Need-Supportive Immersive Learning Design Based on Self-Determination Theory: Effects on Learning Outcomes in a High-Stress Learning Context

Immersive learning environments are increasingly being implemented in high-stress contexts; however, many designs emphasize technological affordances rather than theoretically grounded motivational support. Guided by self-determination theory (SDT), this study developed a need-supportive immersive learning design model, referred to as self-determination theory–based virtual reality learning (VR-SDT), that intentionally integrates autonomy, competence, and relatedness into interactive, scenario-driven experiences. A randomized controlled study involving 84 ICU patients with coronary heart disease compared an immersive SDT-based VR learning condition (VR-SDT) with a non-immersive app-based SDT-informed instructional condition (App-SDT). Results indicated that participants in the VR-SDT condition achieved significantly higher knowledge ( F = 84.23, p < .001) and self-efficacy ( t = 7.96, p < .001) than those in the App-SDT condition. Anxiety reduction was also significantly greater in the VR-SDT condition (t = −8.86, p < .001). These findings suggest that an immersive learning design informed by SDT principles may support improvements in disease-related knowledge, self-efficacy, and anxiety in high-stress learning contexts, while providing theoretically grounded guidance for the design of immersive learning systems.

Authors

Institutions

Publication Details

Journal
Journal of Educational Computing Research
Published
2026-06-16
DOI
https://doi.org/10.1177/07356331261462360
Primary Topic
Motivation and Self-Concept in Sports
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Need-Supportive Immersive Learning Design Based on Self-Determination Theory: Effects on Learning Outcomes in a High-Stress Learning Context

Gwo‐Jen Hwang, Hui‐Chen Lin, Pei-Shan Tsai, Pei-Chin Tien
Journal of Educational Computing Research
Motivation and Self-Concept in Sports
article

Need-Supportive Immersive Learning Design Based on Self-Determination Theory: Effects on Learning Outcomes in a High-Stress Learning Context

Gwo‐Jen Hwang, Hui‐Chen Lin, Pei-Shan Tsai, Pei-Chin Tien
article en

Abstract

Immersive learning environments are increasingly being implemented in high-stress contexts; however, many designs emphasize technological affordances rather than theoretically grounded motivational support. Guided by self-determination theory (SDT), this study developed a need-supportive immersive learning design model, referred to as self-determination theory–based virtual reality learning (VR-SDT), that intentionally integrates autonomy, competence, and relatedness into interactive, scenario-driven experiences. A randomized controlled study involving 84 ICU patients with coronary heart disease compared an immersive SDT-based VR learning condition (VR-SDT) with a non-immersive app-based SDT-informed instructional condition (App-SDT). Results indicated that participants in the VR-SDT condition achieved significantly higher knowledge ( F = 84.23, p < .001) and self-efficacy ( t = 7.96, p < .001) than those in the App-SDT condition. Anxiety reduction was also significantly greater in the VR-SDT condition (t = −8.86, p < .001). These findings suggest that an immersive learning design informed by SDT principles may support improvements in disease-related knowledge, self-efficacy, and anxiety in high-stress learning contexts, while providing theoretically grounded guidance for the design of immersive learning systems.

Journal of Educational Computing Research
National Taiwan University of Science and Technology (TW), Mackay Memorial Hospital (TW), National Taichung University of Education (TW), Taipei Medical University (TW), Yuan Ze University (TW)
National Science and Technology Council
Quality Education
Openalex Percentile: Top 5%
Motivation and Self-Concept in Sports
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.