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Showing all 14 results Save | Export
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Schultheis, Elizabeth H.; Kjelvik, Melissa K. – American Biology Teacher, 2020
Authentic, "messy data" contain variability that comes from many sources, such as natural variation in nature, chance occurrences during research, and human error. It is this messiness that both deters potential users of authentic data and gives data the power to create unique learning opportunities that reveal the nature of science…
Descriptors: Data Analysis, Scientific Research, Science Instruction, Scientific Principles
Meltzoff, Julian; Cooper, Harris – APA Books, 2017
Could the research you read be fundamentally flawed? Could critical defects in methodology slip by you undetected? To become informed consumers of research, students need to thoughtfully evaluate the research they read rather than accept it without question. This second edition of a classic text gives students the tools they need to apply critical…
Descriptors: Critical Thinking, Research Methodology, Evaluative Thinking, Critical Reading
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Helens-Hart, Rose – Communication Teacher, 2015
Coming-out scenarios have been described as potentially traumatic events that change the parent-child relationship (MacDonald, 1983). Little research in the field of communication studies has been conducted on how the process of coming out unfolds within families (Valentine, Skelton, & Butler, 2003). The exercise described in this article…
Descriptors: Data Analysis, Parent Child Relationship, Data Interpretation, Learning Activities
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Gal, Ya'akov; Uzan, Oriel; Belford, Robert; Karabinos, Michael; Yaron, David – Journal of Chemical Education, 2015
A process for analyzing log files collected from open-ended learning environments is developed and tested on a virtual lab problem involving reaction stoichiometry. The process utilizes a set of visualization tools that, by grouping student actions in a hierarchical manner, helps experts make sense of the linear list of student actions recorded in…
Descriptors: Virtual Classrooms, Laboratory Experiments, Online Courses, Electronic Learning
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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
O'Connell, Susan R. – 1997
Glyphs, a way of representing data pictorially, are a new way for elementary students to collect, display, and interpret data. This book contains a number of glyph activities that can be used as creative educational tools for grades 1-3. Each glyph has three essential construction elements: the glyph survey (the questions that are asked), the…
Descriptors: Communication Skills, Data Analysis, Data Interpretation, Elementary Education
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Ward, Roger A.; Grasha, Anthony F. – Teaching of Psychology, 1986
Provides a classroom demonstration designed to test an astrological hypothesis and help teach introductory psychology students about research design and data interpretation. Illustrates differences between science and nonscience, the role of theory in developing and testing hypotheses, making comparisons among groups, probability and statistical…
Descriptors: College Instruction, Data Analysis, Data Interpretation, Higher Education
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Taylor, Judith V. – Teaching Children Mathematics, 1997
Presents activities having to do with data generation, organization, interpretation, representation, drawing conclusions, and making predictions on the basis of data which students have collected. (ASK)
Descriptors: Data Analysis, Data Collection, Data Interpretation, Elementary Education
Curcio, Frances R. – 1989
This book provides elementary and middle school teachers with practical ideas on the use and teaching of graphs. Five sections consist of: (1) "Graphs--What Are They and How Are They Used?"; (2) "Levels of Graph Comprehension"; (3) "Collecting, Organizing, and Analyzing Data"; (4) "Constructing, Interpreting, and Writing about Graphs"; and (5)…
Descriptors: Comprehension, Data Analysis, Data Interpretation, Elementary Education
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Hitch, Chris; Armstrong, Georganna – Arithmetic Teacher, 1994
Presents four sets of activities to develop the concepts of data analysis and graphing. Students estimate sample populations using beans, examine graphs from newspapers and magazines, predict the most popular color of cars, and simulate quality control in a manufacturing process. (MDH)
Descriptors: Concept Formation, Data Analysis, Data Collection, Data Interpretation
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Lilly, 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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Young, Sharon L. – Arithmetic Teacher, 1991
Presents a series of activities using data collection and interpretation techniques designed for levels 1-8, 1-5, 3-6, and 4-8 that integrate mathematics and social studies through the common theme of television viewing. Includes an activity sheet for parents to use with their children, three class-activity sheets, and a data sheet. (MDH)
Descriptors: Data Analysis, Data Collection, Data Interpretation, Elementary Education
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Stevens, Jill – Mathematics Teacher, 1993
Presents activities in which students develop and analyze scatterplots on graphing calculators to model corn growth, decay, a box of maximum volume, and weather prediction. Provides reproducible worksheets. (MDH)
Descriptors: Cooperative Learning, Data Analysis, Data Interpretation, Functions (Mathematics)
Trace, Michael W. – 1982
This learning module, which is intended for use in in-service training for vocational rehabilitation counselors, reviews the systematic methods available to measure and record client behavior. The first section covers procedures for making necessary calculations and keeping needed records with respect to behavioral events and their duration and…
Descriptors: Behavior Change, Behavioral Objectives, Charts, Classroom Observation Techniques