Current theories of gesture production all suggest that spatial working memory is a critical component of iconic gesture production. However, none of the models has a selection mechanism for what aspect of spatial working memory is gestured. We explored how expert and journeyman scientists gestured while discussing their work. Participants were most likely to make iconic gestures about change over time (spatial transformations), less likely to gesture about spatial relations and locations (geometric relations), and far less likely to gesture about the magnitude of spatial entities. We also found that experts were especially likely to have a high degree of association between iconic gestures and spatial transformations. These results show that different features of spatial language are gestured about at different rates. We suggest that current gesture production models need to be expanded to include selection mechanisms to account for these differences.
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Nutrient runoff from catchments that drain into the Great Barrier Reef (GBR) is a significant source of stress for this World Heritage Area. An alliance of collaborative on-ground water quality monitoring (Project 25) and technologically driven digital application development (Digiscape GBR) projects were formulated to provide data that highlighted the contribution of a network of Australian sugar cane farmers, amongst other sources, to nutrient runoff. This environmental data and subsequent information were extended to the farming community through scientist-led feedback sessions and the development of specialised digital technology (1622™WQ) that help build an understanding of the nutrient movements, in this case nitrogen, such that farmers might think about and eventually act to alter their fertilizer application practices. This paper reflects on a socio-environmental sustainability challenge that emerged during this case study, by utilising the nascent concept of digi-grasping. We highlight the importance of the entire agricultural knowledge and advice network being part of an innovation journey to increase the utility of digital agricultural technologies developed to increase overall sustainability. We develop the digi-MAST analytical framework, which explores modes of being and doing in the digital world, ranging from ‘the everyday mystery of the digital world (M)’, through digital ‘awareness (A)’, digitally ‘sparked’ being/s (S), and finally the ability of individuals and/or groups to ‘transform (T)’ utilising digital technologies and human imaginations. Our digi-MAST framework allows us to compare agricultural actors, in this case, to understand present modes of digi-grasping to help determine the resources and actions likely to be required to achieve impact from the development of various forms of digital technological research outputs.
Digital transformation within agriculture involves advances in information and communication technologies that promise a 'next generation' of agricultural technologies that will drive improvements in productivity and efficiency while reducing risks and negative impacts. Here, we discuss the Digiscape Future Science Platform, a program that seeks to facilitate the digital transformation of Australia's agricultural industries and land sector. Digiscape is one example of significant efforts internationally to realise the transformative potential of digital agriculture. However, there are significant socio-ethical challenges associated with digital agriculture. Responsible innovation (RI) provides one conceptual lens to address such challenges, acknowledging the power of research and innovation to create the future and posing questions about the types of futures that societies want to encourage or avoid. This article uses insights from rural sociology and innovation studies, which can complement RI dimensions-anticipation, inclusion, reflexivity and responsiveness-to reflect on how RI can be This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
This paper reports on a laboratory study into the gesture representation interface for remote collaboration on physical tasks. Measured by task performance and user's perception of interaction, the experiment assessed two gesture representations (hands vs. cursor pointer) in the context of a video mediated interface which included a view of the remote partner. We did not find any significant difference between the hands condition and the pointer condition when measuring user's task performance. However, our result showed that participants reported an overall preference of using the pointer functionality than using the hands'. We found that participants perceived higher quality of interaction in the hands condition than in the pointer condition and there was a significant difference. Additionally, majority of the participants valued the ability of being able to see each other's face during the collaboration. We conclude with a discussion on the importance of accounting for the user's perception of interaction in addition to the traditional task performance measure in evaluating gesture representation interface, and the importance of considering these two factors in recommending the most suitable interface design with gesture representation for collaboration on physical tasks.
Many private and public actors are incentivized by the promises of big data technologies: digital tools underpinned by capabilities like artificial intelligence and machine learning. While many shared value propositions exist regarding what these technologies afford, public-facing concerns related to individual privacy, algorithm fairness, and the access to insights requires attention if the widespread use and subsequent value of these technologies are to be fully realized. Drawing from perspectives of data science, social science and technology acceptance, we present an interdisciplinary analysis that links these concerns with traditional research and development (R&D) activities. We suggest a reframing of the public R&D ‘brand’ that responds to legitimate concerns related to data collection, development, and the implementation of big data technologies. We offer as a case study Australian agriculture, which is currently undergoing such digitalization, and where concerns have been raised by landholders and the research community. With seemingly limitless possibilities, an updated account of responsible R&D in an increasingly digitalized world may accelerate the ways in which we might realize the benefits of big data and mitigate harmful social and environmental costs.
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