EARLI 2023, Thessaloniki
Crina is holding a keynote on collaborative learning at this year’s EARLI:
Title and abstract
“Together for learning: Understanding the ecosystem of collaborative learning”
More than ever before, collaboration and dialogue have become means to address major challenges we are currently facing - pandemic, conflict, humanitarian crises. At the macro societal level but also at the micro-level of workplaces and classrooms, knowing how to collaborate and how to solve problems together is paramount. Yet, while the value of working and learning together with others is widely acknowledged, meaningful and productive collaboration remains difficult to accomplish, gauge and guide.In this keynote, I will reflect on the complexity of the collaborative learning process and what it implies for researching these processes from an ecological perspective using new analytics techniques. Outcomes of collaborative learning have been examined extensively through scaled assessments and sociocultural studies continue to reveal new knowledge about the dialogical nature of collaborative learning. Yet remaining are questions about how individual cognitions are joined into productive interaction, how collaboration dynamics are shaped or what drives collaboration when difficulties occur. Against this backdrop, and taking departure in empirical research on small group collaboration in higher education contexts, I will discuss (i) the need for examining the collaborative process as an interrelated set of actions, people and resources – the ecosystem of collaborative learning, (ii) individual and collective factors salient to collaborative learning, and (iii) the multimodal nature of in-situ collaboration. Further, I will elaborate on how digital technologies and data-based analytic techniques offer new opportunities to examine some of the ‘black-boxed’ aspects of collaborative learning.This presentation will also consider the challenges of researching collaborative learning processes. First, I will address methodological challenges, primarily focusing on the pitfalls of reductionistic interpretation and the need for methodological triangulation. Second, I discuss a combined empirical and conceptual challenge; as digital traces of collaboration are disclosed through new digital technologies and analytical techniques, the question of what constitutes collaboration becomes highly relevant. I will conclude by exploring the implications of examining the ecosystem of collaborative learning for how we are framing education to prepare a young generation to jointly engage with present and future hardships.
Daniel is presenting work on how teachers give feedback on collaboration in nursing simulations:
Title and abstract
"Automated Feedback and Learning Design for Collaborative Problem Solving in Simulation Scenarios."
Despite the proliferation of automatic tools that aim to support collaborative learning, little is understood about how feedback generated by these tools is integrated in simulation-based learning design. This gap is critical as it pinpoints how different ways of combining learning design elements and automated feedback create opportunities for learners to collaborate and engage with knowledge in productive ways. This study uses a design-based research and participatory design approach in a high-fidelity simulation-based learning design in nursing education. The study seeks to identify how teachers initially conceive automated feedback as part of their learning design and how they gradually adjust both feedback and learning design in light of empirical evidence. It does so by taking a departure point in models based on research literature and by analysing multiple data sources: observations of simulations, records from co-design meetings, usability testing, user experience (UX) review, and teacher interviews. Findings from these analyses will feed into future developments of automated feedback in collaborative settings.
We also are part of a symposium on multimodal analytical approaches in researching collaborative problem solving, where we present our scoping review:
Title and abstract
"Multimodal collaboration analytics in collaborative problem solving – a scoping review”
In higher education programs, collaborative learning plays a pivotal role, involving students working together in groups or teams. The continuous advancement of technology has opened new possibilities for analyzing and facilitating students' learning through multimodal collaboration analytics (MMCA). To gain a comprehensive understanding of this field, we conducted a scoping review, examining 38 relevant studies that employed MMCA. Our analysis focused on various aspects, including the studies' demographics, methodologies, theoretical frameworks, technical aspects, and empirical findings. Particular attention was given to investigating the combinations of modalities and sensors utilised in these MMCA studies, aiming to uncover their explicit or implicit impact on the conceptualization of collaborative learning. Most of the studies (n=18) combined data from two modalities, followed by 15 studies combining three modalities and three studies combining four modalities. The most prevalent combination observed was audio/visual (n=8), closely followed by audio/visual/tactile modalities (n=6). Other frequently utilised combinations include audio/kinesthetic (n=4) and audio/visual/physiological modalities (n=4). Additionally, three studies combined audio and tactile data (n=3), while two studies used two sub-categories within one modality.
ICQE 2023, Melbourne
Rogers is presenting an epistemic network analysis of group dynamics of a student group in our case study at the Law Faculty:
Title and abstract
"Understanding Group Dynamics During Synchronous Collaborative Problem-solving Activities: An Epistemic Network Approach"
Collaborative problem-solving (CPS) is important in today’s fast-paced and interconnected world. However, assessing and supporting CPS skills and actions in online and co-located collaborative settings is challenging for researchers and teachers. To identify individual and group CPS behavioural patterns, this study employs epistemic network analysis (ENA) in analysing, modelling and visualising the collaborative discourse data of legal students working on an ill-structured problem in a semester-long course. The results showed that individual students’ contributions differed across the two meetings, engaging primarily in the planning phase of self-regulation with limited presence of reflection. We provide implications for researchers working in CPS and underscore the need for multimodal datasets to understand students’ CPS behaviours clearly.