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Tebeck, Claudette – Science Teacher, 2021
School closures in the wake of the COVID-19 pandemic led to kids asking pertinent questions about why they were not in school, especially some students suffering financial hardship. Virtual classrooms became the mundane venues for students to piece together the pandemic puzzle and unpack unseen inequities. This article examines disparities that…
Descriptors: COVID-19, Pandemics, Racial Differences, Science Instruction
Hammett, Amy; Dorsey, Chad – Science Teacher, 2020
To learn with data, students need "data" to explore. This can be deceptive--data-rich experiences typically involve much more than a straightforward science lab. Solving real problems with data means identifying authentic questions that are meaningful to students and provide a foundation for deep inquiry. Such situations often lend…
Descriptors: Data Analysis, Problem Solving, Student Projects, Active Learning
Reed, Megan H.; Jenkins, Tom; Kenyon, Lisa – Science Teacher, 2019
Nitrogen- or phosphorus-based fertilizers, used in agriculture, can run off into nearby waterways during periods of heavy rain or high flow and cause harmful blooms (Paerl et al. 2016), low oxygen (Joyce 2000), and decreased biodiversity (Sebens 1994). Studies of the effects wetlands can have on water and habitat quality (Verhoeven and Meuleman…
Descriptors: Natural Resources, Biodiversity, Grade 9, Ecology
Finzer, William; Busey, Amy; Kochevar, Randy – Science Teacher, 2018
Data-driven inquiry as a science practice and instructional approach can provide a powerful context for project-based learning (PBL). Students engage in data-driven inquiry when they explore a rich data set and observe patterns, ask questions suggested by the data, and pursue answers about underlying phenomena. Krajcik (2015) describes five…
Descriptors: Science Instruction, Teaching Methods, Data Analysis, Maps
Clary, Renee; Wandersee, James – Science Teacher, 2014
Renee Clary and James Wandersee implemented the Stratigraphy and Data Interpretation Project described in this article when they recognized that some students were having difficulties constructing appropriate graphics and interpreting their constructed graphics for an earlier mathematics-science project in their classrooms. They also previously…
Descriptors: Science Instruction, Graphs, Data Analysis, Freehand Drawing
Webber, Hannah; Nelson, Sarah J.; Weatherbee, Ryan; Zoellick, Bill; Schauffler, Molly – Science Teacher, 2014
Data literacy is complex. When students investigate the natural world, they must be able to gather data, organize it in tables and spreadsheets, analyze it in context, and describe and interpret it--usually as evidence to support a scientific argument. These skills are echoed in the science and engineering practices of the "Next Generation…
Descriptors: Science Instruction, Graphs, Science Process Skills, Data 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
Waugh, Michael – Science Teacher, 2007
The purpose of this article is to describe a simple laboratory activity in which students collect a series of measurements and then use graphical analysis to determine the nature of the relationship between an object's mass and the volume of water it displaces. In this activity, students explore the relationships between the mass of a floating…
Descriptors: Scientific Concepts, Models, Science Activities, Science Laboratories

Forkey, Carole – Science Teacher, 1996
Presents the "Before Technology and After Technology" lab where students first complete a simple lab and graph the data by hand and then repeat the lab using graphing calculators. Enables students to see how technology can make data collecting, graphing, and analyzing more fun. (JRH)
Descriptors: Data Analysis, Data Collection, Graphing Calculators, Graphs

Michael, Valerie – Science Teacher, 1989
Discusses a graphical analysis method used in the physics laboratory. Shown are various kinds of graphs to illustrate the relationship between two variables. A procedure for deriving equations from laboratory data is described. (YP)
Descriptors: Data Analysis, Data Interpretation, Equations (Mathematics), Graphs

Palmer, Alfred C. – Science Teacher, 1986
Describes an activity for determining how long and when a tree lived by comparing its ring sizes with local precipitation records. Suggests benefits for this type of dendrochronology activity. (TW)
Descriptors: Climate, Data Analysis, Data Collection, Data Interpretation