Abstract
Active learning is a modern educational strategy that involves students in the learning process through diverse interactive and participatory activities. The MathE platform is an international online platform created to support students and lecturers in the Mathematics teaching and learning process. This platform offers a tool to aid and engage students, ensuring new and creative ways to encourage them to improve their mathematical skills. The study proposed in this paper refers to a comprehensive investigation of the patterns that may exist within the set of questions available on the MathE platform. The objective is to investigate how to evaluate the student’s opinions about the question’s difficulty levels based on the variables extracted from student answers collected through surveys applied among the platform’s users. Moreover, a comparative study between variables is performed using correlation and hypothesis tests. Furthermore, based on the results obtained for samples of different sizes, it was possible to define the most appropriate number of answers that should be considered to categorize the question’s difficulty level. The results demonstrated that the variables extracted could be used to carry out the question level, and 30 answers are the most appropriate number of questions that must be used to categorize the question level.
This work has been supported by FCT Fundação para a Ciência e Tecnologia within the R &D Units Project Scope UIDB/05757/2020, UIDP/05757/2020, SusTEC LA/P/0007/2021 and Erasmus Plus KA2 within the project 2021-1-PT01-KA220-HED-000023288. Beatriz Flamia Azevedo is supported by FCT Grant Reference SFRH/BD/07427/2021.
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Azevedo, B.F., de Souza, R.M., Pacheco, M.F., Fernandes, F.P., Pereira, A.I. (2024). Application of Pattern Recognition Techniques for MathE Questions Difficulty Level Definition. In: Pereira, A.I., Mendes, A., Fernandes, F.P., Pacheco, M.F., Coelho, J.P., Lima, J. (eds) Optimization, Learning Algorithms and Applications. OL2A 2023. Communications in Computer and Information Science, vol 1981. Springer, Cham. https://doi.org/10.1007/978-3-031-53025-8_21
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