Content-Based Recommendation System for Programming Judges using Natural Language Processing and Deep Learning
DOI:
https://doi.org/10.15381/rpcs.v5i1.25802Keywords:
Programming Online Judges, Recommender Systems, Natural Language Processing, Deep LearningAbstract
In the field of education and technology companies, online judges play an important role in the development of programming skills because on these platforms students must solve challenges using specific programming languages. However, the sheer number of coding challenges available can be overwhelming for students, leading to frustration and loss of interest. To resolve this situation, recommender systems can be an effective solution. However, programming judges have not delved far enough into this area. Therefore, this research focused on evaluating six artificial intelligence techniques through a cloud-based architecture for the prediction of the level of difficulty from the statements of the problems to be coupled to a recommendation system. To validate the experiments, a real CodeChef programming judge was used and the experiments were evaluated through statistical tests. The results indicated that the BERT model is the best for predicting the level of the problems, which helps the recommendation system to improve the learning experience of the students in the online programming judges.
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Wilson Julca-Mejia, Herminio Paucar-Curasma
![Creative Commons License](http://i.creativecommons.org/l/by/4.0/88x31.png)
This work is licensed under a Creative Commons Attribution 4.0 International License.
THE AUTHORS RETAIN THEIR RIGHTS:
(a) The authors retain their trademark and patent rights, and also over any process or procedure described in the article.
(b) The authors retain the right to share, copy, distribute, execute and publicly communicate the article published in the Revista Peruana de Computación y Sistemas (for example, place it in an institutional repository or publish it in a book), with acknowledgment of its initial publication in Revista Peruana de Computación y Sistemas.
(c) Authors retain the right to make a subsequent publication of their work, to use the article or any part of it (for example: a compilation of their work, lecture notes, thesis, or for a book), provided that they indicate the source. of publication (authors of the work, magazine, volume, number and date).