Influence of algorithmic abstraction and mathematical knowledge on rates of dropout from Computing degree courses View Full Text


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Article Info

DATE

2018-12

AUTHORS

Raphael Magalhães Hoed, Marcelo Ladeira, Leticia Lopes Leite

ABSTRACT

This paper presents a study of rates of dropout from Brazilian degree courses, based on data provided by the National Institute for Educational Studies and Research “Anísio Teixeira” (INEP) and a case study carried out at the University of Brasilia (UnB). Dropout was calculated by tracking the status of each student between 2010 and 2014 in the eight major areas according to the classification of the Organisation for Economic Co-operation and Development (OECD), for the major area of Science, Mathematics, and Computing, and for the area of Computing. Data were analyzed in order to check for potential evidence regarding the influence on dropout of factors such as algorithmic abstraction, number of applicants per place, or the gender of students. A survey was also performed using online questionnaires for circumvented students from the courses of Bachelor of Computer Science, Degree in Computing, and Computer Engineering between 2005 and 2015. This survey revealed the influence on dropout of several factors and particularly institutional and vocational factors; it is clear that difficulties in algorithmic abstraction and mathematical knowledge influence rates of dropout from computing courses. More... »

PAGES

10

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13173-018-0074-2

DOI

http://dx.doi.org/10.1186/s13173-018-0074-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106085656


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