TY - GEN
T1 - Mapping Artificial Intelligence–Supported Community of Inquiry Research in Higher Education
T2 - 9th International Conference on Innovative Technologies and Learning, ICITL 2026
AU - Chang, Chi Cheng
AU - Liu, Shu Chuan
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2027.
PY - 2027
Y1 - 2027
N2 - Artificial intelligence (AI) is reshaping collaborative inquiry in higher education, yet its integration with the Community of Inquiry (CoI) framework remains conceptually and methodologically fragmented. This study employs CiteSpace-based scientometric analysis to map the intellectual structure, thematic evolution, and emerging trends of AI-supported CoI research. A curated dataset of 85 publications from Web of Science and Scopus was analyzed through reference co-citation, keyword co-occurrence, and citation burst detection. Results indicate that the field remains anchored in CoI’s core constructs (cognitive and social presence and related component dimensions), while AI functions primarily as an enabling analytic and design layer. Emerging fronts such as learning analytics, machine learning, and generative AI suggest a trajectory from theory building to data-driven expansion and, more recently, AI-supported learning design and discourse analysis. Burst detection further highlights growing attention to engagement, online discussion, and AI-enhanced collaboration, underscoring the hybrid evolution of pedagogical theory and computational methods.
AB - Artificial intelligence (AI) is reshaping collaborative inquiry in higher education, yet its integration with the Community of Inquiry (CoI) framework remains conceptually and methodologically fragmented. This study employs CiteSpace-based scientometric analysis to map the intellectual structure, thematic evolution, and emerging trends of AI-supported CoI research. A curated dataset of 85 publications from Web of Science and Scopus was analyzed through reference co-citation, keyword co-occurrence, and citation burst detection. Results indicate that the field remains anchored in CoI’s core constructs (cognitive and social presence and related component dimensions), while AI functions primarily as an enabling analytic and design layer. Emerging fronts such as learning analytics, machine learning, and generative AI suggest a trajectory from theory building to data-driven expansion and, more recently, AI-supported learning design and discourse analysis. Burst detection further highlights growing attention to engagement, online discussion, and AI-enhanced collaboration, underscoring the hybrid evolution of pedagogical theory and computational methods.
KW - Artificial Intelligence
KW - CiteSpace
KW - Community of Inquiry
KW - Learning Analytics
KW - Scientometric Analysis
UR - https://www.scopus.com/pages/publications/105046277403
UR - https://www.scopus.com/pages/publications/105046277403#tab=citedBy
U2 - 10.1007/978-3-032-32112-1_11
DO - 10.1007/978-3-032-32112-1_11
M3 - Conference contribution
AN - SCOPUS:105046277403
SN - 9783032321114
T3 - Lecture Notes in Computer Science
SP - 96
EP - 104
BT - Innovative Technologies and Learning - 9th International Conference, ICITL 2026, Proceedings
A2 - Lin, Chia-Ju
A2 - Istenic, Andreja
A2 - Istenic, Andreja
A2 - Istenic, Andreja
A2 - Huang, Tien-Chi
A2 - Huang, Yueh-Min
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 4 August 2026 through 6 August 2026
ER -