Development of a relevance index for the subjects in a study plan - Case study: Systems and Computer Engineering, Universidad Tecnológica de Pereira


Authors

DOI:

https://doi.org/10.22517/23447214.24454

Keywords:

Educational Data mining

Abstract

This document presents the development of an index that aims to quantify, according to some criteria known in graph theory, how relevant a subject is, taking into account its location in the curriculum, its number of credits, its prerequisites and the subjects dependents. The first thing was to model the academic plan using a graph, which considers only two things: the assigned credits and the prerequisites that must be met before taking the subjects. After having this model, graph theory algorithms were applied that allow to measure the importance of a subject with respect to the location in its curricular mesh (Centrality) and allow to give a measure of the importance of the subjects based on academic credits, its prerequisites and subjects depending on it (Neighborhood). It is important to note that the analysis presented is not intended to indicate that one subject is more important than another for the student's professional development, but rather to analyze, in an estimative way, which subjects contribute more to the connectivity of the program and academic flow by this network only taking into account the information found in the curriculum.The result obtained is a composite index, which allows visualizing the relevance degree of the subjects in the study plan.

Downloads

Download data is not yet available.

References

S.S. Ray. "Introduction to Graphs", in Graph Theory with Algorithms and its Applications, 2013, Springer, ISBN: 978-81-322-0749-8. Available: https://link.springer.com/ DOI: 10.1007/978-81-322-0750-4

https://doi.org/10.1007/978-81-322-0750-4

S. Guze. "Graph Theory Approach to the Vulnerability of Transportation Networks". Department of Mathematics, Gdynia Maritime University. 12 December 2019. Available: https://www.mdpi.com/1999-4893/12/12/270/htm

https://doi.org/10.3390/a12120270

C. Ding, X. He, P. Husbands, H. Zha, H. Simon. Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval. Association for Computing Machinery, 2002, New York, USA. Available: https://dl.acm.org/doi/10.1145/564376.564440. DOI: 10.1145/564376.564440

https://doi.org/10.1145/564376.564440

Ulrik Brandes. A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25(2):163-177, 2001.

https://doi.org/10.1080/0022250X.2001.9990249

Neo4j. "The Betweenness Centrality algorithm". Neo4j Labs Graph Algorithms library. Available: https://neo4j.com/docs/graph-algorithms

M. Benzi, E. Estrada, C. Klymkoc. "Ranking hubs and authorities using matrix functions". Linear Algebra and Its Applications, Elsevier, 2012.

https://doi.org/10.1016/j.laa.2012.10.022

Downloads

Published

2020-09-30

How to Cite

Guerrero-Erazo, J. G., Grandas -Aguirre, G. S., & Castaño-Gómez, J. D. (2020). Development of a relevance index for the subjects in a study plan - Case study: Systems and Computer Engineering, Universidad Tecnológica de Pereira. Scientia Et Technica, 25(3), 455–460. https://doi.org/10.22517/23447214.24454

Issue

Section

Sistemas y Computación