Studying collaborative learning space design with multimodal learning analytics

Resumen

Research has provided relevant advances regarding evidence-based design for productive learning. For example, in the field of collaborative learning, there is extensive evidence about some key learning design elements, such as about methods to structure the sequence of activities, about group formation techniques or about technology mediating collaboration. However, advances have been more limited in the line of evidence-based design of collaborative learning physical spaces. Contradictorily, research on learning spaces and their impact on teaching and learning have been a field of inquiry for decades. Existing studies have explored how learning spaces can have a role in inhibiting or encouraging students’ participation in active learning tasks, such as those applying collaborative learning methods. But the methods used in these studies have provided limited empirical evidence about the effects of specific design elements of collaborative learning spaces on students’ behaviours. In this context, technological advances regarding data capture and analysis tools open new opportunities and challenges to overcome this lack of evidence. In particular, Multimodal Learning Analytics (MMLA) approaches are seen with increasing potential to advance learning space research. This dissertation contributes to emerging MMLA research aiming at disentangling the effects of space design elements and their interaction with other learning design elements, to help advance the evidence-based design spectrum towards more fruitful learning. In particular, the thesis focuses on the interaction of table shapes in learning spaces with the group size learning design element. The dissertation also explores the relevant but often neglected, gender perspective. An experimental design methodology is applied with the aim to answer research questions related to (1) the difference in students' behaviour when two table shapes and two group sizes are used, (2) indicators relevant for collaborative learning space research and (3) data collection, analytical and visualization techniques. Contributions include first empirical evidence about the influence of the table shape on student behavior, with effects arising from the interaction of table shape with group size and student gender. Moreover, the dissertation offers a new case that discusses MMLA indicators in this field and explores how motion capture, temporal analysis and aggregated visualization can contribute to collaborative learning space research.