The potential of the ‘Internet of Things’ to enhance inquiry in Singapore schools

Dan Davies*, Gary Beauchamp, Jason Davies, Ruth Price

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
4 Downloads (Pure)

Abstract

Background: The Internet of Things (IoT) is a global network of data-sensing devices which pupils can access during science or other curriculum activities. Purpose: This article reports on a commissioned evaluation of a small-scale pilot project to explore the potential of the IoT combined with local sensors to enhance pupils’ data interpretation skills within inquiry-based approaches to primary science and secondary geography education. Sample: The project involved 14 teachers and 196 pupils from three primary and two secondary schools in Singapore. Design and methods: Using a mixed-method approach, the evaluation drew upon repeated video interviews with the teaching teams in each school, planning documentation and repeated pupil attitude surveys to determine the extent to which investigative and inquiry-based learning had been promoted; the contextual factors influencing effective implementation and the leadership expertise required to manage the project. Results: The combined use of IoT and local sensors appears to have effected some pedagogic change in participant teachers and led to some pupil learning gains in procedural skills; however significant technical and pedagogic challenges–together with tensions between time allocation and curriculum coverage–limited the extent to which the approach was embedded within classroom practice. Conclusion: This pilot project suggests strategies to meet the challenges associated with using the emergent technology of the Internet of Things to enhance inquiry-based science education.

Original languageEnglish
Pages (from-to)484-506
Number of pages23
JournalResearch in Science and Technological Education
Volume38
Issue number4
DOIs
Publication statusPublished - 17 Jun 2019

Keywords

  • Internet of Things
  • data interpretation skills
  • data-logging
  • inquiry-based learning
  • sensors

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