A PRISMA-ScR checklist for the article, The application of exponential random graph models to online learning networks: a scoping review (update)

As online education continues to gain traction, it is imperative to investigate how interactions within the learning community contribute to individual competencies. There is a growing challenge to analyze networks to delve into students’ development. As a suite of computational and statistical methods, exponential random graph models (ERGMs) examine intricate network structures based on the relational data within the network. The objective of this scoping review was to provide a comprehensive examination of pertinent research on the analysis of online learning environments using ERGMs, with a focus on identifying methods for analyzing collaboration in the extant literature. The study adhered to the SALSA (Search, Appraisal, Synthesis, and Analysis) protocols. Scopus and ScienceDirect were utilized for the literature exploration, resulting in 10 articles meeting the inclusion and exclusion criteria. Four categories of data extraction schema were adopted: bibliometrics, analysis design, network profile, and network structure. In learning networks, connections were formed around the topic center, which differed from interactions in social networks. The studies were conducted across a range of educational fields. Some learners established connections with their peers in diverse clusters, which led to the formation of small-world networks. The findings help educators understand the landscape of detailed ERGM use and the pedagogical areas that have been explored in online learning studies.