Introduction to the Data Science Process

In Step 1 of the data science process, students ask questions. The questions are directly related to factors that impact the stability of a rocket as it travels through Earth’s atmosphere. Then narrow the focus to a single question that can be answered by investigating data.

Age: 11-15 years old

Length: 60 minutes

Lesson highlights:

• Brainstorm questions about factors that could impact rocket launch stability.
• Categorize visual, qualitative, and quantitative data related to a stable rocket launch.
• Develop a question that focuses on a specific data set.
• Determine what data is needed to answer the focus question.

Learning standards:

• NGSS MS-ESS1-3. Analyze and interpret data to determine similarities and differences in findings.
• ISTE 5b. Students collect data or identify relevant data sets, use digital tools to analyze them, and represent data in various ways to facilitate problem-solving and decision-making.
• CSTA 2-DA-09 Collect data using computational tools and transform the data to make it more useful and reliable.

Organizing data is the next step in the data science process. Collected sets of data can be extremely large. In the role as a data scientist, you must make the data manageable by using the power of digital tools to better understand the impact of wind on our rocket launch.

Age: 11-15 years old

Length: 60 minutes

Lesson highlights:

• Type, copy, and paste data in Excel cells
• Read sensor data, and manipulate columns of data
• Organize data into a structured table
• Calculate data with formulas in a table

Learning standards:

• NGSS MS-ESS1-3. Analyze and interpret data to determine similarities and differences in findings.
• ISTE 5b. Students collect data or identify relevant data sets, use digital tools to analyze them, and represent data in various ways to facilitate problem-solving and decision-making.
• CSTA 2-DA-09 Collect data using computational tools and transform the data to make it more useful and reliable.

Step 3 in this data science process is the creation of visual interpretations of our data, such as charts and graphs. They allow data scientists to see the data in ways that numbers and text just can’t provide. The task is to use our organized data from Step 2 and create a chart showing our maximum allowable wind speeds at different elevations.

Age: 11-15 years old

Length: 60 minutes

Lesson highlights:

• Visualize data with column and scatter charts
• Use the Analyze Data feature and learn how to move and resize chart
• Locate different charts from the Insert menu
• Edit titles and labels in a chart

Learning standards:

• NGSS MS-ESS1-3. Analyze and interpret data to determine similarities and differences in findings.
• ISTE 5b. Students collect data or identify relevant data sets, use digital tools to analyze them, and represent data in various ways to facilitate problem-solving and decision-making.
• CSTA 2-DA-09 Collect data using computational tools and transform the data to make it more useful and reliable.

In Step 4 of the data science process, your team interprets the visualized data from Step 3 to make a Go/No-Go determination for a rocket launch. The team reports their findings in a brief report to flight control.

Age: 11-15 years old

Length: 60 minutes

Lesson highlights:

• Learn about visualizing with two types of charts
• Examine a wind speed data chart from a weather balloon
• Use the data available to determine whether the rocket flight is a Go/No-Go for launch

Learning standards:

• NGSS MS-ESS1-3. Analyze and interpret data to determine similarities and differences in findings.
• ISTE 5b. Students collect data or identify relevant data sets, use digital tools to analyze them, and represent data in various ways to facilitate problem-solving and decision-making.
• CSTA 2-DA-09 Collect data using computational tools and transform the data to make it more useful and reliable.

Relevance. Data Science is one of the fastest growing professions, according to the Bureau of Labor Statistics. Every industry needs data analytics – including business in all sectors, healthcare, education, and every form of social programming. Inspiring the advancement of NextGen’s data analytics skills is to stimulate reasoning, discourse, and decision-making, ultimately creating a smarter world for us all.

Equity for All. Multimodal, dynamic, scaffolded instructions support learners at multiple readiness levels and from diverse backgrounds.

Accessibility. Designed to open doors to student participation in the data science revolution, these lessons are supported on any internet-enabled device. Use a larger screen (laptop or desktop) for the best experience.

Aligned to Standards. All activities are aligned to key Next Generation Science Standards (NGSS), International Society for Technology in Education (ISTE) standards, and Computer Science Teacher Association Standards (CSTA) standards.

Use the Excel workbook in Microsoft Teams Create an assignment (Introduction to the Data Science Process) in Microsoft Teams for Education and assign the Excel workbook to individual or small groups of students in a class. Groups turn in one copy of the assignment that can be graded separately or together.