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The trend to adopt more online technologies continues unabated in the higher education sector. This paper elaborates the means by which such technologies can be employed for pedagogical purposes beyond simply providing virtual spaces for bringing learners together. It shows how data about student 'movement' within and across a learning community can be captured and analysed for the purposes of making strategic interventions in the learning of 'at risk' students in particular, through the application of social network analysis to the engagement data. The study that is set out in the paper indicates that online technologies bring with them an unprecedented opportunity for educators to visualise changes in student behaviour and their learning network composition, including the interventions teachers make in those networks over time. To date, these evaluative opportunities have been beyond the reach of the everyday practitioner - they can now be integrated into every teaching and learning plan.

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The ability to develop new skills and competencies is a central concept of lifelong learning. Research to date has largely focused on the processes and support individuals require to engage in upskilling, re-learning or training. However, there has been limited attention examining the types of support that are necessary to assist a learner's transition from 'old' workplace contexts to 'new'. Professionals often undergo significant restructuring of their knowledge, skills, and identities as they transition between career roles, industries, and sectors. Domains such as LA have the potential to support learners as they use the analysis of fine-grained data collected from education technologies.

However, we argue that to support transitions throughout lifelong learning, LA needs fundamentally new analytical and methodological approaches. To enable insights, research needs to capture and explain variability, dynamics, and causal interactions between different levels of individual development, at varying time scales. Scholarly conceptions of the context in which transitions occur are also required. Our interdisciplinary argument builds on the synthesis of literature about transitions in the range of disciplinary and thematic domains such as conceptual change, shifts between educational systems, and changing roles during life course. We highlight specific areas in research designs and current analytical methods that hinder insight into transformational changes during transitions. The paper concludes with starting points and frameworks that can advance research in this area.

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This discussion paper responds to the high level of investment higher education leaders are currently making in data analytics. Australian higher education institutions are devoting considerable resources to better understand the factors that impact student retention and success. The imperative for developing a national learning analytics policy and strategy that evaluates current international practice and proposes key enabling suggestions to guide education executives and government officials in future decision making is presented. The need for a more coordinated and systemic approach arises from pressures surrounding quality assurance and reporting mechanisms, increased student diversity and mobility, budgetary constraints and establishing a competitive advantage for Australian universities within the global education market.

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