Algoritmos de Reconhecimento de Dígitos para Integração de Equações Manuscritas em Sistemas Tutores Inteligentes

• Sergio Chevtchenko UFPE
• Luiz Rodrigues UFAL
• Daniel Rosa UFRPE
• Filipe Cordeiro UFRPE
• Ruan Carvalho UFRPE
• Everton Souza UFRPE
• Thales Vieira UFAL
• Diego Dermeval UFAL
• Ig Ibert Bittencourt UFAL / Escola de Educação de Harvard
• Seiji Isotani Escola de Educação de Harvard
• Marcelo Marinho UFRPE
• Valmir Macario UFRPE

DOI: https://doi.org/10.5753/sbie.2023.235237

Abstract

Intelligent Tutoring Systems (ITSs) have been widely used to assist in mathematics learning. However, the difference in input methods between ITSs, which require keyboard usage, and the standard practice of handwriting, can lead to usability issues and hinder learning. To overcome this limitation, recent research has explored the recognition of handwritten characters on paper as input for ITSs. However, there is a knowledge gap regarding the performance of advanced digit recognition algorithms in the context of basic mathematical operations. This article compares four state-of-the-art algorithms for digit recognition in addition and subtraction math problems. The results reveal that the BTTR algorithm achieved the best performance in terms of accuracy, while the SAN algorithm demonstrated a good balance between accuracy and recognition speed. These findings are relevant for researchers and developers in selecting the most suitable algorithms for the development of ITSs based on handwritten input.

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