329
Views
4
CrossRef citations to date
0
Altmetric
Articles

Science Teachers’ Ability to Self-Calibrate and the Trustworthiness of Their Self-Reporting

ORCID Icon &
Pages 280-299 | Published online: 22 Jan 2019
 

ABSTRACT

National and international standards documents are calling for science teachers to teach their students how to engage in the practices of science. Previous studies have found that most science teachers do not have the knowledge and skill to do this because they have not had experience engaging authentically in science. One way to overcome this problem is for science teachers to participate in short-term Research Experiences for Teachers. However, few studies have looked at teachers’ learning of science skills and practices in such experiences, and almost all have relied primarily on data self-reported by the teachers. In our previous studies we found that there is good reason to find these self-reported data suspect. Therefore, in this study we investigated the low calibration of teachers’ self-reports of their abilities to engage in research skills and practices and their abilities as measured by knowledgeable others, and here we suggest several reasons for this low calibration.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported in part by a grant from the National Science Foundation (Award No. 1200682).

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 132.00 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.