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Assessing the Genetics Content in the Next Generation Science Standards

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  • Katherine S Lontok
  • Hubert Zhang
  • Michael J Dougherty

Abstract

Science standards have a long history in the United States and currently form the backbone of efforts to improve primary and secondary education in science, technology, engineering, and math (STEM). Although there has been much political controversy over the influence of standards on teacher autonomy and student performance, little light has been shed on how well standards cover science content. We assessed the coverage of genetics content in the Next Generation Science Standards (NGSS) using a consensus list of American Society of Human Genetics (ASHG) core concepts. We also compared the NGSS against state science standards. Our goals were to assess the potential of the new standards to support genetic literacy and to determine if they improve the coverage of genetics concepts relative to state standards. We found that expert reviewers cannot identify ASHG core concepts within the new standards with high reliability, suggesting that the scope of content addressed by the standards may be inconsistently interpreted. Given results that indicate that the disciplinary core ideas (DCIs) included in the NGSS documents produced by Achieve, Inc. clarify the content covered by the standards statements themselves, we recommend that the NGSS standards statements always be viewed alongside their supporting disciplinary core ideas. In addition, gaps exist in the coverage of essential genetics concepts, most worryingly concepts dealing with patterns of inheritance, both Mendelian and complex. Finally, state standards vary widely in their coverage of genetics concepts when compared with the NGSS. On average, however, the NGSS support genetic literacy better than extant state standards.

Suggested Citation

  • Katherine S Lontok & Hubert Zhang & Michael J Dougherty, 2015. "Assessing the Genetics Content in the Next Generation Science Standards," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-16, July.
    • Handle: RePEc:plo:pone00:0132742
    DOI: 10.1371/journal.pone.0132742
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    1. Klaus krippendorff, 2004. "Measuring the Reliability of Qualitative Text Analysis Data," Quality & Quantity: International Journal of Methodology, Springer, vol. 38(6), pages 787-800, December.
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