RESEARCH STATEMENT

Research Statement

Research Agenda
My research agenda continues to evolve and expand, focusing on three interconnected areas that are at the forefront of educational technology and learning sciences:

(1) Inclusive and Immersive e-Learning Design,
(2) Adaptive Learning Systems in Immersive Environments,
​(3) Assessment Design through Learning Analytics and AI.

Inclusive and Immersive e-Learning Design

The importance of personalization in digital learning environments remains a central focus of my research, particularly in ensuring these environments are inclusive and accessible to all learners. My work addresses the challenges of creating digital learning experiences that accommodate diverse learner needs, including neurodiverse populations.

  • Framework Development: My publications in high-impact journals such as Virtual Reality (SCIE, IF5 = 5.4) and Research in Learning Technology (IF5 = 2.6) demonstrate my commitment to advancing theoretical and design frameworks for inclusive learning. The study in Virtual Reality revisits multimedia learning design principles, contextualizing them for neurodiverse learners in immersive environments. Meanwhile, the study in Research in Learning Technology discusses practical implementations of immersive technologies to cater to diverse cognitive, emotional, and social learning needs.
  • Empirical Insights: My work in Journal of Autism and Developmental Disorders (SSCI, IF5 = 4.2) empirically evaluates adaptive prompts in VR-based social skills training for autistic adolescents, demonstrating how immersive learning environments can address specific challenges faced by neurodiverse learners.
  • Community Engagement: As the founder of the Korean EdTech/Learning Sciences Researcher Network (KELS), I have also facilitated discussions and collaborations around inclusivity in educational technology, creating a platform for diverse perspectives and shared expertise.
  • Broader Impact: These contributions not only redefine immersive learning design but also inform educators and policymakers on how to integrate adaptive and accessible features into digital learning environments. My recent conference presentations at AERA and AECT highlight the scalability and applicability of these frameworks.

Adaptive Learning Systems in Immersive Environments

Building adaptive learning systems within immersive environments is a cornerstone of my research, focusing on how these systems can dynamically respond to learners’ needs and optimize their learning trajectories. By integrating Artificial Intelligence (AI) and learning analytics, I aim to create systems that provide real-time, evidence-based scaffolding tailored to individual learners’ cognitive and emotional states.

  • AI-Powered Adaptivity:
    My research examines how AI-driven tools enhance adaptivity in immersive learning systems. For example:
    • In the International Journal of Educational Technology in Higher Education (SSCI, IF5 = 9.9), I investigated peer learning dynamics in gamified asynchronous courses, demonstrating how adaptive features like gamified elements and virtual agents can foster collaboration and engagement.
    • My meta-analysis in Educational Psychology Review (SSCI, IF5 = 12.5) synthesized findings on the effectiveness of AI-based virtual agents in improving learning outcomes, offering a comprehensive perspective on the potential of adaptive systems across diverse educational settings.
  • Generative AI in Immersive Learning Design:
    Generative AI plays a pivotal role in my research on adaptive systems. My publication in Technology, Knowledge, and Learning (IF5 = 3.5) outlines how generative AI can enhance adaptivity in digital games and learning systems, offering personalized learning pathways and content generation. I have further explored this theme in:
    • Online Learning (IF5 = 4.4), where I analyzed undergraduate students’ dual perspectives on generative AI, focusing on its integration into teaching and learning practices.
    • Education and Information Technologies (SSCI, IF5 = 5.5), where I investigated the application of generative AI in essay assessment through few-shot learning with large language models.
  • Integration of Gamification and Adaptive Design:
    My research emphasizes the combination of gamified elements with adaptive learning to create engaging and effective educational experiences. For instance, my work on generative AI-driven systems in constructionist gaming environments explores how immersive simulations, such as those in Roblox, can adapt to learners’ problem-solving processes. These findings were presented at conferences like AECT and AERA, where I showcased scalable frameworks for adaptive immersive environments.
  • Real-World Applications and Case Studies:
    I have developed adaptive VR systems for diverse applications, including:
    • Training social and cognitive skills for neurodiverse learners, as evidenced by my work in Journal of Autism and Developmental Disorders.
    • Enhancing hazard identification skills in civil engineering students, a project presented at iLRN and AECT.

By bridging the gap between theory and practice, my research contributes actionable insights into how adaptive learning systems in immersive environments can transform educational experiences. These systems not only foster engagement and deep learning but also promote equity and accessibility, ensuring learners from all backgrounds benefit from cutting-edge educational technologies.

Assessment Design through Learning Analytics and AI

Effective adaptive learning systems rely on evidence-based assessments that provide real-time insights into learners’ progress and needs. My research explores how learning analytics and Artificial Intelligence (AI) can revolutionize assessment design by enabling dynamic, data-driven decision-making in educational contexts. Through innovative applications of sequential data analysis, multimodal analytics, and AI-based feedback systems, I aim to enhance both formative and summative assessment practices.

  • Foundational Frameworks for Data-Driven Assessment:
    My work has contributed to the development of frameworks that utilize advanced data analytics to improve assessment design. For instance:
    • In Educational Technology & Society (SSCI, IF5 = 4.8), I proposed a framework for applying sequential data analytics to personalized game-based learning. This study highlights how behavioral patterns during gameplay can inform the design of assessments that are both engaging and diagnostic.
    • My paper in British Journal of Educational Technology (SSCI, IF5 = 7.2) demonstrates the use of machine learning algorithms to detect the learning states of neurodiverse students, particularly those with Autism Spectrum Disorder, in VR-based training environments.
  • Multimodal Learning Analytics for Formative Assessment:
    Incorporating multimodal data sources, such as eye-tracking, physiological signals, and interaction logs, is a hallmark of my research. For example:
    • My study in Computers & Education: X Reality uses data fusion techniques to synthesize multimodal data, providing actionable insights for formative assessment. This approach enables educators to identify cognitive, emotional, and social factors that influence learning outcomes in immersive environments.
    • In two articles published in International Journal of Educational Technology in Higher Education (SSCI, IF5 = 9.9), I examined how learning analytics can reveal peer learning patterns in asynchronous gamified environments and compared the effectiveness of peer-generated versus AI-generated feedback for improving writing performance.
  • AI-Powered Assessment Systems:
    AI has been a transformative tool in my research on assessment design. My work has demonstrated the potential of AI to enhance assessment validity, reliability, and scalability:
    • In Educational Psychology Review (SSCI, IF5 = 12.5), my meta-analysis revealed how AI-powered virtual agents enhance learning outcomes, particularly in simulation-based environments. This study underscores the role of AI in providing context-sensitive feedback that aligns with learners’ needs.
    • My studies on generative AI, such as those published in Education and Information Technologies (SSCI, IF5 = 5.5), explore the application of large language models for automated essay assessment, showcasing how few-shot learning techniques can streamline the evaluation process while maintaining high levels of accuracy and fairness.
  • Innovations in Gamified and Immersive Assessments:
    My research also extends to the use of gamified elements and immersive environments for assessment purposes:
    • In Interactive Learning Environments (SSCI, IF5 = 4.5), I explored how game-based assessments can be integrated into learning systems to evaluate students’ critical thinking and problem-solving skills.
    • My ongoing projects include creating adaptive assessment scenarios in virtual reality for first responder training, where learners’ performance is evaluated in real-time using AI-driven analytics.
  • Practical Implications and Future Directions:
    My research provides a blueprint for integrating learning analytics and AI into assessment practices, offering significant implications for both educators and policymakers. Future work will focus on:
    • Expanding the use of multimodal analytics to include more granular measures of learner engagement and emotional states.
    • Designing ethical and equitable AI-powered assessment tools that address issues of bias and accessibility.
    • Applying these systems across diverse educational contexts, including K-12 classrooms, higher education, and professional training environments.

By combining advanced analytics with cutting-edge AI technologies, my research aims to redefine assessment practices, making them more dynamic, personalized, and inclusive. These innovations support a deeper understanding of the learning process, empowering educators to make informed decisions and foster meaningful learning outcomes.

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