Back

Socio‐scientific issues instruction for scientific literacy: 5E Framing to enhance teaching practice.

  • Published In: School Science & Mathematics, 2024, v. 124, n. 3. P. 203 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Owens, David C.; Sadler, Troy D. 3 of 3

Abstract

Socio‐scientific issues (SSI) instruction positions the understanding and practice of science in the context of issues that are informed by science but require reasoning about their societal dimensions to respond to those issues effectively. For this reason, instruction in the context of SSI has been considered the gateway to contemporary visions of scientific literacy. SSI instruction is often framed in line with the Socio‐Scientific Issues Teaching and Learning (SSI‐TL) framework, which is prominent in the literature and well‐used by researchers to frame professional development but potentially less familiar to classroom teachers. Given that teachers are likely familiar with the 5E learning cycle, they might experience an easier transition to developing and facilitating SSI instruction using the SSI‐TL model if framed through a lens of 5E. In this article, we unpack the SSI‐TL model of instruction through a 5E lens, then provide an exemplary prototype of the new SSI‐TL infused 5E instruction in the context of a globally relevant SSI to highlight the overlap between engagement in essential science practices and socio‐scientific reasoning. We hope that teachers become more comfortable developing science literacy by addressing both science and societal dimensions of contemporary SSI by considering the SSI‐TL Framework through a 5E lens. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:School Science & Mathematics. 2024/06, Vol. 124, Issue 3, p203
  • Document Type:Article
  • Subject Area:Education
  • Publication Date:2024
  • ISSN:0036-6803
  • DOI:10.1111/ssm.12626
  • Accession Number:177677256
  • Copyright Statement:Copyright of School Science & Mathematics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.