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Identifying student behavior in MOOCs using Machine Learning

Goals and challenges

Authors
  • Vanessa Faria de Souza

    Universidade Federal do Rio Grande do Sul, Brazil

    Author

  • Gabriela Perry

    Universidade Federal do Rio Grande do Sul, Brazil

    Author

Keywords:
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Abstract

This paper presents the results literature review, carried out with the objective of identifying prevalent research goals and challenges in the prediction of student behavior in MOOCs, using Machine Learning. The results allowed recognizingthree goals: 1. Student Classification and 2. Dropout prediction. Regarding the challenges, five items were identified: 1. Incompatibility of AVAs, 2. Complexity of data manipulation, 3. Class Imbalance Problem, 4. Influence of External Factors and 5. Difficulty in manipulating data by untrained personnel.

Author Biographies
  1. Vanessa Faria de Souza, Universidade Federal do Rio Grande do Sul, Brazil

    Graduate Program of Informatics in Education

  2. Gabriela Perry, Universidade Federal do Rio Grande do Sul, Brazil

    Graduate Program of Informatics in Education

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Published
2019-03-01
Section
Journal Articles
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Copyright (c) 2019 Vanessa Faria de Souza, Gabriela Perry

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How to Cite

de Souza, V. F., & Perry, G. (2019). Identifying student behavior in MOOCs using Machine Learning: Goals and challenges. International Journal for Innovation Education and Research, 7(3), 30-39. https://doi.org/10.31686/ijier.vol7.iss3.1318