Learner–learner interaction in digital learning environments: what and how are we measuring?
Galikyan’s dissertation examines how the multidimensionality of learnerlearner interaction data and the multifacetedness of learner-learner interaction itself impact the measurement of learner-learner interaction in digital learning environments.
- Irena Galykian
- 14 April 2022
- Fulltext in Scholarly Publications Leiden University
This dissertation intended to examine how the multidimensionality of learner–learner interaction data and the multifacetedness of learner–learner interaction itself impact the measurement of learner–learner interaction in digital learning environments. The studies reported in this dissertation demonstrate that, on the one hand, the impact is reflected in the degree of variability with which learner–learner interaction is measured in research. The variability is determined both by the variety of the types of data on learner–learner interaction and by the variety of approaches that can be taken to the measurement of learner–learner interaction based on the different types of data.
On the other hand, the impact is reflected in the intricacy with which the different aspects of learner–learner interaction, captured by the different approaches to the measurement of learner–learner interaction, interdepend in learning in digital learning environments. The studies, presented in this dissertation, taken collectively fulfil the triple function of (a) refining our understanding of learner–learner interaction; (b) guiding and improving our interpretation of research findings on learner–learner interaction; and (c) providing guidance and pointers for research and practice, together with identifying the potential pitfalls in researching learner–learner interaction.