Work

Multi-group comparison of STEM education approaches

Year: 2025

Type: article

Abstract: Background Immersive technologies, such as Mixed Reality (MR), are increasingly integrated into STEM education to enhance student motivation and learning outcomes. However, the effectiveness of MR compared to traditional methods, particularly across gender and curriculum stages, remains underexplored. Aims The research aims to compare the effectiveness of traditional and MR-supported STEM education, examining the roles of autonomy, motivation, class participation, and creativity across gender and junior/senior curriculum stages. Sample(s) The experimental setup compared traditional paper-based notes with an MR application (Microsoft HoloLens) for teaching 3D geometry. Randomization was conducted individually, with 281 secondary school students assigned to traditional (n = 116) or MR-supported (n = 165) groups using a random number generator, balanced across gender and curriculum stage (junior: ages 13–14 or below; senior: ages 15–16 or above). Methods A 3D geometry topic was taught using traditional paper-based notes or an MR application via Microsoft HoloLens. A 17-item questionnaire, based on Self-Determination Theory, measured autonomy, motivation, participation, creativity, and learning effectiveness on a 5-point Likert scale. Multi-group analysis and t-tests assessed differences across gender and curriculum stages, with reliability and validity confirmed via Cronbach's alpha, composite reliability, and average variance extracted. Results MR-supported instruction significantly enhanced learning effectiveness and motivation for junior students (p < 0.05) and learning effectiveness, motivation, participation, and creativity for senior students (p < 0.05). Male students preferred MR, showing reduced gender disparities compared to traditional methods, where females scored higher. Conclusions MR-supported instruction boosts motivation and effectiveness, particularly for seniors, and narrows gender gaps. Educators should tailor MR integration to enhance engagement across diverse student groups.

Source: Learning and Instruction

DOI: 10.1016/j.learninstruc.2025.102305

Authors: Yuk Ming Tang, Yee Kiu Chan, Ran Wei, G.T.S. Ho

Institutions: Hong Kong Polytechnic University, Baise University, Hang Seng University of Hong Kong

Language: English

Topic: Augmented Reality Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDGs: Quality education, Reduced inequalities

Open Access status: hybrid

Estimated APC paid: $4,580