Objective: 

Students will collect word length data from two different texts, calculate measures of center and variability, and use these statistics to make informal comparative inferences about the two populations.

Materials Needed:

• Two science textbooks (one for 4th grade, one for 6th grade)

• Highlighters and sticky notes

• Chart paper and markers for data visualization

Steps:

• Introduction: 

  • Start by asking students, “Do you think words in a seventh-grade book are longer than those in a fourth-grade book?” 

  • Explain that they will collect data on word lengths from two different texts and analyze this data using measures of center and variability.

• Group Activity: 

  • Students will work in small groups, choosing a 100-word sample from each text. 

  • They will highlight each word, count the number of letters, and record the word lengths on sticky notes.

• Calculating Measures: 

  • Once data is collected, students will calculate the mean, median, range, and interquartile range for each text’s word lengths. 

  • They will then organize the data into a visual chart on chart paper.

• Making Inferences: 

  • After calculating measures of center and variability, students will compare the two populations (words in each text) and draw informal inferences. 

  • For example, they might conclude that longer words are more common in the seventh-grade text based on their data.

• Presentation and Discussion: 

  • Each group will present their findings to the class, explaining the patterns they observed and how they used statistical measures to compare word lengths.

Equity and Access: 

Provide pre-sorted texts with highlighted words for students needing extra support. Pair students with varied abilities to ensure collaborative learning and ensure everyone can participate in the data collection and analysis process.

Real-World Application: 

Relate this to how linguists and educators analyze readability levels of textbooks or how search engines rank the complexity of web pages by analyzing word lengths.

CS Practice(s):

• Recognizing and Defining Computational Problems: Students identify patterns in word lengths and break down the problem by calculating statistical measures.

• Communicating About Computing: Students use the data they collected to present and explain their findings about word length variations.

Standard(s):

• CA CCSS for Mathematics 6.SP.5.c

• CA CS 6-8.DA.8

Objective: 

Students will use a temperature sensor to collect real-world data and use computational tools (spreadsheet software) to calculate measures of center and variability. They will transform and visualize the data to make inferences about temperature patterns in different areas of their school.

Materials Needed:

• Tablets or computers

• Temperature sensors and a connected app

Steps:

• Introduction: 

  • Begin by asking, “Do you think some parts of the school are warmer than others during the day? Why might that happen?” 

  • Explain that students will use a sensor to measure temperatures in different areas and use the data to investigate variability.

• Group Activity: 

  • In pairs, students will use a temperature sensor to collect data from different areas of the school (e.g., hallways, classrooms, and the cafeteria) at multiple times of the day. 

  • They will input the data into a spreadsheet and organize it into columns.

• Calculating Measures:

  • Once data is collected, students will use spreadsheet formulas to calculate the mean, median, range, and interquartile range for temperatures at each location and time. 

  • They will also create graphs (bar graphs, line graphs) to visually represent the temperature variations.

• Making Inferences: 

  • Based on the data, students will make informal inferences about which areas of the school are consistently warmer or cooler and why. 

  • For example, they may conclude that rooms with more sunlight tend to have higher temperatures in the afternoon.

• Presentation and Discussion: 

  • Each group will present their data and graphs, explaining the temperature patterns they observed and how they used computational tools to make sense of the sensor data.

Equity and Access: 

Provide pre-set temperature sensors with simplified instructions for students who may need additional support in collecting data. Pair students with different levels of experience in using technology to foster collaboration.

Real-World Application: 

Discuss how building engineers use sensors to monitor temperature variations in different areas of a building, optimizing energy usage or improving comfort.

CS Practice(s):

• Creating Computational Artifacts: Students collect temperature data using sensors and input it into a computational tool to calculate and visualize the results.

• Testing and Refining Computational Artifacts: Students refine their graphs and data visualizations based on peer feedback to ensure clarity and accuracy.

Standard(s):

• CA CCSS for Mathematics 6.SP.5.c

• CA CS 6-8.DA.8