A Method to Predict At-risk Students in Introductory Computing Courses Based on Motivation

  • Pablo Schoeffel Universidade do Estado de Santa Catarina
  • Vinicius Faria Culmant Ramos UFSC
  • Raul Sidnei Wazlawick UFSC

Resumo


Despite being a problem reported in a long time, the high rate of dropout and failure in computing courses remains a problem. Although there is a strong relationship between the motivation and the students outcome, few works use the motivation as a factor to identify students at risk. This work presents and evaluates a method to identify features that allow predicting at-risk students in introductory computing courses, based on four main components: pre-university factors, initial motivation, motivation through the course, and professor perception. The method created, named EMMECS, was applied with 245 students from different programs in four different universities in southern Brazil. We carried out several simulations of prediction, using ten different classification algorithms and different datasets. As a result, using support vector machine and AdaBoostM1 algorithms, we identified on average more than 80% of students that would fail, since the first week of the study. The results show that the proposed method is effective compared with related works and it has as advantages its independence of programmatic content, specific assessments, grades, and interaction with learning systems. Furthermore, the method allows the weekly prediction, with good results since the first few weeks.

Palavras-chave: At-risk Students Prediction, Introductory Computing Courses, Motivation

Referências

Schoeffel, Pablo. Cechinel, Cristian. Ramos, Vinicius C.F. Wazlawick, Raul (2020). A Method to Predict At-risk Students in Introductory Computing Courses Based on Motivation. The ACM Transactions on Computing Education (TOCE). “unpublished.
Publicado
24/11/2020
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SCHOEFFEL, Pablo; RAMOS, Vinicius Faria Culmant; WAZLAWICK, Raul Sidnei. A Method to Predict At-risk Students in Introductory Computing Courses Based on Motivation. In: S WORKSHOPS DO CONGRESSO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (WCBIE), 9. , 2020, Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 41-41. DOI: https://doi.org/10.5753/cbie.wcbie.2020.41.