Identifying engagement patterns with video annotation activities: A case study in professional development

Abstract

The rapid growth of blended and online learning models in higher education has resulted in a parallel increase in the use of audio-visual resources among students and teachers. Despite the heavy adoption of video resources, there have been few studies investigating their effect on learning processes and even less so in the context of academic development. This paper uses learning analytic techniques to examine how academic teaching staff engage with a set of prescribed videos and video annotations in a professional development course. The data was collected from two offerings of the course at a large research-intensive university in Australia. The data was used to identify patterns of activity and transition states as users engaged with the course videos and video annotations. Latent class analysis and hidden Markov models were used to characterise the evolution of engagement throughout the course. The results provide a detailed description of the evolution of learner engagement that can be readily translated into action aimed at increasing the quality of the learning experience.