What and how do we measure in learner-learner interaction research? Irena Galikyan (doctoral student at ICLON) defends her thesis on this subject on April 14.
Growing data on learner-learner interaction
Learner-learner interaction refers to the communication between learners enrolled in a course. In digital learning environments, learner-learner interactions are largely “forced” on learners in the hope that these interactions will compensate for the limited instructor presence if necessary. This inevitably results in more and more data on learner-learner interactions and more and more analyzes of this data. However, the multitude of data and analysis does not provide clear answers about the role that learner-learner interaction plays in learning in digital learning environments.
Galikyan’s thesis examines how the multidimensionality of learner-learner interaction data and the multi-facet of learner-learner interaction itself impact the measurement of learner-learner interaction in learning environments digital.
Despite the abundance of data on learner interaction, we are still unable to spot the good, the bad, and the ugly. On the other hand, the theses demonstrate the complexity with which the different aspects of learner-learner interaction, captured by the different approaches to the measurement of learner-learner interaction, interrelate in learning in learning environments. digital.
Journey through a maze
Galikyan concludes that measuring learner-learner interaction is often like traveling through a maze. Researchers must be ready to start maneuvering through the maze and choosing appropriate pathways as soon as they decide to study learner-learner interaction in digital learning environments. The choices are almost endless and are sometimes so small that they can seem insignificant. Moreover, each choice will have its own weight and impact on the measurement of learner-learner interaction.