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| Funder | European Commission |
|---|---|
| Recipient Organization | Universitaet Muenster |
| Country | Germany |
| Start Date | Dec 01, 2024 |
| End Date | Nov 30, 2028 |
| Duration | 1,460 days |
| Number of Grantees | 13 |
| Roles | Participant; Coordinator; Associated Partner |
| Data Source | European Commission |
| Grant ID | 101169131 |
Spatial communication is fundamental to our species.
Spatial terms, including spatial adpositions and demonstratives, are among the most frequent terms in languages and form the key connection between language and objects/locations in the world.
Yet little is known regarding how spatial communication changes as one ages in later life and across different spatial scales and media.
The focus of SCALA is to understand fundamentally how spatial communication changes in typical and atypical ageing across spatial scales, and how technology may be harnessed to afford enhanced understanding of spatial communication and support for spatial communication when needed in the context of an increasingly ageing European population.
This DN will train the next generation of scientists in the full range of multidisciplinary and cross-sectorial methods necessary to make significant progress in understanding human-human and human-technology spatial communication across time and scales, with direct synergies between basic research and application.
Training is structured around two interdisciplinary research themes - Spatial Communication in Typical and Atypical ageing, and Spatial Communication, Technology and Ageing - both involving systematic co-supervision and collaboration across sites, with extensive interplay between academic and non-academic beneficiaries and associated partners.
In turn we expect that a range of applications will be enhanced with increased usability, and with associated societal and economic benefit.
The training of the cohort of Doctoral Candidate Fellows follows innovative PhD training approaches and will provide comprehensive interdisciplinary training, embracing leading peer assisted learning methods that have been successively employed in previous DNs.
This will produce a cohort of unique and highly skilled researchers ideally equipped to add significant value to both the public and private sectors.
Aarhus Universitet; Universitaet Muenster; University of East Anglia; The University of Manchester; Mipsoft Oy; Tobii Ab; Universita Degli Studi Di Firenze; Beemo Gmbh; 52 North Spatial Information Research Gmbh; Friedrich-Schiller-Universität Jena; Consiglio Nazionale Delle Ricerche; Sony Corporation; Norges Teknisk-Naturvitenskapelige Universitet Ntnu
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