Aarhus Universitets segl

Three recommendations to engage At-Risk Students in Critical Reflection on Intelligent Technologies through Remote Learning

Publikation: Bidrag til bog/antologi/rapport/proceedingKonferencebidrag i proceedingsForskningpeer review

DOI

  • Marie Monique Schaper
  • ,
  • Aurelio Ruiz Garcia, Pompeu Fabra University

The agenda of Computational Empowerment points towards the need for inclusive approaches for supporting all students in learning about technology and the development of digital literacy. This paper aims at exploring how to develop remote learning activities in technology education during a pandemic for at-risk students. We present a case study with 23 primary students (11-12 years) who we involved in online and offline learning activities about both how intelligent technologies work but also on the implications that these technologies bring to our society. Our findings showed potential challenges to engage at-risk students in the agenda of Computational Empowerment. We propose three recommendations and future directions to scaffold at-risk students' learning about intelligent technologies in remote contexts: (1) support the development of agency through the engagement of contexts-for-action; (2) reduce the complexity of remote communication through creative and bodily engagement; (3) reflect upon forces that marginalize oneself in a digitized society.

OriginalsprogEngelsk
TitelCHI 2023 - Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems
UdgivelsesstedHamburg
ForlagAssociation for Computing Machinery
Udgivelsesårapr. 2023
Artikelnummer400
ISBN (Elektronisk)9781450394222
DOI
StatusUdgivet - apr. 2023
Begivenhed2023 CHI Conference on Human Factors in Computing Systems, CHI 2023 - Hamburg, Tyskland
Varighed: 23 apr. 202328 apr. 2023

Konference

Konference2023 CHI Conference on Human Factors in Computing Systems, CHI 2023
LandTyskland
ByHamburg
Periode23/04/202328/04/2023
SponsorACM SIGCHI, Apple, Bloomberg, Google, National Science Foundation, Siemens
SerietitelConference on Human Factors in Computing Systems - Proceedings

Se relationer på Aarhus Universitet Citationsformater

ID: 322162826