167
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Investigating U.S. and German pre-service teachers’ beliefs regarding digital technology

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Received 30 May 2022, Accepted 19 Sep 2023, Published online: 17 Oct 2023
 

ABSTRACT

Based on different educational policies around the world, pre-service teachers are expected to use digital technology in their future teaching in school. However, to do this successfully, they need knowledge, skills and appropriate beliefs regarding utilising digital technology in learning scenarios. Thus, this study explores pre-service teachers’ beliefs regarding current digital technologies in their learning and future teaching. 232 pre-service teachers from Germany and the US participated in the comparative study and responded to the Digital Technologies Survey. The results show that overall pre-service teachers’ beliefs regarding digital technology in learning and teaching are on a moderate level. However, significant differences were seen between pre-service teachers from Germany and the US. For US pre-service teachers, digital technology seems more important and helpful for their current learning and future teaching than for German pre-service teachers. The same can be seen for self-assessed competence. The results and further implications are discussed.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,177.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.