QuarkNet Data Portfolio

A collection of proven instructional activities developed around data strands that help students develop an understanding about how scientists make discoveries. 
The Data Portfolio organizes activities by data strand and level of student engagement. Activities differ in complexity and sophistication—tasks in Level 1 are simpler than those in Levels 2 and 3. While each level can be explored individually, students that start in one level and progress to more complex levels experience increasingly engaging and challenging tasks. Teachers select activities to offer a learning experience of an appropriate length and level for their students.

A collection of proven instructional activities developed around data strands that help students develop an understanding about how scientists make discoveries.

The Data Portfolio organizes activities by data strand and level of student engagement. Activities differ in complexity and sophistication—tasks in Level 1 are simpler than those in Levels 2 and 3. While each level can be explored individually, students that start in one level and progress to more complex levels experience increasingly engaging and challenging tasks. Teachers select activities to offer a learning experience of an appropriate length and level for their students.

Activity Name Data Strand Level Curriculum Topics NGSS Practices Topic
Signal and Noise: Cosmic Muons

In this introductory tutorial that, students learn about how to distinguish muon signals from background and instrumental noise.

Signal and Noise: The Basics

Students analyze signals and noise first in audio and video forms and then look at signals and noise from physics measurements.

The Case of the Hidden Neutrino

Students use momentum conservation to examine the decay of top-antitop pairs to determine what is missing from the event.

TOTEM Data Express

Use quantum physics and LHC data to estimate the size of the proton.

What Heisenberg Knew

Heisenberg knew that, at the quantum level, we cannot know everything, at least not all at once. Students explore uncertainties in measurements of complimentary variables to find this out for themselves.