On the feasibility of using electronic textiles to support embodied learning

Olivia Ojuroye, Adriana Gabriela Wilde

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

Electronic textiles (e-textiles) have already proven their practical use in wearable garments and are now also beginning to feature in non-wearable items, such as in furniture and shared surfaces inside a smart home or driverless car interiors. E-textiles, whether worn or not, have the potential to support their users’ embodied learning on a variety of topics. Embodied learning can be supported with e-textiles being part of an Internet of Things (IoT) ecosystem, providing contextual information within a network capturing traces of behavioural and even biological data about its users. Individuals’ “digital identity” expands as the number of connected devices each individual possesses grows. Furthermore, using artificial intelligence (AI), increasingly personalised experiences can be tailored to users through the very devices they interact with. To ensure e-textiles’ data can be useful for this purpose, e-textiles need to be engineered to integrate with everyday activities and lifestyles. In particular, this chapter will examine e-textiles’ potential to be used as pedagogical conduit to facilitate individualised embodied learning experiences.
Original languageEnglish
Title of host publicationPerspectives on Wearable Enhanced Learning (WELL)
Subtitle of host publicationCurrent Trends, Research, and Practice
EditorsIlona Buchem, Ralf Klamma, Fridolin Wild
Place of PublicationCham
PublisherSpringer
ChapterPart IV
Pages169-186
Number of pages18
Edition1
ISBN (Electronic)9783319643014
ISBN (Print)9783319643007
DOIs
Publication statusPublished - 2019

Keywords

  • Electronic textiles
  • Embodied learning
  • Education
  • Internet of Things
  • Artificial intelligence

Fingerprint

Dive into the research topics of 'On the feasibility of using electronic textiles to support embodied learning'. Together they form a unique fingerprint.

Cite this