An Idea to Explore: AI ‐Supported Digital Twin Laboratory for Risk‐Reduced and Immersive Biochemistry Education

ABSTRACT Biochemistry education faces persistent challenges in equipping students with the skills required to manage complex laboratory protocols, advanced instrumentation, and analytical procedures, particularly in high‐risk or resource‐intensive experimental settings. Traditional hands‐on training is constrained by limited access to equipment, safety concerns, and high operational costs, hindering institutions from providing realistic and scalable laboratory experiences. However, Digital Twin technology presents a transformative alternative. It creates simulations of real biochemical laboratories, providing immersive, scalable, and cost‐efficient environments unconstrained by physical limitations. This approach supports interactive, avatar‐mediated engagement that bridges conceptual knowledge with applied practice. In this study, we aimed to introduce BioDTLab, a custom Digital Twin framework for biochemistry education that integrates Virtual Reality, Internet of Things, robotics, data analytics, and an Artificial Intelligence (AI)‐driven Virtual Chat‐GPT Tutor. BioDTLab synchronizes physical and digital domains to provide high‐fidelity simulations of biochemical processes and instrumentation, while the AI‐driven Virtual Chat‐GPT Tutor evaluates student engagement, comprehension, and procedural accuracy. Our findings demonstrate that Digital Twin frameworks, such as BioDTLab, can redefine biochemistry education by making advanced experiential learning more accessible, safe, and scalable, while reducing reliance on costly physical resources. BioDTLab integrates immersive simulation, real‐time data synchronization, and AI‐driven feedback to provide a sustainable model for future science education that enhances conceptual understanding and practical competence. In addition, its adaptability makes it suitable for instructional models, such as the flipped classroom, where pre‐laboratory virtual practice can complement and enhance in‐person laboratory training.

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Publication Details

Journal
Biochemistry and Molecular Biology Education
Published
2026-09-30
DOI
https://doi.org/10.1002/bmb.70082
Primary Topic
Experimental Learning in Engineering
Type
article
Field-Weighted Citation Impact
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article

An Idea to Explore: AI ‐Supported Digital Twin Laboratory for Risk‐Reduced and Immersive Biochemistry Education

Jihoon Shin, Juhyung Son
Biochemistry and Molecular Biology Education
Experimental Learning in Engineering
article

An Idea to Explore: AI ‐Supported Digital Twin Laboratory for Risk‐Reduced and Immersive Biochemistry Education

Jihoon Shin, Juhyung Son
article en

Abstract

ABSTRACT Biochemistry education faces persistent challenges in equipping students with the skills required to manage complex laboratory protocols, advanced instrumentation, and analytical procedures, particularly in high‐risk or resource‐intensive experimental settings. Traditional hands‐on training is constrained by limited access to equipment, safety concerns, and high operational costs, hindering institutions from providing realistic and scalable laboratory experiences. However, Digital Twin technology presents a transformative alternative. It creates simulations of real biochemical laboratories, providing immersive, scalable, and cost‐efficient environments unconstrained by physical limitations. This approach supports interactive, avatar‐mediated engagement that bridges conceptual knowledge with applied practice. In this study, we aimed to introduce BioDTLab, a custom Digital Twin framework for biochemistry education that integrates Virtual Reality, Internet of Things, robotics, data analytics, and an Artificial Intelligence (AI)‐driven Virtual Chat‐GPT Tutor. BioDTLab synchronizes physical and digital domains to provide high‐fidelity simulations of biochemical processes and instrumentation, while the AI‐driven Virtual Chat‐GPT Tutor evaluates student engagement, comprehension, and procedural accuracy. Our findings demonstrate that Digital Twin frameworks, such as BioDTLab, can redefine biochemistry education by making advanced experiential learning more accessible, safe, and scalable, while reducing reliance on costly physical resources. BioDTLab integrates immersive simulation, real‐time data synchronization, and AI‐driven feedback to provide a sustainable model for future science education that enhances conceptual understanding and practical competence. In addition, its adaptability makes it suitable for instructional models, such as the flipped classroom, where pre‐laboratory virtual practice can complement and enhance in‐person laboratory training.

Biochemistry and Molecular Biology Education
Pohang University of Science and Technology (KR), National Taiwan University of Science and Technology (TW), National Taiwan University (TW), National Taipei University (TW)
Quality Education
Openalex Percentile: Top 15%
Experimental Learning in Engineering
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