Article 2025

The Role of Haptic Interaction in Embodied Extended-Reality Learning: A Three-Level Meta-Analysis

Educational Psychology Review
Journal · Vol. 37 · Issue 4 · Art. 97
Abstract

While haptic interactions are increasingly integrated into embodied Extended-Reality (XR) educational systems, their impacts on students’ learning outcomes remain underexplored. To address this gap, a comprehensive three-level meta-analysis of 25 studies (50 effect sizes) was conducted to evaluate how haptic interactions in XR learning environments affect students’ learning (i.e., conceptual learning, operational performance, and user experience). Funnel plots and Egger’s regression method revealed no significant publication bias. Results indicated significant improvements in conceptual learning (g = 0.91, 95% CI: [0.40, 1.41]) and user experience (g = 0.48, 95% CI: [0.06, 0.90]) with haptic interactions, though effects on operational performance were non-significant. Moderator analyses explicitly identified key contextual drivers of efficacy: 1) Intervention time: Long-term (g = 0.79) and middle-term (g = 1.65) interventions outperformed short-term implementations; 2) Learning pace: System-paced (g = 0.97) outperformed self-paced; 3) Environment: Both classroom (g = 0.90) and lab (g = 0.87) settings yielded significant gains; 4) Subject domain: Health sciences (g = 0.79) and science technology (g = 0.62) yielded significant gains; 5) Haptic type: Kinesthetic feedback (g = 1.21) surpassed tactile approaches. These findings underscore haptic interactions’ potential to enhance educational outcomes through multi-sensory learning, while providing actionable strategies, such as prioritizing kinesthetic tools, to optimize XR-based learning. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

Keywords

Author Keywords

meta-analysis Embodied Learning Extended-Reality Haptic Interaction

Index Keywords

Author Affiliations
College of Education for the Future, Beijing Normal University, Beijing, China
School of Artificial Intelligence, Beijing Normal University, Beijing, China
College of Electrical Engineering, Northwest Minzu University, Lanzhou, Gansu, China
Funding & Acknowledgements
National Natural Science Foundation of China, NSFC
Grant: 62377004
Funding text 1: This research was funded by the National Natural Science Foundation of China (No.62377004), partially by Guangdong Education Science Planning Project 2023 (Higher Education Special Fund), Grant number 2023GXJK672 in China\u00A0and\u00A0Jiangxi Provincial Natural Science Foundation (20252BAC200199).; Funding text 2: This research was funded by the National Natural Science Foundation of China (No.62377004), partially by Guangdong Education Science Planning Project 2023 (Higher Education Special Fund), Grant number 2023GXJK672 in China and Jiangxi Provincial Natural Science Foundation (20252BAC200199).
National Natural Science Foundation of China, NSFC
Funding text 1: This research was funded by the National Natural Science Foundation of China (No.62377004), partially by Guangdong Education Science Planning Project 2023 (Higher Education Special Fund), Grant number 2023GXJK672 in China\u00A0and\u00A0Jiangxi Provincial Natural Science Foundation (20252BAC200199).; Funding text 2: This research was funded by the National Natural Science Foundation of China (No.62377004), partially by Guangdong Education Science Planning Project 2023 (Higher Education Special Fund), Grant number 2023GXJK672 in China and Jiangxi Provincial Natural Science Foundation (20252BAC200199).
Grant: 2023GXJK672
Funding text 1: This research was funded by the National Natural Science Foundation of China (No.62377004), partially by Guangdong Education Science Planning Project 2023 (Higher Education Special Fund), Grant number 2023GXJK672 in China\u00A0and\u00A0Jiangxi Provincial Natural Science Foundation (20252BAC200199).; Funding text 2: This research was funded by the National Natural Science Foundation of China (No.62377004), partially by Guangdong Education Science Planning Project 2023 (Higher Education Special Fund), Grant number 2023GXJK672 in China and Jiangxi Provincial Natural Science Foundation (20252BAC200199).
Natural Science Foundation of Jiangxi Province
Grant: 20252BAC200199
Funding text 1: This research was funded by the National Natural Science Foundation of China (No.62377004), partially by Guangdong Education Science Planning Project 2023 (Higher Education Special Fund), Grant number 2023GXJK672 in China\u00A0and\u00A0Jiangxi Provincial Natural Science Foundation (20252BAC200199).; Funding text 2: This research was funded by the National Natural Science Foundation of China (No.62377004), partially by Guangdong Education Science Planning Project 2023 (Higher Education Special Fund), Grant number 2023GXJK672 in China and Jiangxi Provincial Natural Science Foundation (20252BAC200199).
Natural Science Foundation of Jiangxi Province
Funding text 1: This research was funded by the National Natural Science Foundation of China (No.62377004), partially by Guangdong Education Science Planning Project 2023 (Higher Education Special Fund), Grant number 2023GXJK672 in China\u00A0and\u00A0Jiangxi Provincial Natural Science Foundation (20252BAC200199).; Funding text 2: This research was funded by the National Natural Science Foundation of China (No.62377004), partially by Guangdong Education Science Planning Project 2023 (Higher Education Special Fund), Grant number 2023GXJK672 in China and Jiangxi Provincial Natural Science Foundation (20252BAC200199).
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