42
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Predicting student dropouts using random forest

&

References

  • Government of India, “Unified District Information System for Education plus 2019-20,” 2020. Accessed: Jan. 16, 2022. [Online]. Available: https://dashboard.udiseplus.gov.in/#/home
  • J. J. Doll, Z. Eslami, and L. Walters, “Understanding Why Students Drop Out of High School, according to Their Own Reports: Are They Pushed or Pulled, or Do They Fall Out? A Comparative Analysis of Seven Nationally Representative Studies,” SAGE Open, vol. 3, no. 4, pp. 1–15, (2013) doi: 10.1177/2158244013503834
  • K. De Witte, S. Cabus, G. Thyssen, W. Groot, and H. M. van den Brink, “A critical review of the literature on school dropout,” Educational Research Review, vol. 10, pp. 13–28, (2013) doi: 10.1016/j.edurev.2013.05.002
  • N. Mduma, K. Kalegele, and D. Machuve, “A Survey of Machine Learning Approaches and Techniques for Student Dropout Prediction,” Data Science Journal, vol. 18, pp. 1–10, (2019). doi: 10.5334/dsj-2019-014
  • L. Kemper, G. Vorhoff, and B. U. Wigger, “Predicting student dropout: A machine learning approach,” European Journal of Higher Education, vol. 10, no. 1, pp. 28–47, (2020). doi: 10.1080/21568235.2020.1718520
  • M. Utari, B. Warsito, and R. Kusumaningrum, “Implementation of Data Mining for Drop-Out Prediction using Random Forest Method”, pp. 1–5, (2020).
  • L. Breiman, “Random Forests,” Machine Learning, vol. 45, no. 1, pp. 5–32, (2001). doi: 10.1023/A:1010933404324
  • S. Jayaprakash, S. Krishnan, and J. V, “Predicting Students Academic Performance using an Improved Random Forest Classifier,” pp. 238–243, (2020)
  • A. Verikas, A. Gelzinis, and M. Bacauskiene, “Mining data with random forests: A survey and results of new tests,” Pattern Recognition, vol. 44, no. 2, pp. 330–349, (2011). doi: 10.1016/j.patcog.2010.08.011
  • A. Peña-Ayala, “Educational data mining: A survey and a data mining-based analysis of recent works,” Expert Systems with Applications, vol. 41, no. 4, Part 1, pp. 1432–1462, (2014). doi: 10.1016/j.eswa.2013.08.042
  • K. Kalegele, “School dropout profiling and prediction approach using machine learning,” International Journal of Information Technology, Communications and Convergence, vol. 3, No. 4, pp. 245-258, (2020).
  • M. Cannistrà, C. Masci, F. Ieva, T. Agasisti, and A. M. Paganoni, “Early-predicting dropout of university students: an application of innovative multilevel machine learning and statistical techniques,” Studies in Higher Education, vol. 0, no. 0, pp. 1–22, (2021).
  • Y. N. Mnyawami, H. H. Maziku, and J. C. Mushi, “Enhanced Model for Predicting Student Dropouts in Developing Countries Using Automated Machine Learning Approach: A Case of Tanzanian’s Secondary Schools,” Applied Artificial Intelligence, vol. 36, no. 1, pp. 2071406-(433-451), (2022).
  • A. A. Mubarak, H. Cao, and W. Zhang, “Prediction of students’ early dropout based on their interaction logs in online learning environment,” Interactive Learning Environments, vol. 0, no. 0, pp. 1–20, (2020).
  • R. do Nascimento, R. Fagundes, and R. Souza, “Statistical Learning for Predicting School Dropout in Elementary Education: A Comparative Study,” Annals of Data Science, (2021).
  • J. Y. Chung and S. Lee, “Dropout early warning systems for high school students using machine learning,” Children and Youth Services Review, vol. 96, pp. 346–353, (2019). doi: 10.1016/j.childyouth.2018.11.030
  • S. Lee and J. Y. Chung, “The Machine Learning-Based Dropout Early Warning System for Improving the Performance of Dropout Prediction,” Applied Sciences, vol. 9, pp.1-14, (2019).
  • E. Maheshwari, C. Roy, M. Pandey, and S. Rautray, “Prediction of Factors Associated with the Dropout Rates of Primary to High School Students in India Using Data Mining Tools,” pp. 242–251, (2020).
  • V. Makhloga, K. Raheja, R. Jain, and O. Bhattacharya, “Machine Learning Algorithms to Predict Potential Dropout in High School,” pp. 189–201, (2021).

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.