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Blattner, Margaret; Hug, Barbara; Ogrodnik, Jon; Korol, Donna – Science Teacher, 2013
Generating, collecting, and analyzing data is an essential practice in the science classroom (NRC 2012). Taking this data and using it to craft an explanation that demonstrates understanding of content is another essential practice. But both practices can be challenging, and students often require teacher support to succeed. Accordingly, the…
Descriptors: Science Instruction, Teaching Methods, Secondary School Science, High Schools
Smith, Amy; Molinaro, Marco; Lee, Alisa; Guzman-Alvarez, Alberto – Science Teacher, 2014
For students to be successful in STEM, they need "statistical literacy," the ability to interpret, evaluate, and communicate statistical information (Gal 2002). The science and engineering practices dimension of the "Next Generation Science Standards" ("NGSS") highlights these skills, emphasizing the importance of…
Descriptors: STEM Education, Statistics, Statistical Analysis, Learning Modules
Leege, Lissa M.; Schriver, Martha; Chassereau, Karen D. – Science Teacher, 2008
The "Under the Mistletoe" project was developed to capitalize on student curiosity about the American Christmas Mistletoe plant and draw learners into an engaging, inquiry-based exercise that incorporates numerous life science standards and collaborative research. By collecting data on host and nonhost tree size, location, and number of mistletoe…
Descriptors: Inquiry, Science Instruction, Plants (Botany), Scientific Research
Peer reviewedCrump, Reva – Science Teacher, 1994
This activity uses ice crystals to introduce middle school and high school students to the collection, preparation, examination, and manipulation of scientific data. (PR)
Descriptors: Data Analysis, Data Collection, High Schools, Junior High Schools
Peer reviewedLilly, Sherril L. – Science Teacher, 1989
Describes a two-day forensic science course that is offered to eighth grade students enrolled in Science, Mathematics, and Technology Magnet Schools. Provides sample student activity sheets for the course. (Author/RT)
Descriptors: Chemistry, Data Analysis, Data Collection, Data Interpretation

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