Objective:

Students will sort and classify objects based on properties such as hardness, texture, and weight. They will use computational thinking to recognize patterns, analyze data, and make predictions about the properties of new objects, creating visual representations such as bar graphs and Venn diagrams to support their findings.

Materials Needed:

• A variety of classroom objects with different properties (e.g., smooth rocks, cotton balls, marbles, paper)

• Chart paper and markers

• Sticky notes for labeling objects

Steps:

• Introduction:

  • Begin by asking, "How do we describe different objects around us?" 

  • Engage students in a discussion about object properties such as hardness, smoothness, and weight. 

  • Show examples of objects and ask students to describe their properties.

• Group Activity:

  • Divide students into small groups and provide each group with several objects. 

  • Ask them to classify the objects into different categories based on their properties, such as hard/soft or heavy/light. 

  • Encourage students to explore relationships between the categories (e.g., are objects that are soft also light?). They will record their findings on a chart.

• Analyzing Data:

  • Each group will create a bar graph or a Venn diagram to visually represent their classifications. 

  • Afterward, they will share their findings with the class, pointing out any patterns they observed (e.g., "Most objects that are hard are also smooth").

• Making Predictions:

  • Show students pictures of new objects (e.g., a feather, a metal spoon). 

  • Have them predict the properties of these objects based on what they learned from their classification activity.

• Reflection:

  • After predicting the properties of new objects, students reflect on how their classifications can help them understand the world, reinforcing the concept of pattern recognition and data analysis as key components of computational thinking.

Equity and Access:

Provide pre-classified objects for students who may need additional support and encourage peer collaboration to ensure all students are engaged in the activity.

Real-World Application:

Relate the lesson to everyday scenarios where sorting and classifying objects is important, such as recycling (sorting materials like plastic and glass) or organizing items at home based on their properties.

CS Practice(s):

• Recognizing and Defining Computational Problems: Students identify object properties and use them to categorize and classify the objects.

• Communicating About Computing: Students share their observations and explain the patterns they identified during classification.

Standard(s):

• CA NGSS 2-PS1

• CA NGSS 2-PS1-2

• CA CS K-2.DA.9

Objective:

Students will use a tablet or computer to input data about object properties and create digital graphs to analyze the relationships between the properties (e.g., hardness and texture). They will also make predictions about new objects based on the collected data.

Materials Needed:

• Tablets or computers with a spreadsheet application (e.g., Google Sheets, Microsoft Excel)

• A collection of classroom objects with various properties

• Pictures of additional objects for prediction activities

Steps:

• Introduction:

  • Discuss with students how computers can help us collect, store, and analyze data. 

  • Show them how to use a spreadsheet to input data about the properties of objects and introduce the concept of visualizing data through graphs.

• Group Activity:

  • In pairs, students will input their observations about a set of objects (e.g., rock, cotton ball, eraser) into a spreadsheet. 

  • They will classify each object by properties such as hardness, texture, and weight. 

  • Once the data is entered, they will generate a bar graph or pie chart to represent their findings.

• Analyzing Data:

  • Guide students in looking for relationships between object properties. 

  • For example, they might observe that most hard objects are also smooth, while soft objects tend to be fluffy. 

  • Students will then explain their findings in small groups, using their digital graphs to support their observations.

• Making Predictions:

  • Show images of new objects and ask students to predict their properties based on the patterns they’ve identified. 

  • Students can input these predictions into their spreadsheets to compare later.

Equity and Access:

Provide templates with pre-entered data for students who need extra assistance. Encourage collaboration by pairing students with different levels of experience with technology.

Real-World Application:

Connect the lesson to real-world situations, such as using data charts to compare product features when shopping or organizing items by properties at home.

CS Practice(s):

• Creating Computational Artifacts: Students create digital graphs to represent the relationships between object properties.

• Testing and Refining Computational Artifacts: Students review and modify their charts as they test their predictions and refine their understanding of object properties.

Standard(s):

• CA NGSS 2-PS1

• CA NGSS 2-PS1-2

• CA CS K-2.DA.9