1,044
Views
14
CrossRef citations to date
0
Altmetric
Articles

Identifying and formulating teachers’ beliefs and motivational orientations for computer science teacher education

, , , &
Pages 1958-1973 | Published online: 03 Feb 2015
 

Abstract

How teachers are able to adapt to a changing environment is essentially dependent on their beliefs and motivational orientations. The development of these aspects in the context of professional competence takes place during teachers’ educational phase and professional practice. The overall understanding of professional competence for teaching computer science follows the notion of empirical educational research including beliefs and motivational aspects. This article aims to investigate relevant domain-specific beliefs and motivational orientations for teaching computer science and their consideration in curricula for computer science teacher education. Therefore, results of an expert interview study based on the critical incident technique lead to appropriate descriptions for domain-relevant beliefs and motivational orientations. Results of a broad curriculum analysis indicate how those aspects are normatively considered in computer science university and school education in Germany. The data were analyzed by qualitative content analysis.

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

The research initiative is funded by the German Federal Ministry of Education and Research [grant number 01PK11019A, B, C].

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 678.00 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.