A model for collecting and analyzing action data in a learning process based on activity theory

Abstract

Research on learning analytics in technology-enhanced learning has recently been on the rise with the intent to support learners’ achievements, develop personalized learning environments, and improve learning methods. Learning analytics is a data analysis method intended to help understand learners’ tendencies toward activities and the significant aspects of such activities manifest in their teaching–learning process. In learning, an activity is comprised of a series of actions and then gives a couple of examples for different actions. To better understand a teaching–learning activity, the data from the stream of actions taking place need to be analyzed. To that end, this paper proposes a model for collecting and structuring the teaching–learning action data based on activity theory. The proposed model is designed to identify activities based on a series of learner actions over time. Among the components of activity theory, the model focuses on subjects, objects, and tools to collect data, which elucidates the use of tools that serve as the media between subjects (i.e., learners) and learning activities. The model offers insight into the continuity and persistence of objects or teaching–learning activity systems to better understand teaching–learning activities.