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Duncan, Bruce; Fitzallen, Noleine – Australian Mathematics Teacher, 2013
The learning sequence described in this article was developed to provide students with a demonstration of the development of box plots from authentic data as an illustration of the advantages gained from using multiple forms of data representation. The sequence follows an authentic process that starts with a problem to which data representations…
Descriptors: Data Analysis, Data, Teaching Methods, Comparative Analysis
Sneider, Cary; Stephenson, Chris; Schafer, Bruce; Flick, Larry – Science Teacher, 2014
A "Framework for K-12 Science Education" identified eight practices as "essential elements of the K-12 science and engineering curriculum" (NRC 2012, p. 49). Most of the practices, such as Developing and Using Models, Planning and Carrying Out Investigations, and Analyzing and Interpreting Data, are well known among science…
Descriptors: High School Students, Secondary School Science, Thinking Skills, Computation
Kellie, Andrew C. – Engineering Design Graphics Journal, 2009
This paper discusses the character and challenges inherent in the graphical portrayal of features in subsurface mapping. Subsurface structures are, by their nature, hidden and must be mapped based on drilling and/or geophysical data. Efficient use of graphical techniques is central to effectively communicating the results of expensive exploration…
Descriptors: Data Interpretation, Earth Science, Geology, Models

Pearlman, Susan; Pericak-Spector, Kathleen – Science and Children, 1995
Advocates using graphs with young children to express relationships in a visual form. Describes how to teach children about graphs to encourage them to develop the ability to quantify data and the confidence to use this tool for science learning. (NB)
Descriptors: Data Interpretation, Early Childhood Education, Graphs, Mathematics
Roth, Wolff-Michael – International Journal of Computers for Mathematical Learning, 2003
Past research has shown that many scientists, when asked to interpret unfamiliar graphs that have nevertheless been culled from introductory undergraduate courses in their own field, experience problems and cannot give the standard answer accepted in the field. Yet, these same scientists turn out to be highly competent when it comes to graphs from…
Descriptors: Scientists, Laboratories, Graphs, Data Interpretation

Brown, Richard; Davis, Gretchen – Mathematics Teacher, 1990
Presents an activity considering whether a difference exists in the age of Oscar winners. Describes how to draw a stem plot and a box plot as an example of implementing the recommendations of the NCTM Standards. Provides tables showing the name, movie titles, and ages of the Oscar winners since 1928. (YP)
Descriptors: Data Analysis, Data Interpretation, Graphs, Mathematics
Maone, Teresa – Science Scope, 2004
Students at the middle school level are expected to use appropriate tools and techniques, including mathematics and graphing, to analyze and interpret data and communicate experimental findings. Measures of central tendency (mean, median, and mode--see sidebar for definitions) are often used as descriptive statistics when students conduct…
Descriptors: Statistical Analysis, Data Analysis, Science Education, Graphs

Davis, Gretchen – Mathematics Teacher, 1990
Describes classroom activities and shows that statistics is a practical tool for solving real problems. Presents a histogram, a stem plot, and a box plot to compare data involving class enrollments. (YP)
Descriptors: Data Analysis, Data Interpretation, Graphs, Mathematics
Ballenger, Cynthia; Rosebery, Ann S. – Teachers College Record, 2003
In this article we address questions raised by the research methods used in teacher research by exploring a particular approach to teacher research. This approach is based in teachers' concerns with underachieving children, particularly those who come from diverse cultural and linguistic backgrounds. It grows out of the work of the Brookline…
Descriptors: Educational Research, Research Methodology, Children, Underachievement

Barbella, Peter; And Others – Mathematics Teacher, 1990
Demonstrates a statistically valid method allowing students to explore randomization. Described are two examples: counting techniques for a small set of data and simulation for a large sample. (YP)
Descriptors: Data Analysis, Data Interpretation, Mathematical Concepts, Mathematical Logic