Global challenges of students dropout: a prediction model development using machine learning algorithms on higher education datasets

HIGHLIGHTS

• who: Amare Meseret Yihun and Simonova Stanislava from the University of, Faculty of Economics and Administration, Institute of System Engineering have published the paper: Global challenges of students dropout: A prediction model development using machine learning algorithms on higher education datasets, in the Journal: (JOURNAL)
• what: Early students' dropout prediction can help academic institutions to provide a timely intervention and apply appropriate planning and training to improve students' success rate.
• how: As described in the literature review section of this study these algorithms are used to classify students' performance into two categories Fail . . .
  

   

  

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