Data collection methods in Higher Education research are predominantly centred on surveys and interviews. As a result, much of our current knowledge of higher education practice is built on perception-based data. The purpose of this paper is to highlight developments in digital technologies that offer access to new types of data that allow us to investigate what actually occurs (reality of practice) rather than what is assumed to have occurred (perception of practice). The core of this new approach is the use of ‘sensor-based’ systems that offer live feeds of data over continual periods. The benefit of these new approaches is built on the emerging interest in understanding the impact that established patterns of behaviour have on the process of change/learning. Until now, the difficulty has been the lack of methods to capture such patterns: 1] the continuity needed to capture data over extended periods in order to analyse at a macro-level or 2] the ability to capture the detail required to analyse at a micro-level. In both cases, any process employed will result in the generation of enormous amounts of data. One of the challenges of these new approaches is how to manage the data volumes. The value therefore of these new approaches will be contingent on our ability to draw on emerging approaches within the field of big data analytics to find and develop relevant methods of data transfer, storage and analysis. Two examples from a study on academic practice will be presented to show what is possible: 1) the use of live computer monitoring software capturing application analytics and 2) the use of surveillance camera’s capturing live daily office-based practice. In both cases, data was collected from five lecturers over an entire semester (5,000+ hours per data set equating to 13TB data). The paper will discuss the various challenges, benefits and methods involved in the process of data capture, transfer, storage and analysis.
Addressing the theme/s of the Conference (up to 200 words recommended)
New academics feel the pressure to be more productive and efficient, but are unaware of how to achieve this. As one academic states: “ I know the papers I have published, classes I taught and progress my PhD's made-but how I achieved this is pretty vague: to-do lists mixed with lots of guilt and panic. I know I can be more productive, just not sure how to change, or if I want to”. This study is an attempt to take our gaze away from the recognised measures of academic action that are focused on outputs and to look instead at the very building blocks that underpin these outputs. On the surface, it is about the routine and mundane, but within this is a rich view of the very elements of academic practice. These new methods show that it is possible to exploit emerging technologies to enable academics to gain a better understanding of how they perform their daily functions and empower them to be more focused and strategic in their academic development.