Innovative Research Award

Guangji Yuan
Affiliation	National Institute of Education (NIE),
Country	Singapore
Scopus ID	57198491888
Documents	39
Citations	317
h-index	9
Subject Area	Educational Technology
Event	Top Teachers Awards
Google Scholar	n6i7kCcAAAAJ

Guangji Yuan is an education research scientist at the National Institute of Education(NIE), Singapore, whose academic work spans learning sciences, computer-supported collaborative learning, knowledge building, learning analytics, artificial intelligence in education, and multimodal research methods. His record combines research, postgraduate teaching and supervision, educational consultancy, academic service, and professional engagement across Singapore and the United States. The supplied profile records 39 Scopus documents, 317 citations, and an h-index of 9.[1][2]

Abstract

Guangji Yuan is an education research scientist affiliated with the Centre for Research in Pedagogy & Practice at the National Institute of Education, Nanyang Technological University. His documented research interests include collaborative learning, knowledge building, artificial intelligence-supported instructional design, learning analytics, and multimodal approaches to educational research. His academic record also includes teaching, thesis advisory work, professional memberships, editorial service, school consultancy, and recognition for research and professional development.[1][2]

Keywords

Teacher development; knowledge building; computer-supported collaborative learning (CSCL); artificial intelligence in education; learning analytics; educational technology; multimodal learning analytics; collaborative learning.

Introduction

Guangji Yuan’s academic trajectory includes doctoral and master’s study at the State University of New York at Albany and undergraduate study at Jiangsu Ocean University. His professional experience includes research scientist, data analyst, and postdoctoral fellow roles, followed by his current position at NIE. The supplied record identifies an Innovation Research Award at NIE in 2026 and earlier academic distinctions including the Presidential Distinguished Doctoral Dissertation Award in 2020.[1][2]

Research Profile

The research profile is interdisciplinary, connecting learning sciences with educational technology and data-informed pedagogical research. The stated areas include computer-supported collaborative learning and knowledge building, AI-enabled instructional design and generative AI in learning, learning analytics, and multimodal and neuroscience-informed research methods.

• Computer-Supported Collaborative Learning and Knowledge Building
• AI-Enabled Instructional Design and Generative AI in Learning
• Learning Analytics
• Multimodal and Neuroscience-Informed Research Methods

Academic qualifications. Guangji Yuan received a PhD from the State University of New York at Albany during 2014–2019, an MS from the same institution during 2012–2013, and a BA from Jiangsu Ocean University during 2007–2011.

Period	Qualification	Institution	Country
2014–2019	PhD	The State University of New York at Albany	USA
2012–2013	MS	The State University of New York at Albany	USA
2007–2011	BA	Jiangsu Ocean University	China

Professional memberships and service. The record identifies membership in the International Society of the Learning Sciences and the American Educational Research Association, as well as service on the Knowledge Building International Conference Organizing Committee. It also records editorial, school consultancy, university committee, examination, and academic-community responsibilities.

Research Contributions

The supplied publications and symposium activities indicate a research programme concerned with collaborative knowledge construction and the role of technology in supporting learning processes. Earlier work examined online collaborative learning, minority students’ online learning experiences, and cultural diversity in online education. More recent work addresses multimodal learning analytics, knowledge-building practice, and the use of AI to scaffold knowledge-building activity.[3][4][5]

The 2026 symposium record includes work on enhancing epistemic-agency practices through vibe-coding projects for secondary students and on using AI to scaffold knowledge building. These activities position AI not only as an instructional technology but also as an object of inquiry within collaborative learning environments.

Publications

Guangji Yuan’s publications examine online collaborative learning, educational technology, cultural diversity, and AI-supported knowledge building. Key studies include research on minority students’ collaborative learning experiences, factors shaping online learning and academic self-concept, and instructors’ perspectives on cultural diversity in online education.[3][4][5]

Selected highly cited publications and scholarly contributions supplied for this profile include the following:

• Kumi-Yeboah, A., Dogbey, J., & Yuan, G. (2017). Online Collaborative Learning Activities: The Perspectives of Minority Graduate Students. Online Learning Journal, 21(4).
• Kumi-Yeboah, A., Dogbey, J., & Yuan, G. (2018). Exploring Factors that Promote Online Learning Experiences and Academic Self-Concept of Minority High School Students. Journal of Research on Technology in Education, 50(1), 1–17.
• Kumi-Yeboah, A., Dogbey, J., Yuan, G., & Smith, P. (2020). Cultural Diversity in Online Education: An Exploration of Instructors’ Perceptions and Challenges. Teachers College Record, 122(7), 1–46.

2026 symposium contributions. The supplied record lists Guangji Yuan as a contributor to a Knowledge Building Summer Institute symposium in Nanjing, China, on enhancing epistemic-agency practices with vibe-coding projects for secondary students. It also identifies a February 2026 presentation on using AI to scaffold knowledge building at the Nanyang Technological University context.

• Teo, C. L., Ong, A., Lee, A., & Yuan, G. (2022). Multimodal Learning Analytics for Collaborative Learning. Symposium contribution on AI and analytics for collaborative learning and knowledge building.
• Teo, C. L., Yuan, G., Lee, A., Ong, A., Ong, G., Chan, M., Tey, A. H., Jothinathan, L., & Kanapathy, S. (2022). Practical Knowledge about Knowledge Building: Principle-based and idea-centric approach. Symposium contribution on knowledge-building practice.

• Yuan, G., Ong, M., Teo, C. L. (2026), Enhancing Epistemic Agency Practices with Vibe-coding Projects for Secondary Students; Symposium of Rethinking Epistemic Agency in Knowledge Building in the Age of AI. Knowledge Building Summer Institute. Chair Bodong Chen.

Research Impact

The supplied bibliometric information reports 39 Scopus-indexed documents, 317 citations, and an h-index of 9. A separate Google Scholar figure supplied in the record reports 53 documents, 661 citations, and an h-index of 12. Because bibliometric databases use different coverage and counting methods, these figures should be interpreted as database-specific indicators rather than directly interchangeable measures.[1][2]

The profile also documents teaching across master’s and undergraduate contexts, research supervision, thesis advisory participation, school-based consultancy, and academic-community service. These activities indicate engagement beyond publication outputs, particularly in the application of learning-sciences research to pedagogical practice.

Award Suitability

For the Top Teachers Awards’ Innovative Research Award, the supplied record presents evidence across several relevant dimensions: a sustained research profile in educational technology and learning sciences; publications concerning collaborative and online learning; current research on AI and knowledge building; documented teaching and postgraduate supervision; and professional service. The record also identifies an Innovation Research Award at NIE in 2026 and prior academic distinctions, including the Presidential Distinguished Doctoral Dissertation Award.[1][2]

The evidence supports consideration of the profile on the basis of documented scholarly activity, educational practice, and service. Award assessment should remain subject to the criteria, verification procedures, and eligibility requirements established by the awarding organisation.

Conclusion

Guangji Yuan’s supplied academic record describes an interdisciplinary education researcher working at the intersection of learning sciences, collaborative knowledge building, educational technology, AI, and learning analytics. His profile combines research publications and symposium activity with teaching, supervision, consultancy, academic service, and professional recognition. The documented record provides a structured basis for evaluating his suitability for an innovative research recognition within education.[1][2]

External Links

• Scopus Author Profile
• Google Scholar Profile
• Award Website

References

1. Elsevier. (n.d.). Scopus author details: Guangji Yuan, Author ID 57198491888. Scopus. https://www.scopus.com/authid/detail.uri?authorId=57198491888
2. Google Scholar. (n.d.). Guangji Yuan — Google Scholar profile. https://scholar.google.com/citations?user=n6i7kCcAAAAJ&hl=en&oi=sra
3. Kumi-Yeboah, A., Dogbey, J., & Yuan, G. (2017). Online Collaborative Learning Activities: The Perspectives of Minority Graduate Students. Online Learning Journal, 21(4). https://www.learntechlib.org/p/183774/
4. Kumi-Yeboah, A., Dogbey, J., & Yuan, G. (2018). Exploring Factors that Promote Online Learning Experiences and Academic Self-Concept of Minority High School Students. Journal of Research on Technology in Education, 50(1), 1–17. https://doi.org/10.1080/15391523.2017.1365669
5. Kumi-Yeboah, A., Dogbey, J., Yuan, G., & Smith, P. (2020). Cultural Diversity in Online Education: An Exploration of Instructors’ Perceptions and Challenges. Teachers College Record, 122(7), 1–46. https://doi.org/10.1177/016146812012200708