Research on the mechanism of improving environmental information cognition and environmental awareness in site ecological virtual laboratory

In the context of today's global ecological and environmental crises and challenges, environmental education is a super important for achieving sustainable development. Traditional environmental education often suffers from superficial understanding of environmental information and a lack of depth in environmental awareness. The purpose of this study is to guide students towards a deep cognition of environmental information and to enhance environmental awareness, while exploring the pathways. The study establishes a Site-scale Ecological Virtual Laboratory (SEVL) on the campus. Based on the Game-Based Learning (GBL) model, the study introduces three mediators: self-efficacy, learning motivation, and cognitive load, to construct a Partial Least Squares Structural Equation Model (PLS-SEM). The data for this study were collected from 146 Chinese students majoring in landscape architecture. According to the analysis results derived from PLS-SEM, we confirm that: (1) SEVL can effectively intervene in environmental education; (2) SEVL influences learning motivation which subsequently affects self-efficacy, ultimately leading to positive outcomes in environmental education (β = 0.040, p < 0.05, 95%CI[0.018,0.094]); (3) SEVL impacts cognitive load which then influences self-efficacy, resulting in effective outcomes in environmental education (β = 0.048, p < 0.05, 95%CI[0.012,0.088]). The study provides a reference for leveraging virtual laboratory in environmental education.

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Publication Details

Journal
Scientific Reports
Published
2026-01-15
DOI
https://doi.org/10.1038/s41598-026-35279-x
Primary Topic
Educational Games and Gamification
Type
article
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Research on the mechanism of improving environmental information cognition and environmental awareness in site ecological virtual laboratory

Lihua Xian, Wei Gao, Shengjie Hu, Yijun Liu et al.
Scientific Reports
Educational Games and Gamification
article

Research on the mechanism of improving environmental information cognition and environmental awareness in site ecological virtual laboratory

Lihua Xian, Wei Gao, Shengjie Hu, Yijun Liu, Pu Chen
article en

Abstract

In the context of today's global ecological and environmental crises and challenges, environmental education is a super important for achieving sustainable development. Traditional environmental education often suffers from superficial understanding of environmental information and a lack of depth in environmental awareness. The purpose of this study is to guide students towards a deep cognition of environmental information and to enhance environmental awareness, while exploring the pathways. The study establishes a Site-scale Ecological Virtual Laboratory (SEVL) on the campus. Based on the Game-Based Learning (GBL) model, the study introduces three mediators: self-efficacy, learning motivation, and cognitive load, to construct a Partial Least Squares Structural Equation Model (PLS-SEM). The data for this study were collected from 146 Chinese students majoring in landscape architecture. According to the analysis results derived from PLS-SEM, we confirm that: (1) SEVL can effectively intervene in environmental education; (2) SEVL influences learning motivation which subsequently affects self-efficacy, ultimately leading to positive outcomes in environmental education (β = 0.040, p < 0.05, 95%CI[0.018,0.094]); (3) SEVL impacts cognitive load which then influences self-efficacy, resulting in effective outcomes in environmental education (β = 0.048, p < 0.05, 95%CI[0.012,0.088]). The study provides a reference for leveraging virtual laboratory in environmental education.

Scientific ReportsVol. 16(1)
South China Agricultural University (CN)
Quality Education
Openalex Percentile: Top 90%
Educational Games and Gamification
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Research on the mechanism of improving environmental information cognition and environmental awareness in site ecological virtual laboratory — Lihua Xian, Wei Gao, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS