A Quantitative Methodology For Determining the Critical Benchmarks for Project 2061 Strand Maps

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Kuhn, G. (2008). A Quantitative Methodology For Determining the Critical Benchmarks for Project 2061 Strand Maps. Journal of Computers in Mathematics and Science Teaching, 27(3), 299-324. Chesapeake, VA: AACE.
Retrieved from http://www.editlib.org/p/24200.

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Journal Information

Journal of Computers in Mathematics and Science Teaching
ISSN 0731-9258
Volume 27, Issue 3, July 2008
Association for the Advancement of Computing in Education (AACE)  Chesapeake, VA

More Information on JCMST

Author

G Kuhn, Tanner Corp., United States

Abstract

Abstract The American Association for the Advancement of Science (AAAS) was tasked with identifying the key science concepts for science literacy in K-12 students in America (AAAS, 1990, 1993). The AAAS Atlas of Science Literacy (2001) has organized roughly half of these science concepts or benchmarks into fifty flow charts. Each flow chart or strand map contains only those AAAS benchmarks relevant to that specific area of K-12 science education. While all the connections and benchmarks are needed for complete K-12 science literacy in that science topic, it is reasonable to assume that some of the blocks and connections are more critical than others. This study develops a quantitative algorithm identifying the specific linear sequence of K-12 benchmarks containing the highest information potential for a subset of Project 2061 strand maps relating to a single topic. As such it represents the shortest and most efficient topical K-12 science-learning path. Science educators should focus their teaching expertise and assessment skills on this defined set of benchmarks in each strand map. It is also where local administrators should focus their funding and science curriculum publishers focus their authoring.

Keywords

• Standards
• Elementary Education
• Secondary Education
• Developmental Stages
• Administrators
• Computer Sciences
• Information Sciences
• Sciences
• Learning Objects
• Teaching Methods

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