early Dropout Factors By Using Apm |
Researcher: | Saravanan,M |
Guide(s): | Jyothi,V L |
Keywords: | Computer Science Computer Science Artificial Intelligence Engineering and Technology |
University: | Sathyabama Institute of Science and Technology |
Completed Date: | 2021 |
Abstract: | Transformation of higher education is a major focus on addressing shift in education that responds to economic, social and cultural changes and are to be characterized by increased globalization, interdependency and development in different order among nations. Research in the areas of higher education mainly concentrates on demographics, investigation of various factors that indicate the performance, and apply research results to practical leadership training for social change in various demographics. newline newlineThe critical contributing factor to sustainable livelihoods and economic development of the nation is the major driving factor for the Higher Education in India. This also plays a pivotal role in cognitive understanding and wellbeing, also making every citizen socially conscious, self-aware, cultured and humane nation. In view of forthcoming Industrial Revolution 4.0 specified by the European nations and Society 5.0 concentrated by the Japanese, India aims to lead an increased proportion of employment opportunities with skilled labor having creativeness and multi-disciplinary nature, not only this, young generations are aspiring to become competitive utilizing the higher education opportunities. newline newlineAlthough there has been a drastic improvement in the research and development of Higher Education in India, there have been studies on the various factors that affect studentand#8223;s achievements in particular courses within Indian Universities. The factors that affect these achievements are collected basically to understand that the students are incapable of understanding the requirements essential for the higher education or the choice of wrong major. This leads to the early student dropout amongst the younger generation. This research is done focused towards higher education, to identify, classify and predict an individual newline newlinestudent performance through mining algorithms using certain quality attributes that could make them predict the student dropout ratio. newline newlineThe primary focus of this research stays in investigating, finding |
Pagination: | A5 |
URI: | http://hdl.handle.net/10603/351945 |
Appears in Departments: | COMPUTER SCIENCE DEPARTMENT |
Files in This Item:
File | Description | Size | Format | |
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01. title.pdf | Attached File | 328.26 kB | Adobe PDF | View/Open |
02. certificate.pdf | 729.85 kB | Adobe PDF | View/Open | |
03. acknowledgement.pdf | 521.58 kB | Adobe PDF | View/Open | |
04. abstract.pdf | 869.16 kB | Adobe PDF | View/Open | |
05. table of contents.pdf | 1.28 MB | Adobe PDF | View/Open | |
06. chapter 1.pdf | 5.87 MB | Adobe PDF | View/Open | |
06. chapter 2.pdf | 6.84 MB | Adobe PDF | View/Open | |
06. chapter 3.pdf | 6.48 MB | Adobe PDF | View/Open | |
06. chapter 4.pdf | 4.54 MB | Adobe PDF | View/Open | |
06. chapter 5.pdf | 3.25 MB | Adobe PDF | View/Open | |
06. chapter 6.pdf | 5.2 MB | Adobe PDF | View/Open | |
07. conclusion.pdf | 541.06 kB | Adobe PDF | View/Open | |
08. references.pdf | 3.94 MB | Adobe PDF | View/Open | |
09. curriculam vitae.pdf | 325.61 kB | Adobe PDF | View/Open | |
10. evaluation reports.pdf | 2.58 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 328.26 kB | Adobe PDF | View/Open |
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