# The impact of system interaction quality on learning outcomes in online virtual experiment teaching: the mediating role of extraneous cognitive load

**Authors:** Peng Yin, TingYu Sun

PMC · DOI: 10.3389/fpsyg.2025.1739300 · Frontiers in Psychology · 2026-01-21

## TL;DR

This study shows that better system interaction in online virtual experiments improves learning by reducing mental effort.

## Contribution

The study demonstrates how system interaction quality affects learning outcomes through extraneous cognitive load in virtual teaching.

## Key findings

- User interface and communication quality positively predict learning outcomes.
- Extraneous cognitive load partially mediates the effect of system interaction quality on learning outcomes.

## Abstract

This study investigates the effect of system interaction quality on learning outcomes in online virtual experiment teaching, with extraneous cognitive load serving as a mediating variable. Based on Cognitive Load Theory, a structural equation model was constructed to examine the relationships among user interface quality, communication quality, extraneous cognitive load, and learning outcomes. Using a cross-sectional questionnaire study, data collected from 610 valid samples were analyzed using SPSS 27.0 and AMOS 29.0. The results revealed that both user interface quality and communication quality significantly and positively predicted learning outcomes. Moreover, extraneous cognitive load partially mediated these relationships, indicating that high system interaction quality enhances learning outcomes not only directly but also indirectly by reducing unnecessary cognitive burdens. These findings extend the application of Cognitive Load Theory to virtual teaching contexts and provide empirical evidence for the “technology–cognition–learning” mechanism. Practically, the study offers actionable guidance for optimizing user interface design, improving communication performance, and enhancing instructional strategies to promote effective learning in online virtual experiment environments.

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12868159/full.md

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12868159/full.md

## References

59 references — full list in the complete paper: https://tomesphere.com/paper/PMC12868159/full.md

---
Source: https://tomesphere.com/paper/PMC12868159