TriMElo: A Proposed Model for Evaluating Multi-Skills

• Fabiana Zaffalon Ferreira Federal University of Rio Grande (FURG) https://orcid.org/0000-0001-8777-9560
• André Prisco Vargas Federal University of Rio Grande (FURG)
• Ricardo Lemos de Souza Federal University of Rio Grande (FURG)
• Jean Luca Bez Regional Integrated University of Alto Uruguay and the Missions
• Neilor Tonin Regional Integrated University of Alto Uruguay and the Missions
• Rafael Penna Santos Federal University of Rio Grande (FURG)
• Silvia Silva da Costa Botelho Federal University of Rio Grande (FURG) https://orcid.org/0000-0002-8857-0221

DOI: https://doi.org/10.5753/cbie.sbie.2020.102

Abstract

The assessment methods that stand out the most are those that present a precise overview of the evolution of the multiple skills of students. In this way, we present the TriMElo model that aims to simultaneously estimate the general and ad sub-skills of students according to the skills involved in the problems. The model is concerned with verifying which are the sub-skills that are decisive for the error or correctness of the question so that its updates occur differently. To validate the model we use a database from the URI Online Judge platform. The empirical results show that the TriMElo model updates the sub-skills more smoothly, according to the wrong or correct answer.

Keywords: Skills, Elo, IRT, TriMelo

References

Andrade, D., Tavares, H., and Valle, R. (2000). Teoria da resposta ao item: conceitos e aplicações. In Simpósio Nacional de Probabilidade e Estatística (SINAPE).


Baker, F. (2001). The basics of Item Response Theory. ERIC.


Bez, J. L., Tonin, N. A., and Rodegheri, P. R. (2014). URI Online Judge Academic: A tool for algorithms and programming classes. In 2014 9th International Conference on Computer Science Education, pages 149–152.


Cazella, S. C., Behar, P., Schneider, D., da Silva, K. K., and Freitas, R. (2012). Desenvolvendo um sistema de recomendação de objetos de aprendizagem baseado em


competências para a educação: relato de experiências. In Brazilian Symposium on Computers in Education (Simpósio Brasileiro de Informática na Educaçãao-SBIE), volume 23.


Elo, A. (1978). The rating of chessplayers, past and present. Arco Pub.


Moreira, G. L., Holanda, W., Coutinho, J. C. d. S., and Chagas, F. S. (2018). Desafios na aprendizagem de programação introdutória em cursos de TI da UFERSA, campus Pau dos Ferros: um estudo exploratorio. Anais do Encontro de Computação do Oeste Potiguar ECOP/UFERSA (ISSN 2526-7574), (2).


Nojosa, R. T. (2002). Teoria da Resposta ao Item (TRI): modelos multidimensionais. Estudos em Avaliação Educacional, (25):123–166.


Park, J. Y., Cornillie, F., van der Maas, H. L., and Van Den Noortgate, W. (2019). A multidimensional irt approach for dynamically monitoring ability growth in computerized practice environments. Frontiers in psychology, 10.


Pasquali, L. (2018). TRI–Teoria de resposta ao item: Teoria, procedimentos e aplicações. Editora Appris.


Pelanek, R. (2016). Applications of the Elo rating system in adaptive educational systems. Computers Education, 98:169–179.


Prisco, A., Santos, R., Botelho, S., Tonin, N., and Bez, J. (2018). A multidimensional Elo model for matching learning objects. In 2018 IEEE Frontiers in Education Conference (FIE).


Reckase, M. D. (2006). Multidimensional item response theory. Handbook of statistics, 26:607–642.


Robins, A. (2010). Learning edge momentum: A new account of outcomes in cs1. Computer Science Education, 20(1):37–71.


Vargas, A. P., dos Santos, R. A. P., Bez, J., Tonin, N., and da Costa Botelho, S. S. (2019). Um modelo de mediação pedagógica para ambientes massivos. RENOTE-Revista Novas Tecnologias na Educação , 17(1):93–102.


Wauters, K., Desmet, P., and Van Den Noortgate, W. (2012). Item difficulty estimation: An auspicious collaboration between data and judgment. Computers & ducation,


58(4):1183–1193.