Initial Publication Date: December 21, 2006
Evidence from science education research suggests that activities are most effective when they are designed to interactively engage students.
More on interactive engagement
More on interactive engagement
There are many ways to design activities that utilize data and also engage students as active participants in the learning process. We describe two basic activity design archetypes below:
- The analysis and interpretation of existing data from large science projects. Resources for using published data sets
- The collection and analysis of data by students in a microcomputer-based laboratory (MBL) environment. Learn more about Microcomputer Based Laboratories
- Having students use traditional measurement approaches (meter sticks, mass balances, pH meters, stop watches, etc.) to collect their own data can intimately connect them with their data. This approach is particularly useful when stressing measurement uncertainty and data quality.
- Student data collection networks, such as the GLOBE Project (more info) in which students not only collect their own data but also contribute and have access to a larger archive of student collected data.
It is important to stress that in all using data activities a discussion of the source and quality of data is an essential component of the learning process.
A working knowledge of fundamental statistics (mean, variance, standard error, confidence intervals, and linear regression) is important aspect of working with data.
Resources for Introductory Statistics.
Resources for Introductory Statistics.
Graphs are often used to help students visualize data. Having students make their own graphs, read data/information from graphs, and describe graphs in their own words are all important "Using Data" learning objectives.
More about teaching using graphs
More about teaching using graphs
