Join Bodong Chen, Tobias Hecking, Sasha Poquet, and many other colleagues in the first Learning Analytics Workshop on Modelling Digital Learning Networks.
This is a FULL-DAY workshop at the 10th International Learning Analytics and Knowledge Conference to be hosted in Frankfurt, Germany. We invite you to attend the workshop as a presenter or a participant.
To join as a presenter, please send a 3 page summary of your work that you intend to share following the Companion Proceedings Template (including references) to firstname.lastname@example.org by December 15, 2019. Notification of acceptance will be made in January 2020. Presenters need to register for the workshop during the LAK registration process.
To join as a participant, please directly register for the workshop during your LAK registration process. Space is limited and be provided on a first-come, first-served basis.
Since its inception, the Learning Analytics community has integrated the use of network analysis (including Social Network Analysis) and related methodologies into the analysis of learning. Representationally, networks allow us to visually communicate learning patterns; computationally, network analysis presents a suite of methods that generate network metrics potentially useful for assessing learning.
One would expect that network applications in Learning Analytics would have matured over the last decade. However, we observe an underwhelming number of their applications that (a) accommodate diverse data sources in learning settings, (b) model network dynamics and network formation mechanisms within learning settings, (c) derive new network metrics that integrate heterogeneous information important for network dynamics, or (d) addresses how to integrate network analytical approaches with other methods, such as text analysis.
To push the frontier of network analysis in Learning Analytics, we welcome various types of submissions to the workshop including (but are not limited to):
The workshop will gather scholars from various disciplinary backgrounds working in these areas to build a foundation of advanced network modeling of learning data. By doing so, we hope to collectively shape strategies of future work in this important sub-field of LA.
Accepted workshop papers will be published on the workshop website and in a joint LAK Companion Proceedings (published by SoLAR). Additional workshop materials will also be shared via the workshop website.
The workshop will combine the symposium and interactive workshop session formats.
Anyone with an interest in the area is welcome to register. To present, participants need to submit proposals for consideration to Dr. Poquet by December 15.
The workshop will be organized around thematic contributions to provide discussion foci for participation in small groups (see possible themes listed above). This interactive format, which was very successful at prior workshops organized by the team, aims to facilitate an inclusive and effective discussion on the day, and onwards. Specifically, the workshop will include the following components: approximately 5 paper presentations; groups organized around presentations; a “birds of a feather” activity organized around themes that emerge from discussions; large-group discussion that sets the agenda for future work in this area.
Twitter conversations will happen under workshop hashtag #LAK20Network.