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A huge amount of data that education systems produce increases every year and it is difficult by traditional techniques to manage, predict and analyze this data. This challenge can be addressed through mining large amount of data. It enables the institutions to use their present reporting trends to unmask hidden patterns and identify data relationships. Through this, institutions easily predict which students are likely to dropout, and their performance. Present paper conducts a detailed and exhaustive study on techniques and approaches implemented in education mining for predicting dropouts.<\/jats:p>","DOI":"10.4018\/ijicte.2019070107","type":"journal-article","created":{"date-parts":[[2019,5,14]],"date-time":"2019-05-14T18:00:17Z","timestamp":1557856817000},"page":"89-102","source":"Crossref","is-referenced-by-count":9,"title":["Analytical Approach for Predicting Dropouts in Higher Education"],"prefix":"10.4018","volume":"15","author":[{"given":"Garima","family":"Jaiswal","sequence":"first","affiliation":[{"name":"Indira Gandhi Delhi Technical University for Women, New Delhi, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9404-4519","authenticated-orcid":true,"given":"Arun","family":"Sharma","sequence":"additional","affiliation":[{"name":"Indira Gandhi Delhi Technical University for Women, New Delhi, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sumit Kumar","family":"Yadav","sequence":"additional","affiliation":[{"name":"Indira Gandhi Delhi Technical University for Women, New Delhi, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2432","reference":[{"key":"IJICTE.2019070107-0","doi-asserted-by":"publisher","DOI":"10.7763\/IJCTE.2015.V7.923"},{"key":"IJICTE.2019070107-1","doi-asserted-by":"crossref","unstructured":"Almayan, H., & Al Mayyan, W. 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