The document discusses using data in the classroom. It provides examples of designing classroom activities using different types of data, including carbon dioxide levels, temperature and precipitation data, grain size data, and global climate model output. Example activities have students examine trends, compare rates of change, identify relationships, and consider the impact of climate change. The document emphasizes considering learning goals, available time, students' skills, and how student work will be assessed when designing data-based classroom activities.

1. Using data in the
classroom
Workshop facilitators:
Cindy Shellito
Kathy Surpless

2. Brainstorming
1. What does it mean to use data in the
classroom?
2. Why have students use data? What are
the learning goals for students?

3. Designing activities
 What is the learning goal?
 How much time do you have?
 What do your students already know and what are
your students comfortable with?
◦ Are they familiar with Excel, or other software?
◦ To what extent will you need to ‘package’ the data?
 Will students work in teams or individually?
 How will you frame your activity?
◦ Will students do the activity first, as an active introduction
to specific content?
◦ Will students complete the activity as a follow-up or building
on content?
 How will you assess your activity?

4. Example 1: Using CO2 data
 Many sources for CO2 data available
online:
◦ Mauna Loa observatory: daily, monthly, annual
data since 1958
◦ Globally averaged surface data since 1980
◦ Vostok ice core data (to 414,000 BP)
 Plot data at different time scales and for
different time periods
◦ Assess trends
◦ Compare rates and direction of change
◦ Make predictions based on trends
◦ Discuss size of datasets

5. Example 1: Using CO2 data

6. Example 2: Using temperature and
precipitation data
 Students work in groups to examine
tropical Pacific SST and precipitation data
over 10-yr time span. Used as intro to El
Niño in an intro-level meteorology course.
 Students learn to read lat-lon plots;
identify year to year changes; make
connections between SST and location of
precipitation.

7. Example 2: Using temperature and
precipitation data

8. Example 3: Using grain-size data
 Collect grain size data using sieves (for
disaggregated sample) and thin section
measurements
 Plot grain size data using Excel
 Calculate statistics to assess size range and
sorting
 Plot multiple samples to compare sizes and
sorting, assess size grading
◦ Think about how different data collection methods
impact interpretation of results
 Work with large dataset of grain size data
already collected

9. Example 2: Using grain-size data
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
-1.00 0.00 1.00 2.00 3.00 4.00 5.00 6.00
CumulativePercent
Grain size (phi)
95-DG-9
96-DG-23
96-DG-24
97-DG-53
95-DG-10
96-DG-26
97-DG-54
96-DG-27

10. Example 4: Using global climate
models
 Students examine global climate model
output available online and consider
impact of global warming on tropical
cyclone initiation and evolution.
 Available online at:
http://serc.carleton.edu/NAGTWorkshops/hurrican
es/activities/28268.html

11. Example 4: Using global climate
models
Sample climate
model output
available online at
the National
Center for
Atmospheric
Research

12. Your turn!
Take a moment to identify an activity or a
data set that you would like bring into one
of your classes.
1. What do you want your students to learn
from the activity?
2. What resources or tools might you need
to complete the activity?
3. How will you know what students have
learned from this activity?