Roger Azevedo | Educational Technology | Innovative Research Award

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Innovative Research Award

Roger Azevedo — University of Central Florida, United States

Roger Azevedo
Affiliation University of Central Florida
Country United States
Google Scholar gAFP2yQAAAAJ
Documents 460
Citations 33,168
h-index 85
Subject Area AI and Pedagogical Agents
Event Top Teachers Awards
Scopus ID 18036509700
ORCID 0000-0002-5018-6232

Roger Azevedo is a professor in the School of Modeling, Simulation and Training at the University of Central Florida (UCF), with affiliated appointments in Computer Science and Internal Medicine and leadership responsibilities within the Learning Sciences Faculty Cluster Initiative. His research examines how cognitive, metacognitive, affective, motivational, and social self-regulatory processes interact with advanced learning technologies, including intelligent tutoring systems, pedagogical agents, simulations, serious games, hypermedia, multimedia, and immersive virtual learning environments. His work combines interdisciplinary measurement and computational approaches to understand human–intelligent-system interaction and its implications for learning, performance, and transfer. [1][2]

Abstract

Roger Azevedo’s research is situated at the intersection of educational psychology, learning sciences, artificial intelligence, human–computer interaction, and advanced learning technologies. His program investigates how learners regulate cognition, metacognition, motivation, affect, and social processes while interacting with intelligent learning environments. His research also addresses the design of systems capable of detecting, modeling, tracking, and supporting these processes across laboratory, classroom, simulation, and other authentic learning contexts. [1]

Keywords

  • Artificial intelligence
  • Pedagogical agents
  • Metacognition
  • Self-regulated learning
  • Multimodal data
  • Advanced learning technologies
  • Learning analytics
  • Human–AI interaction
  • Human digital twins

Introduction

Roger Azevedo’s academic career spans educational psychology, cognitive science, educational technology, computer science, medical informatics, and simulation-based training. He received a PhD in Educational Psychology from McGill University, specializing in Applied Cognitive Science and Educational Psychology, following an M.A. in Educational Technology and a B.A. in Psychology from Concordia University. He subsequently completed postdoctoral training in Cognitive Psychology at Carnegie Mellon University. [2]

His professional appointments have included faculty positions at the University of Maryland, University of Memphis, McGill University, North Carolina State University, and the University of Central Florida. At UCF, his roles have included professor in the School of Modeling, Simulation and Training, associate faculty appointments in Computer Science and Internal Medicine, and leadership within the Learning Sciences Faculty Cluster Initiative.[1]

Research Profile

The central objective of Roger Azevedo’s research is to understand the complex interactions between people and intelligent learning systems. His studies examine temporally unfolding self- and other-regulatory processes involving humans, teachers, peers, and artificial agents. The research program integrates cognitive, metacognitive, affective, motivational, and social measures with multimodal process data to model learning and human–machine interaction. [1]

His research areas include advanced learning and training technologies, human digital twins, human–machine AI collaboration, intelligent environments for education and training, metacognition and self-regulated learning, and multimodal process data in human–machine interactions.

Education: PhD in Educational Psychology, McGill University (1993–1998); M.A. in Educational Technology, Concordia University (1989–1993); and B.A. in Psychology, Concordia University (1986–1989).

Selected professional appointments: Professor, School of Modeling, Simulation and Training, University of Central Florida; Associate Faculty, Department of Computer Science and Department of Internal Medicine, UCF; Lead Scientist and Co-Cluster Lead, Learning Sciences Faculty Cluster Initiative; Professor, Department of Psychology, North Carolina State University; Endowed Senior Canada Research Chair (Tier 1), McGill University; Professor and Cognitive Area Director, University of Memphis; and Professor, Department of Human Development, University of Maryland.

Selected distinctions: 2026 Honorary Doctorate, Philosophiae Doctor Honoris Causa, University of Jyväskylä; 2025 Member of the Academy of Science, Engineering and Medicine of Florida; 2025 Fellow of the American Educational Research Association; 2025 Pegasus Professor at the University of Central Florida; 2018 Barry J. Zimmerman Award for Outstanding Contributions to Studying and Self-Regulated Learning Research; 2011 Endowed Senior Canada Research Chair; and 2009 Fellow of the American Psychological Association, Division 15.

Professional associations: American Educational Research Association, American Psychological Association, Association for Computing Machinery, European Association for Research on Learning and Instruction, International Artificial Intelligence in Education Society, Society for Learning Analytics Research, and Society for Simulation in Healthcare.

Research Contributions

Roger Azevedo’s contributions emphasize the integration of learning science with intelligent technologies. His work investigates how learners deploy and adapt cognitive and metacognitive strategies, how motivational and affective states develop during learning, and how intelligent systems can provide adaptive scaffolding. This line of research has informed the design of computer-based learning environments intended to support self-regulated learning and metacognition. [3]

  • Advanced learning and training technologies for complex educational and professional environments.
  • Human digital twins and computational representations of human learning and performance.
  • Human–machine AI collaboration and interaction with intelligent learning systems.
  • Pedagogical agents and adaptive computer-based scaffolding.
  • Metacognition and self-regulated learning across different learning contexts.
  • Multimodal process data for detecting and modeling cognitive, affective, motivational, and social processes.
  • Learning analytics and intelligent environments for education and training.

Editorial and scholarly service: Roger Azevedo has held editorial and peer-review responsibilities across educational psychology, learning sciences, artificial intelligence in education, human–computer interaction, cognitive psychology, learning analytics, and related fields. Reported roles include Co-Editor-in-Chief of the British Journal of Educational Psychology, previous Editor-in-Chief of Metacognition and Learning, and editorial board memberships for journals including Learning and Instruction, Learning and Individual Differences, Applied Cognitive Psychology, Metacognition and Learning, International Journal of Artificial Intelligence in Education, Educational Psychology Review, and Instructional Science.

Selected honors and awards: In addition to major professional fellowships and professorship distinctions, his record includes Best Conference Paper and Best Paper awards associated with conferences and journals in artificial intelligence in education, intelligent virtual agents, intelligent tutoring systems, learning analytics, and related areas, as well as the Outstanding International Research Collaboration Award from an AERA special interest group.

Invited scholarly activity: His keynote and invited lecture record extends across international conferences and universities in North America, Europe, Asia, Latin America, Australia, and other regions. Recent topics and venues include artificial intelligence in education, cognitive science, self-regulated learning, human digital twins, multimodal affect, learning analytics, simulation, and human–AI interaction.

Publications

Roger Azevedo’s publication record addresses self-regulated learning, metacognition, intelligent learning environments, hypermedia, educational technology, and learning processes. Representative highly cited work includes the study of training in self-regulated learning and students’ learning with hypermedia, research on scaffolding self-regulated learning and metacognition in computer-based environments, and work examining models of reading comprehension. [3] [4] [5]

The supplied research-profile metrics report 460 documents, 33,168 Google Scholar citations, and an h-index of 85. The corresponding Scopus information supplied for the profile reports 295 documents, 14,668 citations, and an h-index of 60. These figures are platform-specific and may change as databases are updated.[2]

Research Impact

The reported citation record indicates substantial scholarly visibility in the fields represented by Roger Azevedo’s research. His work connects theories of learning and self-regulation with the development of intelligent technologies, creating a research program relevant to educational psychology, learning sciences, artificial intelligence in education, learning analytics, simulation, and human–computer interaction.[1]

His research impact is also reflected in professional recognition, including election as a Fellow of the American Educational Research Association, appointment as a Pegasus Professor at UCF, recognition as a Fellow of the American Psychological Association, the Barry J. Zimmerman Award, a Tier 1 Canada Research Chair, and multiple conference and publication awards.

Award Suitability

The profile presents several characteristics relevant to consideration for an Innovative Research Award. These include a sustained interdisciplinary research program, extensive scholarly publication and citation activity, research on emerging artificial intelligence and learning technologies, contributions to metacognition and self-regulated learning, international research engagement, editorial service, mentoring, and recognition through professional awards and fellowships.

Particularly relevant to an innovation-focused recognition is the integration of psychological theories and empirical methods with intelligent tutoring systems, pedagogical agents, multimodal data, simulations, immersive environments, and human–AI collaboration. The combination of foundational learning-science research and technology-oriented system design provides a coherent basis for evaluating the nominee’s contribution to innovative research. [1][2]

Conclusion

Roger Azevedo’s academic profile reflects a long-term interdisciplinary research program focused on learning, self-regulation, cognition, affect, motivation, and interaction with intelligent technologies. His research combines educational psychology and learning sciences with artificial intelligence, multimodal measurement, learning analytics, simulation, and human–machine interaction. His publication record, professional service, fellowships, awards, and international scholarly activity collectively provide substantial evidence of sustained research engagement relevant to an Innovative Research Award.[1][2]

References

  1. University of Central Florida. (n.d.). Roger Azevedo — School of Modeling, Simulation and Training. University of Central Florida. https://simulation.ucf.edu/person/roger-azevedo/
  2. Google Scholar. (n.d.). Roger Azevedo — Google Scholar profile. Google Scholar. https://scholar.google.com/citations?user=gAFP2yQAAAAJ&hl=en
  3. Azevedo, R., & Hadwin, A. F. (2005). Scaffolding self-regulated learning and metacognition—Implications for the design of computer-based scaffolds. Instructional Science, 33(5–6), 367–379. https://www.jstor.org/stable/41953688
  4. Azevedo, R., & Cromley, J. G. (2004). Does training on self-regulated learning facilitate students’ learning with hypermedia? Journal of Educational Psychology, 96(3), 523–535. DOI: https://doi.org/10.1037/0022-0663.96.3.523
  5. Cromley, J. G., & Azevedo, R. (2007). Testing and refining the direct and inferential mediation model of reading comprehension. Journal of Educational Psychology, 99(2), 311–325. DOI: https://doi.org/10.1037/0022-0663.99.2.311

Mei-Rong Alice Chen | Educational Technology | Innovative Research Award

Published on by Top Teachers

Innovative Research Award

Mei-Rong Alice Chen
Soochow University, Taiwan
Mei-Rong Alice Chen
Affiliation Soochow University
Country Taiwan
Scopus ID 57203980835
Documents 34
Citations 1,331
h-index 13
Subject Area Educational Technology
Event Top Teachers Awards
ORCID 0000-0003-2722-0401
Google Scholar JYD308IAAAAJ

Mei-Rong Alice Chen is an academic researcher whose work connects digital learning and education, applied linguistics, English language education, educational technology, artificial intelligence in education, and technology-enhanced learning. Her academic appointments and research presentations indicate an interdisciplinary profile spanning language pedagogy, digital humanities, generative artificial intelligence, multimodal literacy, EFL writing, collaborative learning, and learner engagement. Bibliographic records identify a substantial body of scholarly output and citation activity in these fields.[1][2]

Abstract

Mei-Rong Alice Chen is a Taiwan-based scholar in digital learning and education whose academic work integrates applied linguistics, English language education, educational technology, and emerging artificial intelligence applications. Her profile includes university teaching and research appointments at Soochow University and National Taiwan University of Science and Technology, as well as research experience at Kyoto University. Her scholarly activity addresses EFL writing, AI-supported language learning, digital humanities, multimodal literacy, augmented reality, collaborative learning, learner self-efficacy, and digital engagement. Her publication and citation records, together with institutional research recognition, provide evidence of sustained scholarly activity in technology-enhanced education.[1][2]

Keywords

Digital learning; educational technology; applied linguistics; EFL education; artificial intelligence in education; generative AI; digital humanities; multimodal literacy; EFL writing; augmented reality; collaborative learning; learning analytics; learner engagement; self-efficacy; technology-enhanced language teaching.

Introduction

Mei-Rong Alice Chen’s academic trajectory combines language and linguistics training with doctoral specialization in digital learning and education. Her appointments have included Associate Professor and Assistant Professor in the Department of English Language and Literature at Soochow University, Assistant Professor and Postdoctoral Researcher at the Institute of Digital Learning and Education of National Taiwan University of Science and Technology, and a program-specific research position at Kyoto University.

Her research is situated at the intersection of language education and digital transformation. Particular emphasis is placed on how artificial intelligence, digital environments, multimodal resources, augmented reality, and structured learning approaches can support language development, reflection, engagement, and learner autonomy. Studies associated with her scholarly profile include research on AI in language education, emergency online learning, concept-mapping-based flipped learning, and extensive reading.[3][4][5]

Research Profile

Academic appointments

  • Associate Professor, Department of English Language and Literature, Soochow University, Taiwan.
  • Assistant Professor, Department of English Language and Literature, Soochow University, Taiwan.
  • Assistant Professor, Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan.
  • Postdoctoral Researcher, Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan.
  • Program-Specific Researcher, Academic Center for Computing and Media Studies, Kyoto University, Japan.

Education

  • Ph.D. in Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan, September 2017–June 2019.
  • Doctoral Coursework in Business Administration, National Taiwan University of Science and Technology, Taiwan, September 2010–June 2011.
  • M.A. in Linguistics, California State University, Long Beach, California, USA, January 2000–June 2001; academic distinction: President’s List.
  • B.A. in English, concentration in Language and Linguistics, California State University, Long Beach, California, USA, June 1998–January 2000; academic distinction: Dean’s List.
  • General Education Coursework, El Camino College, Torrance, California, USA, September 1996–June 1998.

Primary research areas

Digital Learning and Education, English Language and Literature, Applied Linguistics and EFL Education, Educational Technology and Artificial Intelligence in Education, Generative AI in Language Learning, Computer Edication, Digital Humanities and Multimodal Literacy, Technology-Enhanced Writing and Writing Pedagogy, Augmented Reality and AI-Assisted Learning, Learning Analytics and Digital Engagement, Collaborative Learning and Socially Shared Regulation, Design Thinking, Humanistic AI, and Digital Learning Innovation.

Research Contributions

A major component of Mei-Rong Alice Chen’s research concerns the integration of emerging technologies with language education. Her work examines how artificial intelligence and technology-mediated environments can influence language learning, learner engagement, reflection, and instructional practice. A bibliographic review co-authored by Chen examined the roles and research foci of artificial intelligence in language education, placing AI-supported language learning within a broader research landscape.[3]

Her research also addresses instructional design and learner-centered pedagogy. A study of concept-mapping-based flipped learning investigated effects on EFL students’ English speaking performance, critical-thinking awareness, and speaking anxiety, illustrating the relationship between instructional structure and multiple dimensions of language learning.[5]

Additional work examines digital learning under constrained conditions, including student engagement strategies in emergency online learning. This strand of research complements Chen’s broader interest in designing learning environments that support participation and effective use of educational technologies.[4]

Recent conference presentations further extend these themes to humanistic AI in digital humanities education, AI-generated tour-guide chatbots, augmented-reality-guided writing, generative-AI digital narratives, cognitive process-based visual feedback, socially shared regulation, structured reflection, and sustainable learning habits.

Publications

Mei-Rong Alice Chen’s publications examine artificial intelligence in language education, EFL learning, digital pedagogy, and technology-enhanced instruction. Her research includes systematic analysis of AI in language education, flipped learning, and AI-supported language learning, demonstrating sustained contributions to digitally mediated language education and educational technology research.[3][5]

Selected publications demonstrate the interdisciplinary character of Mei-Rong Alice Chen’s research. Her work has appeared in international journals addressing educational technology, artificial intelligence in language education, online learning, language pedagogy, and learning engagement. The selected publications below represent particularly relevant contributions to the research profile described on this page.[3][4][5]

  1. Liang, J. C., Hwang, G. J., Chen, M. R. A., & Darmawansah. (2021). Roles and research foci of artificial intelligence in language education: An integrated bibliographic analysis and systematic review approach. Interactive Learning Environments.
  2. Abou-Khalil, V., Helou, S., Khalifé, E., Chen, M. R. A., Majumdar, R., & Ogata, H. (2021). Emergency online learning in low-resource settings: Effective student engagement strategies. Education Sciences, 11(1), 24.
  3. Chen, M. R. A., & Hwang, G. J. (2020). Effects of a concept mapping-based flipped learning approach on EFL students’ English speaking performance, critical thinking awareness and speaking anxiety. British Journal of Educational Technology, 51(3), 817–834.

Research Impact

The supplied bibliographic profile reports 34 Scopus-indexed documents, 1,331 citations, and an h-index of 13. The supplied Google Scholar profile reports 65 documents, 3,058 citations, and an h-index of 21. Because bibliometric indicators can vary by database, indexing coverage, author disambiguation, and update date, these figures should be interpreted as database-specific indicators rather than interchangeable measures.[1][2]

The research record is notable for its breadth across language education, digital learning, AI-supported education, and technology-enhanced pedagogy. Its impact profile includes publications addressing AI in language education, Computer education, online learning engagement, flipped learning, extensive reading, and technology-based STEM education, reflecting collaboration across educational technology and learning-science research communities.[3][4][5]

Award Suitability

Based on the supplied academic appointments, research areas, publications, conference presentations, bibliometric indicators, and reported recognitions, Mei-Rong Alice Chen’s profile is relevant to award categories emphasizing interdisciplinary research and innovation in digital education. The following areas are academically aligned with the documented research themes:[1][2]

Digital Learning and Education Research Award, AI in Education Research Award, Educational Technology Innovation Award, Digital Humanities Research Award, Applied Linguistics Research Award, English Language Education Innovation Award, Generative AI in Education Award, Technology-Enhanced Language Learning Award, EFL Writing Research Award, Innovative Teaching and Research Award, Educational Innovation Award, Emerging Technologies in Education Award

Conclusion

Mei-Rong Alice Chen’s academic profile combines formal training in linguistics and digital learning with university teaching, research appointments, international scholarly collaboration, and publications in educational technology and language education. Her research emphasizes the educational application of artificial intelligence, digital environments, multimodal learning, EFL pedagogy, learner engagement, and technology-enhanced instructional design. The documented publication and bibliometric records, together with reported academic recognitions, provide a basis for considering her for research and educational innovation recognition in these areas.[1][2]

References

  1. Elsevier. (n.d.). Scopus author details: Mei-Rong Alice Chen, Author ID 57203980835. Scopus. https://www.scopus.com/pages/authors/57203980835
  2. Google Scholar. (n.d.). Mei-Rong Alice Chen: Google Scholar author profile. https://scholar.google.com/citations?user=JYD308IAAAAJ&hl=en&oi=sra
  3. Liang, J. C., Hwang, G. J., Chen, M. R. A., & Darmawansah. (2021). Roles and research foci of artificial intelligence in language education: An integrated bibliographic analysis and systematic review approach. Interactive Learning Environments. https://doi.org/10.1080/10494820.2021.1958348
  4. Abou-Khalil, V., Helou, S., Khalifé, E., Chen, M. R. A., Majumdar, R., & Ogata, H. (2021). Emergency online learning in low-resource settings: Effective student engagement strategies. Education Sciences, 11(1), 24. https://doi.org/10.3390/educsci11010024
  5. Chen, M. R. A., & Hwang, G. J. (2020). Effects of a concept mapping-based flipped learning approach on EFL students’ English speaking performance, critical thinking awareness and speaking anxiety. British Journal of Educational Technology, 51(3), 817–834. https://doi.org/10.1111/bjet.12887

Guangji Yuan | Educational Technology | Innovative Research Award

Published on by Top Teachers

Innovative Research Award

Guangji Yuan
Education Research Scientist, Centre for Research in Pedagogy & Practice (CRPP), National Institute of Education (NIE), Malaysia
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]

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

Liao Zhongyuan | Educational Technology | Innovative Research Award

Published on by Top Teachers

Innovative Research Award

Liao Zhongyuan
Fuzhou University of International Studies and Trade (FUIST), China

Liao Zhongyuan
Affiliation Fuzhou University of International Studies and Trade
Country China
ORCID 0009-0000-2375-3361
Document 1
Citations 6
Subject Area Educational Technology
Event Top Teachers Awards

Liao Zhongyuan is an Associate Professor in the College of Education at Fuzhou University of International Studies and Trade (FUIST), China. His scholarly activities focus on Chinese cultural international communication, rural revitalization, Fujian–Taiwan cultural heritage, educational innovation, and the integration of ideological and political education with digital pedagogy. Through sustained academic engagement, he has contributed to interdisciplinary discussions concerning educational technology, cultural transmission, and intelligent learning systems. His research record includes numerous journal publications, project leadership activities, and academic collaborations within provincial and national research initiatives.[1]

Abstract

This article presents an overview of the academic profile and research achievements of Liao Zhongyuan, an Associate Professor at Fuzhou University of International Studies and Trade. His work integrates educational technology, cultural studies, digital pedagogy, and ideological education within contemporary Chinese educational contexts. His scholarly contributions include research on intelligent educational systems, cultural heritage education, and interdisciplinary approaches that combine artificial intelligence with moral and cultural instruction. His publications, funded projects, and award-winning research demonstrate active engagement with educational innovation and social science research development.[1][2]

Keywords

Educational Technology; Digital Pedagogy; Chinese Cultural Communication; Fujian–Taiwan Cultural Heritage; Rural Revitalization; Smart Education; Artificial Intelligence in Education; Moral Education; Cultural Studies; Ideological and Political Education.

Introduction

Educational transformation in the digital era increasingly requires interdisciplinary scholarship that connects technology, culture, and pedagogy. Liao Zhongyuan’s academic work contributes to this evolving landscape through research that examines how emerging technologies can support cultural education, moral development, and heritage preservation. His investigations have explored both theoretical and applied dimensions of educational innovation, particularly within Chinese educational environments and regional cultural contexts.[1]

His research activities extend across multiple domains, including Chinese cultural international communication, Fujian–Taiwan cultural studies, rural revitalization initiatives, and the integration of digital technologies into educational systems. These areas collectively support broader discussions regarding sustainable educational development and culturally informed innovation.[1]

Research Profile

Liao Zhongyuan holds a Master’s degree in Teaching Chinese to Speakers of Other Languages from Northwest Normal University. As an academic researcher and educator, he has developed a research portfolio emphasizing cultural education, intelligent learning environments, and educational policy implementation. His scholarly record includes nearly twenty academic publications in domestic and international journals, together with authorship and co-authorship of academic monographic work.[1]

In addition to publication activities, he has served as principal investigator for seven provincial-level social science projects and twenty-three prefectural-level projects. He has also participated as a core member in national and provincial social science research initiatives, reflecting sustained involvement in collaborative research networks.[1]

Research Contributions

  • Investigation of Chinese cultural international communication and contemporary cultural dissemination strategies.
  • Research concerning Fujian–Taiwan cultural heritage and regional cultural integration.
  • Studies on rural revitalization and educational participation in community development.
  • Exploration of digital pedagogy and intelligent educational technologies in teaching practice.
  • Analysis of ideological and political education through integrated and technology-enhanced learning frameworks.
  • Research on artificial intelligence applications in moral and cultural education systems across educational levels.[2]

A notable scholarly achievement includes his award-winning study titled The Generative Logic, Operational Mechanism, and Practical Path of Smart Ideological and Political Education Empowering the “Fu” Culture Education in Min Capital from an Integrated Perspective, which received First Prize at the Fifth National Symposium on the Integrated Practice of Ideological and Political Education in Primary, Secondary, and Tertiary Education.[1]

Publications

Liao Zhongyuan has published nearly 20 scholarly papers and co-authored an academic monograph. His notable 2026 study on AI-enabled “Fu” culture education advanced educational technology research.[2][1]

  • Liao, Z. (2026). Artificial intelligence-enabled integration of “Fu” culture into the moral education system for special education across K-12 and higher education: a soft computing approach. Disability and Rehabilitation: Assistive Technology.
  • Author or co-author of nearly twenty academic papers published in domestic and international scholarly journals addressing educational innovation, cultural communication, and interdisciplinary educational research.[1]
  • Author or co-author of one academic monograph related to educational and cultural studies.[1]

Research Impact

The impact of Liao Zhongyuan’s research is reflected through sustained project leadership, scholarly publication, and participation in multidisciplinary research programs. His work contributes to discussions regarding educational modernization, cultural preservation, and technology-assisted learning. By integrating artificial intelligence, cultural education, and moral instruction, his studies address contemporary educational challenges while supporting evidence-based academic discourse.[1][2]

His ongoing research project concerning Fujian–Taiwan “Fu” culture, funded by the National Ethnic Affairs Commission, further illustrates continuing engagement with cultural heritage research and educational application. Such initiatives contribute to broader scholarly understanding of regional cultural resources and their role in educational development.[1]

Award Suitability

The academic record of Liao Zhongyuan aligns with the objectives commonly associated with scholarly recognition programs that acknowledge innovation, research productivity, educational impact, and interdisciplinary contributions. His combination of publication activity, project leadership, educational research, and award-winning scholarship demonstrates a sustained commitment to advancing knowledge within the fields of educational technology and cultural education.[1][2]

His work also reflects contemporary priorities in higher education, including digital transformation, cultural sustainability, and the responsible application of emerging technologies in teaching and learning environments. These characteristics support consideration within academic recognition frameworks such as the Top Teachers Awards.

Conclusion

Liao Zhongyuan has established a multidisciplinary academic profile centered on educational technology, cultural communication, and innovative pedagogy. Through publication, research leadership, funded projects, and scholarly recognition, he has contributed to ongoing academic discussions regarding intelligent education systems and cultural learning. His research activities demonstrate continued engagement with contemporary educational challenges and opportunities in both regional and international contexts.[1][2]

References

  1. ORCID. (n.d.). ORCID profile: Liao Zhongyuan (ORCID: 0009-0000-2375-3361). ORCID Registry. https://orcid.org/0009-0000-2375-3361
  2. Liao, Z. (2026). Artificial intelligence-enabled integration of “Fu” culture into the moral education system for special education across K-12 and higher education: a soft computing approach. Disability and Rehabilitation: Assistive Technology. DOI: https://doi.org/10.1080/17483107.2025.2555541