Educational Data Mining to Support the Teacher's Decision-Making Process

  • Alana M. Morais UFCG
  • Joseana Fechine UFCG

Abstract


This paper presents an approach to identify which factors are most relevant in e-learning student’s performance. So, we use classification algorithms on study of relevant factors in the sample. The results showed that the score of student’s participation and good performance in your tasks influence the positive student’s results in the course.

References

Amorim, M.T. ; Cury, D. ; Menezes, C. S. (2011). Um sistema inteligente baseado em ontologia para apoio ao esclarecimento de dúvidas. In: XXII Simpósio Brasileiro de Informática na Educação, 2011, Aracaju. Anais do SBIE-2011.

Baker, R.S.J. (2011) Data Mining for Education. International Encyclopedia of Education, 3rd ed., edited by B. McGaw, P. Peterson, and E. Baker. Oxford, UK: Elsevier.

Chikalov, I. (2011). Average Time Complexity of Decision Trees. Springer. Disponivel em: [link]. ISBN 978-3-642-22660-1.

Corrigan, J. A. (2012). The implementation of e-tutoring in secondary schools: A diffusion study. Computers & Education. 59 (3) pages 925–936. Elsevier.

Russell, S., Norvig, P. (2004) Artificial Intelligence – A Modern Approach, Prentice-Hall, 2a Edição.
Published
2013-07-23
MORAIS, Alana M.; FECHINE, Joseana. Educational Data Mining to Support the Teacher's Decision-Making Process. In: WORKSHOP ON COMPUTING EDUCATION (WEI), 21. , 2013, Maceió/AL. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2013 . p. 478-483. ISSN 2595-6175.