Joint Research Program
Learning, Technology and Knowledge-in-Action
The core problem we are addressing
At the heart of this research program – the core problem – is the need for a better understanding of relations between knowledge and action. This manifests itself in a variety of ways:
- Why does so much of the knowledge taught in formal education end up being inert and fragmented?
- Why do new graduates find it hard to apply what they know in the workplace?
- When expert knowledge becomes tacit, how can it be reflected upon, or shared with others?
- How do our skills in using language, interacting with others and interpreting situations affect our ability to make use of the rest of what we know?
The problem is complicated by the accelerating interpenetration of the digital and material worlds – not just mobile devices, but augmented realities, ubiquitous computing and the ever-increasing mediation of communications technologies in work and social life. These technological developments rearrange the relations between knowledge and action. They make it harder to define the nature of expertise, skill and capability – but they also offer sharper tools for research and richer contexts for learning.
The novelty of our approach
Conventional wisdom suggests that the difficulties people have in applying knowledge are the result of shortcomings in the processes of learning and teaching. Our position is that effective action in the world depends on more complex configurations of knowledge than convention supposes. We need more rigorous analyses of real-world expertise, to inform innovations in educational processes.
The novelty and timeliness of our research program spring from three insights:
- fluent use of knowledge in action – including conceptual knowledge - depends upon skills acquired through practical experience – ‘skill is the very ground of knowledge and not merely its application’ (Ingold)
- skill, action and learning are the achievement of an ‘extended mind’ – of a person or group plus the tools, artefacts and other resources that come to hand, operating as an interdependent system
- learning is increasingly fragmented across experiences, time, space, media, epistemologies and organizational boundaries. Research is needed that can help understand the nature of learning over the longer-term: cumulative, coherent and applicable.
Organization of our research program
Our research program consists of four interlocking strands of work, supported by a ‘virtual collaboratory’ (for innovation in research tools and methods), all grounded in the realities of learning and teaching in two important application domains: initial and continuing education for professional work (especially in Medicine and Teaching) and education in the science, technology, engineering and maths (STEM) disciplines.
Research Strand A:
The analysis of knowledge-in-action - analyzing expertise as it manifests itself in modern life. How best can we represent skill, deep understanding, disciplinary thinking, professional identity, robust actionable knowledge – especially when knowledge and capability are distributed (across people, tools and artefacts) and when they blend tacit and explicit knowledge, as well as language and perception in action? Also, what capacities underpin invention and mastery of new technologies and working practices? The Strand A team focuses on examples for analysis from the STEM and professional work areas (including engineering and IT, spanning both). Applying cutting edge research from linguistics, the sociology of knowledge, psychology and human-computer interaction, they compare and contrast insights gained from analyzing:
- disciplinary and professional knowledge practices, using constructs from Legitimation Code Theory, linguistics and literacy, and the study of epistemic fluency, creativity and invention;
- ecologies of tools, instruments, activity and knowledge, using constructs from Activity Theory, ergonomics, Science and Technology Studies, ecological psychology and the study of computer-supported co-operative work (CSCW).
Research Strand B:
Designing, creating, evaluating and improving innovative technologies for closer human:computer interaction – natural user interfaces; lifelong learner modeling; affective technologies; collaboration tools for design, writing, and scientific inquiry; augmentation tools for reflecting in and on action. This requires research at the frontiers of computer science and engineering, to solve complex problems of systems and tool design. Our work focuses on the creation of effective new software and hardware systems. These will provide new forms of interaction for learning. They will collect long-term data on how the technology is being used, its impact on learning, behaviour and affect. This multimodal platform requires contributions at the core of some of the Grand Challenges in Computer Science: security, scalability, privacy, data integration and interfaces for augmented cognition.
Research Strand C:
Constructing and testing innovative designs for learning – new combinations of pedagogy, technology, activity - with a focus on learning that aligns with our analyses of expertise, and uses of technology that close the gaps between knowledge and action: e.g. simulation-based learning, modeling environments, collaborative inquiry and design, virtual and augmented realities, epistemic games, performance support tools. Our work here is at the leading edge of developments in the science and technologies of learning – blending performance support and the acquisition of expertise.
Research Strand D:
Translational R&D that can improve learning and teaching outcomes - working with those best placed to understand how to promote such changes, especially in STEM education (mainly through the Institute for Innovation in Science & Maths Education), and education for the professions (mainly through the Workforce Education & Development Group in Medicine). This design-based research activity involves the iterative development and testing of new combinations of pedagogy, technology and physical/virtual space. It will feed the development of new theories of learning and knowledgeable action and also inform innovations in educational approaches and learning environments across the University.
The virtual collaboratory (CoLab).
Innovative research tools can bring major breakthroughs. The CoLab will be a focus for methodological innovation, pioneering e-research methods, providing access to new research tools and datasets, aimed at modeling, monitoring and helping manage learning processes and contexts. It will augment and help integrate the four existing physical labs run by the CoCo, CHAI, Latte and Design Computing & Cognition teams and will provide methodological resources for the joint doctoral program and related capacity-building activities. E-research for education, including the use of educational data-mining, and micro-genetic analysis of skill, learning and development are key strengths at Sydney. The methodological innovation work includes the refinement of e-research techniques, including event-based process modeling and visualisation. We will also be sharpening the application of ethnographic, ethnomethodological, linguistic and phenomenological research methods, for use in complex, technology-rich settings.