Estimating GPS Positional Error
This activity has benefited from input from faculty educators beyond the author through a review and suggestion process.
This review took place as a part of a faculty professional development workshop where groups of faculty reviewed each others' activities and offered feedback and ideas for improvements. To learn more about the process On the Cutting Edge uses for activity review, see http://serc.carleton.edu/NAGTWorkshops/review.html.
This activity was selected for the On the Cutting Edge Reviewed Teaching Collection
This activity has received positive reviews in a peer review process involving five review categories. The five categories included in the process are
- Scientific Accuracy
- Alignment of Learning Goals, Activities, and Assessments
- Pedagogic Effectiveness
- Robustness (usability and dependability of all components)
- Completeness of the ActivitySheet web page
For more information about the peer review process itself, please see http://serc.carleton.edu/NAGTWorkshops/review.html.
This page first made public: Jul 12, 2007
Designed for an introductory geology course
Skills and concepts that students must have mastered
How the activity is situated in the course
Content/concepts goals for this activity
Higher order thinking skills goals for this activity
Other skills goals for this activity
Description of the activity/assignment
After instructing students on basic receiver operation, each student will make many (10-20) position estimates of 3 benchmarks over a week. The different benchmarks will have different views of the skies or vegetation cover. Each student will download their data into a spreadsheet and calculate horizontal and vertical errors which are collated into a class spreadsheet. The positions are sorted by error and plotted in a cumulative frequency plot. The students are encouraged to discuss the distribution, sources of error, and estimate confidence intervals. This exercise gives the students a gut feeling for confidence intervals and the accuracy of data. Students are asked to compare results from different types of data and benchmarks with different views of the sky.Uses online and/or real-time data
Has minimal/no quantitative component <BR> Addresses student fear of quantitative aspect and/or inadequate quantitative skills
Addresses student misconceptions