Current interactive media presentations of textiles provide an impoverished communication of their 'textile hand', that is their weight, drape, how they feel to touch. These are complex properties experienced through the visual, tactile, auditory and proprioceptive senses and are currently lost when textile materials are presented in interactive video. This paper offers a new perspective from which the production of multi-touch interactive video representations of the tactile qualities of materials is considered. Through an understanding of hand properties of textiles and how people inherently touch and handle them, we are able to develop methods to animate and bring these properties alive using design methods. Observational studies were conducted, noting gestures consumers used to evaluate textile hand. Replicating the appropriate textile deformations for these gestures in interactive video was explored as a design problem. The resulting digital textile swatches and their interactive behavior were then evaluated for their ability to communicate tactile qualities similar to those of the real textiles.
While shopping online for textiles from a mobile device, we face the perceptual gap between qualities we can perceive via the interface and those we sense when handling the real textile product. In this research I first investigate the qualities that people look for when interacting with textiles. Further, I examine the gestures people commonly use to handle fabrics, and I propose a way to imitate them on a mobile device. Finally, I prototype touch-screen interactive-video interfaces and assess best practice.
In this paper we provide an account of how we ported a text and data mining course online in summer 2020 as a result of the COVID-19 pandemic and how we improved it in a second pilot run. We describe the course, how we adapted it over the two pilot runs and what teaching techniques we used to improve students' learning and community building online. We also provide information on the relentless feedback collected during the course which helped us to adapt our teaching from one session to the next and one pilot to the next. We discuss the lessons learned and promote the use of innovative teaching techniques applied to the digital such as digital badges and pair programming in break-out rooms for teaching Natural Language Processing courses to beginners and students with different backgrounds.
In this paper we provide an account of how we ported a text and data mining course online in summer 2020 as a result of the COVID-19 pandemic and how we improved it in a second pilot run. We describe the course, how we adapted it over the two pilot runs and what teaching techniques we used to improve students' learning and community building online. We also provide information on the relentless feedback collected during the course which helped us to adapt our teaching from one session to the next and one pilot to the next. We discuss the lessons learned and promote the use of innovative teaching techniques applied to the digital such as digital badges and pair programming in break-out rooms for teaching Natural Language Processing courses to beginners and students with different backgrounds.1 EFI is a new institute at the University of Edinburgh which will support interdisciplinary research and teaching for the whole institution. https://efi.ed.ac.uk
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