Improving agency using STS based approaches.
There are three main aspects of agency to consider in this research.
- The agency of students
- The agency of technologies
- The agency of sociotechnical systems
Agency of students
Recognising the need to adapt to the demands of twenty-first century social realities, there is a trend for universities to declare that they strive to create better equipped student researchers through partnership (i.e. Healey, Flint, & Harrington, 2016; Mercer-Mapstone et al., 2017).
This approach is called student-as-partner (SAP) and is focussed on the relationships between organisational members (for example, HDRs, supervisors, and university management) and the resulting processes derived from encouraging these relationships (Matthews, Dwyer, Hine, & Turner, 2018). The SAP approach to HE is one that considers the relationships between different actors or agents within an educational system (Matthews et al., 2018).
Additionally, in the interest of developing agency in students, by empowering them to manage and observe their own progress using new technological tools, they may be able to enhance their capability to ‘Learn to learn’ and take ownership of their own skills acquisition beyond methods already provided by universities and supervisors.
Agency of technology
The emerging field known as Machine Behaviour described by (Rahwan et al., 2019) is perhaps more a re-branding of Actor Network Theory and STS for a modern age than a completely new field. Nevertheless, it is an important field to recognise in this research as it explicitly focuses on the agency of technologies, machines, and algorithms in our human systems (Rahwan et al., 2019).
Scholarly research that falls under this heading is also closely connected with fields such as “human-machine networks” (Tsvetkova et al., 2017), “human-agent collectives” (Jennings et al., 2014), “cyber-physical systems” (Lee, Bagheri, & Kao, 2015), and a host of other variations of updated approaches to the system relationships between humans and machines.
One of the most useful aspects of the field of machine behaviour to the research proposed here, are the explorations of the ethical implications of machine agents in our human systems as well as the call for strong interdisciplinary study (Rahwan et al., 2019).
Agency of STS
The systems we employ in our universities, and that we ask students and staff to engage with have, an agentic impact on the construction of our organisations.
To understand how our STS can influence university outcomes – in this instance graduate research students – we can employ a well tested framework. Actor Network Theory (ANT) is a theoretical and methodological field of sociology originally developed by scholars Latour, Callon, Law, and Rip in Paris in the 1980’s that sought to understand the relationships in social and technology studies (Latour, 1996).
The highly useful aspect of the ANT approach to this thesis work, is that it describes the relationships between people and things (Law, 2007) and thus can be applied to systems where technologies and algorithms have agency (Bucher, 2018). The fundamentally constructivist nature of ANT makes it ideally suited to research seeking to understand co-constructed environments in STS in GRE environments.
Sociotechnical systems (STS) theory, is an extension of sociotechnical theory that combines human behaviourist and systems thinking approaches, and is a discipline aimed at designing better implementation models of technology into human systems by understanding the systematic co-constructive nature of humans, technology, and their environment (Baxter & Sommerville, 2011; Edwards, 2003). By looking at the relationships between people and their techne (material, structure, and process), and the behaviour of these people within their complex socio-technical systems, STS theory seeks to help us create organisational environments that facilitate the emergence of positive outcomes or at least, the reduction of negative outcomes.
The STS framework has been applied to educational policies for future workforces (Richey et al., 2014), learning communities in higher education (Jahnke, 2012), and in university management (Navarro, Bowles, & Walker, 2019). The field of STS can help us understand organisational dynamics of technological implementation more holistically than the more uni-dimensional models such as user acceptance testing (UAT) or user experience (UX) which are simple, single-loop feedback approaches to human-computer interaction (HCI).
Universities seeking to facilitate an adaptable organisation that readily accepts sociotechnical change would need to address the underlying structures that govern how people, technologies, and STS interact with one another to impact on the agency of all parties in the system.