I report on how the latest app technology (Video Enhanced Observation) can be used to research which features of a speaker’s talk listeners notice at which exact time during a video. The same video can be played to any number of users anywhere in the world, who each record what they notice when, and how they analyse or evaluate the talk.
In the film Rashomon, a number of people provided different, conflicting accounts of the same event. This problem of intersubjectivity also applies to language teaching and testing, as the same L2 speaking performance may be analysed and evaluated in very different ways by different teachers/testers. Given that language teaching and testing are huge global industries, it would be helpful to be able to understand this problem and consider how teachers'/testers' perspectives might be harmonised to a greater extent. The issue is relevant to CA practitioners in that data workshops of L2 lessons are in effect exercises in developing intersubjectivity in relation to interactional episodes. I report on how the latest app technology (Video Enhanced Observation) can be used to research which features of a speaker's talk listeners notice at which exact time during a video. Listeners can write notes or analyses and evaluate the talk. We developed a graphical means of representing the 'noticing trajectories', as well as the degrees of convergence and divergence of the listeners' perspectives. This also enables investigation of the reasons for convergence/divergence. I illustrate this by reference to a funded study of the IELTS Speaking Test (Seedhouse and Satar, 2021). Finally I discuss how this approach works with L2 classroom interaction. The same video can be played to any number of users anywhere in the world, who each record what they notice when, and how they analyse or evaluate the talk. This raises the prospect of a future worldwide online CA data workshop in which large numbers of people all view the same L2 classroom data and record what they notice.
