Potentially disruptive IS innovation in UK higher education institutions: an actor-network theory analysis of the embedding of m-learning

Bird, Peter William (2014) Potentially disruptive IS innovation in UK higher education institutions: an actor-network theory analysis of the embedding of m-learning. Doctoral thesis (PhD), Manchester Metropolitan University.

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Abstract

The use of mobile devices to support students’ learning experiences is a growing area of interest in higher education (Wankel & Blessinger, 2013). This study adopts an ‘umbrella’ term of m-learning to consider the use of mobile and wireless technologies to support students in a blended learning environment. Whilst m-learning pedagogy has received considerable attention (e.g. Attewell, 2005, Sharples et. al. 2007, Kukulska-Hulme, 2012), the process of adopting this potentially disruptive innovation within universities has been neglected. This study addresses this gap by attempting to answer the research question: How do university organizations (business models, modes of operation, people and processes) adapt to a potentially disruptive innovation like m-learning and what factors and working practices support or hinder embedding? Possible frameworks for studying innovation are reviewed, including Rogers’ innovation diffusion framework (Rogers, 1962), Actor-Network Theory (Latour, 2005) , Activity Theory ngestr m 1987), Structuration Theory (Giddens, 1984), theories of disruptive innovation (Christensen, 1997) and the Technology Acceptance Model (Venkatesh and Davis, 2000), Actor-Network Theory (ANT) is chosen as the most promising theoretical lens for an in-depth investigation of m-learning embedding, and a participative fieldwork approach is developed that uses Law and Callon’s ANT notion of ‘points of passage’ between local and global networks (Law and Callon, 1991) to illuminate factors and working practices that affect embedding. A framework based on Law and Callon’s work is developed through a year-long study of competing text messaging projects within a university and developed further through a three-year, longitudinal case study involving five universities using smartphone applications to assess students in medical practice situations. Several institutional issues are identified that help or hinder embedding, such as fragmentation of IT strategy and decision-making, and the need to provide students with a compelling offer of multiple institutional services on their mobiles. The role of people and artefacts in forming a link, or ‘point of passage’ between m-learning projects ‘local networks’) and institutional IT strategies and services ‘global networks’) is found to be of central interest for understanding processes of embedding. A clear path to an ANT analysis is demonstrated starting from interview and observation data, using coding techniques borrowed from grounded theory (Schatzman and Strauss, 1973) and finishing with Law and Callon’s local-global network model, which is used to compare and contrast embedding trajectories of the case study institutions. Systematic comparison enables a three dimensional model of embedding trajectories to be built, which extends Law and Callon’s work and places in sharper focus the importance of establishing a path by which local initiatives can be evaluated strategically and, where appropriate, incorporated in a timely manner into a university’s IT strategy. Grounded in extensive longitudinal research, the study offers a contribution to methodology through its demystification of ANT; a contribution to theory through its three dimensional model for mapping embedding trajectories; and a contribution to practice by highlighting specific issues that affect mobile technology adoption in higher education, such as having a compelling, multi-service offer, appropriate mobile tariffs for undertaking mandatory assessment and guidelines for incorporating knowledge gained from technology experiments into institutional strategies and decision-making. The study concludes by highlighting opportunities for using its model to explore challenges of embedding faced not only by formal projects but by ‘maverick’ innovators and for potentially disruptive technologies other than m-learning, such as Web 2.0 services.