Development of a virtual reality model for STEM education

Frontiers in Education, 2026

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.3389/feduc.2026.1863366
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

Immersive virtual reality (VR) enables interactive three-dimensional representations of abstract scientific phenomena, but its educational value depends on how it is integrated into instructional practice. This study developed and longitudinally evaluated a VR-supported instructional model for undergraduate electromagnetism. The baseline cohort comprised 193 students from two physics-related programmes; 187 completed the immediate post-test (T2), and 181 completed the two-month follow-up (T3). The intervention consisted of four 40–50-minute instructional sessions delivered over two weeks, with approximately 5–10 min of active VR interaction per participant during each session. The instructional sequence combined guided exploration, manipulation of a current-carrying loop in a magnetic field, prediction tasks, instructor-facilitated discussion, and structured reflection. Repeated-measures analyses based on 181 complete cases showed significant changes over time in electromagnetism achievement, cognitive processing, learning motivation, and perceived learning outcomes (all p < .001; partial η p 2 = .385–.465 ) . Cognitive processing, learning motivation, and perceived learning outcomes remained relatively stable from T2 to T3, whereas electromagnetism achievement showed a small descriptive decline while remaining above its baseline mean. Structural equation modelling using T2 data ( n = 187) showed positive associations between perceived visualisation quality and cognitive processing ( β = .61), cognitive processing and learning motivation ( β = .57), and learning motivation and perceived learning outcomes ( β = .63). The sequential indirect association between perceived visualisation quality and perceived learning outcomes through cognitive processing and learning motivation was also significant [ β = .22, 95% CI (.142,.319), p < .001]. Given the single-group design and concurrent measurement of the SEM constructs, the findings indicate within-cohort temporal changes and theoretically consistent associations rather than causal effects of VR.