Computer Science Education in Secondary School: A Real-Life Approach to Teaching Students Technology-Critical Aspects of AI

  • Elisa Nadire Caeli
  • , Cecilie Svane Pedersen
  • , Sine Zambach
  • , Morten Misfeldt
  • , Jeppe Bundsgaard

Publikation: Bidrag til bog/antologi/rapportKonferenceabstrakt i proceedingsForskningpeer review

Abstract

In this paper, we present a teaching material designed as part of a research project aiming to investigate approaches to teaching lower secondary school students technology-critical aspects of AI, specifically machine learning. The approach is scenario-based, meaning that students act in real-life roles, in this case in a fictional company that develops apps. The material has been tested in four classes in 2024, and analysis of the results is still ongoing. As part of our research, we examine whether and how a scenario-based approach contributes to understanding machine learning and its' use in the real world. Preliminary analysis suggests that participating students perceive the approach differently.
OriginalsprogEngelsk
TitelITiCSE 2025: Proceedings of the 30th ACM Conference on Innovation and Technology in Computer Science Education, Volume 2
RedaktørerErik Barendsen, Floor Binkhorst, Ángel Velázquez-Iturbide, Jaime Urquiza Fuentes, James Paterson, Keith Quille
Antal sider2
UdgivelsesstedNew York
ForlagAssociation for Computing Machinery
Publikationsdato2025
Sider727-728
ISBN (Trykt)9798400715693
ISBN (Elektronisk)9798400715693
DOI
StatusUdgivet - 2025
BegivenhedThe 30th ACM Conference on Innovation and Technology in Computer Science Education. ITiCSE 2025 - Radboud University, Nijmegen, Holland
Varighed: 30 jun. 20252 jul. 2025
Konferencens nummer: 30
https://iticse.acm.org/2025/

Konference

KonferenceThe 30th ACM Conference on Innovation and Technology in Computer Science Education. ITiCSE 2025
Nummer30
LokationRadboud University
Land/OmrådeHolland
ByNijmegen
Periode30/06/202502/07/2025
Internetadresse
NavnProceedings of the Annual Conference on Innovation & Technology in Computer Science Education
Vol/bind30
ISSN1942-647X

Emneord

  • Secondary school education
  • Scenario-based learning
  • Computer Science
  • Machine learning
  • AI

Citationsformater