Augmented reality (AR) has attracted significant attention and has become an important topic for many professionals and researchers. This is due to the capability of AR to offer a multitude of advantages that can enrich various domains of life. In education, AR technology has been increasingly used to create new learning experiences and transform real 3D (three-dimensional) or 2D (two-dimensional) objects into virtual elements, capturing users’ interests and motivation while fostering the growth of various human abilities and attitudes. The integration and use of educational games and applications based on AR in mathematics education have historically grown, and their impact has been beneficial for teaching mathematics and creating effective pedagogical scenarios. This paper presents an experiment we will undertake with our educational mobile application, GeoFormeAR, to animate a lesson on “Cylinder and Prism” and then compare it with a similar lesson delivered using the traditional approach in the second class. A post-test was administered to measure the students’ understanding and application of geometric concepts. Additionally, a questionnaire was distributed to collect the students’ perceptions of usability and engagement. The results of this study indicate a significant difference in performance scores between students using the GeoFormeAR mobile application and those learning geometry using traditional methods. Moreover, the questionnaire results reveal positive student perceptions regarding the usability and engagement of the GeoFormeAR mobile application. In conclusion, this study aims to broaden the scope of future vision on the conceptions and adoption of AR in mathematics teaching and learning.

Despite the challenges posed by the ongoing pandemic, there is a growing consensus that classroom assessment remains a more advantageous option for students than distance evaluation. The pandemic has catalysed developing robust information infrastructure and training qualified personnel to ensure educational continuity and assessment reliability. However, a recent comparative study on ENS maths students revealed no significant difference. This article examines the distance and face-to-face evaluations, presenting data from a comparative study during the pandemic.

Spectral clustering has established itself as a powerful technique for data partitioning across various domains due to its ability to handle complex cluster structures. However, its computational efficiency remains a challenge, especially with large datasets. In this paper, we propose an enhancement of spectral clustering by integrating Cover tree data structure to optimize the nearest neighbor search, a crucial step in the construction of similarity graphs. Cover trees are a type of spatial tree that allow for efficient exact nearest neighbor queries in high-dimensional spaces. By embedding this technique into the spectral clustering framework, we achieve significant reductions in computational cost while maintaining clustering accuracy. Through extensive experiments on random, synthetic, and real-world datasets, we demonstrate that our approach outperforms traditional spectral clustering methods in terms of scalability and execution speed, without compromising the quality of the resultant clusters. This work provides a more efficient utilization of spectral clustering in big data applications.

The didactic transposition is used to adapt scientific knowledge into taught knowledge for students through two steps, namely external and internal transposition. This process is crucial when applied to mathematics content as it enhances the understanding of complex concepts and makes knowledge more accessible to learners. To create effective lessons and scholarly knowledge objects, teachers must establish connections between their learned knowledge and the lesson structure. Metric and probabilistic metric spaces are two complex structures of knowledge that require understanding and teaching. This article explores the didactic transposition approach for teaching the concept of metric space, including probabilistic metric space, through external and internal steps of transposition, it provides two examples of transposing the Metric Distance notion in the Euclidean space, as well as two examples of the probabilistic metric space, aiming to transpose function distribution distance. It also outlines strategies for introducing metric spaces to students, referencing examples while acknowledging the teaching obstacles posed by this concept.

The innovation of intelligent tools and virtual worlds is progressing rapidly in the face of the rapid advancement of technology and digital revolutions. Virtual Reality (VR) and Augmented Reality (AR) are prime examples of such innovations. They have the potential to greatly improve and enhance various areas, particularly in educational settings. Since the 1960s, these technologies have undergone periodic development and renewals, from hardware to software. This paper aims to review the historical evolution of VR and AR, including recent advances, and their current applications in education, particularly in mathematics education. The paper will also address the challenges these technologies face in an educational context. This article reviews 30 papers published between 2015 and 2023 from three databases (ACM Digital Library, Scopus, and Web of Science), selected using the PRISMA method, to answer the following research questions: How have VR and AR evolved? What are the educational uses and applications of VR and AR? What are the challenges that could be addressed?