<p>This study used bibliometric analysis to examine the factors influencing interaction within the broad field of digital learning, given its crucial role in effective learning. The author employed a mixed-methods research design, incorporating both quantitative and qualitative methods. Relevant computations were undertaken in bibliometric mapping software VOSviewer to identify the ten most frequently cited sources, countries, organisations and authors in the existing literature. The clustering function in CitNetExplorer was also used to formulate the citation network and identify the longest path for network analysis. The study further combined the community of inquiry framework (which includes teaching, cognitive and social presence) with the interaction model, which emphasises the role of online collaboration through course and instructional design in interactive educational experiences. Four types of interaction were examined: learner–teacher, learner–content, learner–learner and learner–interface interactions. There were inconclusive findings regarding the relationship between course and instructional design and learner–content interaction. Social presence was closely related to learner–learner and learner–teacher interactions. Cognitive presence was associated with learner–content interaction, and teaching presence was linked with learner–interface and learner–teacher interactions. Artificial intelligence (AI) was related to both learner–teacher and learner–learner interactions. The findings suggest that future research should further examine human–AI collaboration, community of inquiry (CoI) processes in different learning environments, and the mechanisms underlying learner–content interaction. In practice, educators and system developers should strengthen instructional scaffolding, learner communication, teacher–AI collaboration and AI-supported assessment to improve interaction in digital learning environments.</p>