BACKGROUND: Improving students' problem-solving skills is one of the primary objectives of mathematics education. Problem-solving skills are closely related to the mathematical modeling process and the competencies required in this process, which are...
This study investigates how secondary students engage with an AI teachable agent (TA) during mathematics learning, with particular focus on learners whose performance declined after interacting with the TA system. Using a mixed-methods design, we an...
General-purpose AI already correctly solves most traditional assessment problems in first-year STEM education, and it continues to become more proficient with every release. This quiet superheating of familiar practices by increasing AI capabilities ...
According to productive failure (PF) theory, experiencing failure during problem-solving can enhance students' knowledge acquisition in subsequent instruction. However, challenging students with problems beyond their current capabilities may strain t...
In this work we present a C-MATH-NN framework that extends a C-MATH framework that was developed in recent years to include prediction using artificial neural networks (NN) in a way that is engaging, interdisciplinary and collaborative to help equip ...
Multi-objective production scheduling faces the problems of inter-objective conflicts, many uncertainty factors and the difficulty of traditional optimization algorithms to deal with complexity and ambiguity, and there is an urgent need to introduce ...
Learning disabilities affect a substantial proportion of children worldwide, with far-reaching consequences for their academic, professional, and personal lives. Here we develop digital twins-biologically plausible personalized deep neural networks (...
In the 21st century, the variety of instructional media for mathematics has significantly diversified. Generative AI (Gen-AI) is one technology that K-12 teachers can utilize for teaching mathematics. However, as a new instructional medium, Gen-AI pr...
This paper introduces fuzzy subalgebras of autometrized algebras and studies their properties. Also, we present fuzzy ideals of autometrized algebras and provide examples to illustrate our findings. We examine the homomorphisms of both the images and...
BACKGROUND: JU-algebras, an important class in abstract algebra, are extended here by incorporating fuzzy set theory to handle uncertainty in algebraic structures. In this study, we apply the concept of Q-fuzzy sets to JU-subalgebras and JU-ideals in...
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