DataClassroom is best used in classes where students want to quickly and easily analyze data that they've collected themselves. After uploading the data, kids will be asked to estimate the mean, but then with a click of a button, the computer does the actual calculating for them. Many students can use an equation to calculate the standard deviation without actually understanding what it means. DataClassroom helps students visualize this concept by dragging the shaded bars to cover two-thirds of the data -- but, once again, the actual calculations are done by the computer.
With a click of a button, a box and whisker plot or a "means with error" plot can appear. Students are provided with the definition of these items but aren't asked to set these up themselves or internalize what these mean. The chi-square analysis functions similarly; students must determine the expected values and the degrees of freedom themselves with some text that coaches them along the way. But the rest of the chi-square calculations are done for them. Additionally, the p-value is determined for them, instead of allowing students to interpret the graph and do the analysis themselves.Continue reading Show less
DataClassroom helps teachers store, manipulate, and analyze data sets. Teachers can set up classes so that students can share data sets; this also allows teachers to track individual progress as their students upload and save data. DataClassroom can easily import class rosters right from Google Classroom.
Sample data sets are provided to help students practice using statistical tools. Kids can use an existing data set to explore research questions like "Is beak depth (mm) different between birds that died and those that lived through the drought of 1977?" This data set coordinates with free supplementary materials from HHMI BioInteractive.
DataClassroom's biggest strength is the way it models for students how to analyze and interpret data. Kids are walked step by step through a t-test, visualizing mean and standard deviation along the way. Students then use their t-score, sample size, and p-value to form a conclusion to their research question. After they're done using the statistical analysis to form a conclusion, all of their statistics and notes are combined into an editable Word document.
While DataClassroom helps students visualize what the t-test and chi-square analysis can tell us about data, it doesn't require students to do any of the actual calculations. Not only does it calculate the p-value for the students, but it also tells the students what a particular p-value means in the context of their data set -- for example, directly telling the students that the two groups of birds are statistically different. This takes some of the analysis away from kids. However, this modeling can be useful when students go on to analyze their own data sets. Students can also use the existing data sets to make a graph themselves. While the t-test and chi-square analysis tools provide excessive amounts of coaching, students will need more support than is provided when using DataClassroom to build graphs.
Key Standards Supported
Interpreting Categorical And Quantitative Data
Represent data with plots on the real number line (dot plots, histograms, and box plots).
Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets.
Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).
Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages. Recognize that there are data sets for which such a procedure is not appropriate. Use calculators, spreadsheets, and tables to estimate areas under the normal curve.
Statistics And Probability
Recognize that a measure of center for a numerical data set summarizes all of its values with a single number, while a measure of variation describes how its values vary with a single number.
Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line.
Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a two-way table. Construct and interpret a two-way table summarizing data on two categorical variables collected from the same subjects. Use relative frequencies calculated for rows or columns to describe possible association between the two variables. For example, collect data from students in your class on whether or not they have a curfew on school nights and whether or not they have assigned chores at home. Is there evidence that those who have a curfew also tend to have chores?
Key Standards Supported
Biological Evolution: Unity and Diversity
Apply concepts of statistics and probability to support explanations that organisms with an advantageous heritable trait tend to increase in proportion to organisms lacking this trait.
Create or revise a simulation to test a solution to mitigate adverse impacts of human activity on biodiversity.
Earth and Human Activity
Use a model to represent the relationship between the needs of different plants or animals (including humans) and the places they live.
Ask questions to obtain information about the purpose of weather forecasting to prepare for, and respond to, severe weather.
Communicate solutions that will reduce the impact of humans on the land, water, air, and/or other living things in the local environment.
Make a claim about the merit of a design solution that reduces the impacts of a weather-related hazard.
Obtain and combine information to describe that energy and fuels are derived from natural resources and their uses affect the environment.
Generate and compare multiple solutions to reduce the impacts of natural Earth processes on humans.
Obtain and combine information about ways individual communities use science ideas to protect the Earth’s resources and environment.
Construct a scientific explanation based on evidence for how the uneven distributions of Earth’s mineral, energy, and groundwater resources are the result of past and current geoscience processes.
Analyze and interpret data on natural hazards to forecast future catastrophic events and inform the development of technologies to mitigate their effects.
Apply scientific principles to design a method for monitoring and minimizing a human impact on the environment.
Construct an argument supported by evidence for how increases in human population and per-capita consumption of natural resources impact Earth’s systems.
Ask questions to clarify evidence of the factors that have caused the rise in global temperatures over the past century.
Construct an explanation based on evidence for how the availability of natural resources, occurrence of natural hazards, and changes in climate have influenced human activity.
Evaluate competing design solutions for developing, managing, and utilizing energy and mineral resources based on cost-benefit ratios.
Create a computational simulation to illustrate the relationships among management of natural resources, the sustainability of human populations, and biodiversity.
Evaluate or refine a technological solution that reduces impacts of human activities on natural systems.
Analyze geoscience data and the results from global climate models to make an evidence-based forecast of the current rate of global or regional climate change and associated future impacts to Earth systems.
Use a computational representation to illustrate the relationships among Earth systems and how those relationships are being modified due to human activity.
Ecosystems: Interactions, Energy, and Dynamics
Use mathematical representations to support and revise explanations based on evidence about factors affecting biodiversity and populations in ecosystems of different scales.
Heredity: Inheritance and Variation of Traits
Apply concepts of statistics and probability to explain the variation and distribution of expressed traits in a population.