The next SNOLA (Spanish Network Of Learning Analytics) webinar will take place on April 22nd at 16:00h. Enter this link to see more information.

Overview: There have been remarkable efforts in studying collaborative, social and learning networks using Social Network Analysis. Such efforts have demonstrated the wealth of insights that network analysis could bring. However, the majority of network analysis research has used static networks, i.e., aggregated networks that compile interactions without taking time into account. Therefore, temporal networks have emerged as a subfield of network science that is concerned with the study of time-ordered interactions. As a paradigm, temporal networks should not be simply summarized as a generalization of static networks, neither should they be confused with static networks that account for the chronological order of interactions. This presentation will give an overview on the structure and characteristics of temporal networks. Case studies will be presented in which temporal networks have been implemented to study students’ interactions, discourse analysis and the temporal progression of students’ strategies.

Mohammed Saqr

DMohammed Saqr has a PhD in learning analytics from Stockholm University, Sweden. He works on all issues regarding analytics and big data in education, network science and Scientometrics. His research in learning analytics focuses on social and temporal networks, machine learning, process and sequence mining and temporal processes in general. He is also an active member of several scientific organizations and acts as an academic editor in leading academic publications. Here is a link to his research: