Maskinlæring i folkeskolen: Fra tekniske til teknologikritiske kompetencer

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

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

In this article, first results are presented from a three-year research project that aims to investigate how secondary school students develop an understanding of artificial intelligence in science contexts. Specifically, we have conducted a pilot test of parts of a technology comprehension course in the spring-summer of 2023, where students in groups should design their own machine learning model and app. Our approach was based on a broad perspective of technology comprehension as an interconnection between technical competences, design competences and technology-critical competences. Despite this, our initial experiences point to challenges in progressing from a practical level to a more reflective level. The article discusses this issue and what it means for future research.
Original languageDanish
Volume24
Issue number4
Pages (from-to)54-69
Number of pages16
ISSN2245-8948
Publication statusPublished - 2024

Cite this