Workshop: Capturing Complex Dynamics of Networked Learning Through Visual Mapping

Abstract

Complex networked learning dynamics in professional and work-related contexts are challenging to observe and difficult to capture empirically – particularly when seeking to understand how such processes evolve over time.

To address this challenge, a data collection method has been developed that maps networked learning dynamics and the interactions between people and resources (Goodyear et al., 2004) through a visual mapping technique – for example integrated into an interview.

The technique goes beyond simply mapping human and non-human elements and their connections. It incorporates qualitative dimensions such as the strength of connections, the relative importance of elements, questions of legitimacy, boundaries and identities (Wenger-Trayner & Wenger-Trayner, 2021).  

The purpose of the workshop is to further explore this method and its affordances for understanding networked learning dynamics. Participants will gain first-hand experience with the technique through a practical exercise and will also learn from insights generated across 45 interviews conducted using the method before workshopping the method to advance it theoretically and practically.  

The visual interview technique is inspired by situational analysis (Clarke et al., 2022) and social learning theory including system convening. (Wenger-Trayner & Wenger-Trayner, 2021). During a facilitated process, participants or interviewees will develop a visual representation of for example their work context -mapping connections between actors, the strength of ties, areas of challenge and opportunity, and areas where for example a course or conference is perceived to contribute (Wenger-Trayner & Wenger-Trayner, 2021).