Go-along interviewing is an emerging qualitative research method where researcher and interviewee go together to a location relevant for the research. Usually employed in ethnographic studies, the method is used to provide a contextualized understanding of a participant’s experience. This paper explores performing Go-along interviews in Immersive Virtual Reality (VR). Through an analysis of ten interviews conducted inside our participants’ Virtual Mind Palaces we show how the interlocutors’ shared presence in the virtual environment established a common ground beneficial for communication. Being in VR enabled our participants to demonstrate interactions spontaneously, and, by providing a guided tour, show us relevant objects and locations in their Virtual Mind Palace. Benefits and challenges of adapting this method to VR are discussed and recommendations for researchers who want to conduct VR Go-along interviews are provided. Finally, we argue the method as an effective tool for eliciting contextual, phenomenological accounts of virtual environments.

Firefighter learning is high stake. They need to maintain certain competence levels related to physical, mental, and firefighting and rescue skills in order to provide the public with a high level of emergency service. Fire and Rescue Services need to maintain an overview of the current competences of their personnel and to react when there is a competence gap. This poster presents our approach to using competence modelling, learner models, learning analytics, and visualisations in order provide insight into competence status and development on the individual, team, and organisation level, and to provide early-alerts and automated messages to instructors responsible for planning training activities, as well as to team leaders responsible for making decisions about teams in high stakes situations.

This paper considers teacher adoption of an open learner model (OLM) constructed from automated and manual data. It shows OLM visualisations; how teachers, students and peers can provide data to an individual’s model; and an overview of how such manually-provided information is combined with automated data. Teacher experiences reveal the potential for OLMs of this type in classrooms, as well as some of the barriers to achieving this.

With the increase of ICT in classrooms comes much data that can be used for evidence-based assessment. We focus on harnessing and interpreting this data to empower teachers in formative assessment. We describe e-assessment of English as a Second Language and illustrate how we move from data collected in classroom activities, through an automated assessment method, to visualising competence levels in an open learner model.