Evaluating student behaviour on the mathE platform - clustering algorithms approaches
Conference Paper
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abstract
The MathE platform is an online educational platform that
aims to help students who struggle to learn college mathematics as well
as students who wish to deepen their knowledge on subjects that rely
on a strong mathematical background, at their own pace. The MathE
platform is currently being used by a significant number of users, from
all over the world, as a tool to support and engage students, ensuring
new and creative ways to encourage them to improve their mathematical
skills. This paper is addressed to evaluate the students’ performance on
the Linear Algebra topic, which is a specific topic of the MathE platform.
In order to achieve this goal, four clustering algorithms were considered;
three of them based on different bio-inspired techniques and the k-means
algorithm. The results showed that most students choose to answer only
basic level questions, and even within that subset, they make a lot of
mistakes. When students take the risk of answering advanced questions,
they make even more mistakes, which causes them to return to the basic
level questions. Considering these results, it is now necessary to carry
out an in-depth study to reorganize the available questions according to
other levels of difficulty, and not just between basic and advanced levels
as it is.
This work has been supported by FCT Fundação para a Ciência e Tecnologia within
the R&D Units Project Scope UIDB/00319/2020, UIDB/05757/2020 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.
