Abstract
BackgroundCollaborative learning facilitates reflection, diversifies understanding and stimulates skills of critical and higher-order thinking. Although the benefits of collaborative learning have long been recognized, it is still rarely studied by social network analysis (SNA) in medical education, and the relationship of parameters that can be obtained via SNA with students’ performance remains largely unknown. The aim of this work was to assess the potential of SNA for studying online collaborative clinical case discussions in a medical course and to find out which activities correlate with better performance and help predict final grade or explain variance in performance.MethodsInteraction data were extracted from the learning management system (LMS) forum module of the Surgery course in Qassim University, College of Medicine. The data were analyzed using social network analysis. The analysis included visual as well as a statistical analysis. Correlation with students’ performance was calculated, and automatic linear regression was used to predict students’ performance.ResultsBy using social network analysis, we were able to analyze a large number of interactions in online collaborative discussions and gain an overall insight of the course social structure, track the knowledge flow and the interaction patterns, as well as identify the active participants and the prominent discussion moderators. When augmented with calculated network parameters, SNA offered an accurate view of the course network, each user’s position, and level of connectedness. Results from correlation coefficients, linear regression, and logistic regression indicated that a student’s position and role in information relay in online case discussions, combined with the strength of that student’s network (social capital), can be used as predictors of performance in relevant settings.ConclusionBy using social network analysis, researchers can analyze the social structure of an online course and reveal important information about students’ and teachers’ interactions that can be valuable in guiding teachers, improve students’ engagement, and contribute to learning analytics insights.
Highlights
Collaborative learning facilitates reflection, diversifies understanding and stimulates skills of critical and higher-order thinking
Research question 1 What information can the study of the social structure provide about the status of online collaborative learning on the course, discussion, and individual level?
The data were drawn from 34 discussion threads, and the data set totaled 1251 interactions. These interactions were visually and mathematically analyzed on course level, discussion thread level, and individual learner levels as follows: Visualization At the course level Interpretation of social networks depends on the context and the design of the course where it occurs [33], and the interactions can be mapped in different ways
Summary
Collaborative learning facilitates reflection, diversifies understanding and stimulates skills of critical and higher-order thinking. TEL has the power to transcend the boundaries of space and time, offering convenience, efficiency, and cost-effectiveness Social constructivists see humans as social creatures who grow up by developing knowledge and skills through interactions with different communities They assume that learning is a social byproduct of conversation and negotiation with peers and that learners acquire knowledge by participating in relevant social activities or working collaboratively in groups [9, 10]. Connectivism—a theory developed to address learning in the digital age—asserts that knowledge and learning exist in a multiplicity of viewpoints and that learning as a process occurs by connecting sources of information It values the role of communication and information appraisal skills in the development of learning and staying up-to-date [8, 11]
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