Objective:

Students will collect, organize, and analyze data on environmental factors influencing plant growth and use computational thinking to develop a systematic process for understanding how different conditions impact plants.

Materials Needed:

• Classroom plants or seedlings in different environments (e.g., varying light, temperature, or water conditions)

• Journals or data recording sheets for tracking environmental factors and plant growth

• Paper for creating flowcharts

Steps:

• Introduction: 

  • Discuss how environmental factors like light, temperature, and water affect plant growth. 

  • Ask, "How might we systematically track these factors and their impact on plant health?" 

  • Introduce the idea of using data collection and analysis as a way to understand these relationships.

• Group Activity – Collecting Data: 

  • In small groups, students observe classroom plants placed under different environmental conditions (e.g., one in direct sunlight, another in shade). 

  • They measure and record daily data manually, such as how many hours of sunlight each plant gets, the estimated room temperature, and the amount of water given to each plant. 

  • Each group is responsible for ensuring accurate data collection over a week.

• Creating Flowcharts and Pseudocode: 

  • After collecting data, students will create flowcharts and write pseudocode to model how they would program a system to collect and analyze the same data using sensors. For example, a flowchart might include steps like “Measure sunlight hours” followed by “Compare plant growth to light exposure." Their pseudocode will outline simple instructions for processing the data and making comparisons between environmental factors and plant growth.

• Analysis and Discussion: 

  • Using their recorded data, students will analyze how different environmental factors (e.g., more sunlight vs. less sunlight) influenced the growth of their plants. 

  • They will then discuss how they could use technology, such as sensors or software, to automate this data collection and analysis process in a real-world setting.

• Presentation and Reflection: 

  • Each group will present their findings and explain how they organized their data, created their flowcharts, and wrote pseudocode. They will discuss the challenges of manual data collection and the benefits of using computational systems to automate the process.

Equity and Access:

Provide structured templates for flowcharts and pseudocode for students who need extra support. Encourage collaboration by pairing students with varying abilities to ensure everyone contributes to data collection and analysis.

Real-World Application:

Connect the lesson to real-world agricultural technology, where sensors and data collection systems help farmers optimize growing conditions for crops, leading to more efficient and sustainable farming practices.

CS Practice(s):

• Collaborating around Computing: Students work in small groups to collect, organize, and analyze environmental data related to plant growth, fostering peer collaboration and teamwork.

• Recognizing and Defining Computational Problems: Students identify key environmental factors influencing plant growth and break down the data collection process into manageable steps.

• Developing and Using Abstractions: Through pseudocode and flowcharts, students model a process for data collection and analysis, creating abstractions for real-world problems.

• Communicating about Computing: Students present their flowcharts and pseudocode to peers, explaining how they structured their data collection and analysis systems.

Standard(s):

• CA NGSS MS-LS1-5

• CA CS 6-8.AP.10

Objective:

Students will use physical computing (sensors) to collect data on environmental factors influencing plant growth and analyze the relationship between environmental and genetic factors in growth.

Materials Needed:

• Arduino, Micro:Bit or other kits with sensors (light, temperature, soil moisture)

• Laptops with Arduino IDE or similar software

• Plant growth setups for experiments

Steps:

• Introduction: 

  • Discuss the importance of environmental and genetic factors in plant growth. 

  • Introduce how sensors can be used to measure and track environmental conditions over time.

• Group Activity: 

  • Students set up sensors to monitor plant growth in different conditions. 

  • They collect data on light, temperature, and soil moisture, creating a dataset over several days.

• Data Analysis: 

  • Using computational tools, students visualize the data through charts and graphs, comparing how different conditions affect plant growth.

• Presentation and Discussion: 

  • Groups present their findings, comparing the environmental and genetic factors influencing growth and discussing how data representation supports their conclusions.

Equity and Access:

Offer pre-built sensor kits or simplified setups for students with limited experience. Encourage collaboration between students of different skill levels to ensure peer support.

Real-World Application:

Discuss the role of sensors in agriculture, such as precision farming, where data is used to optimize conditions for crop growth, leading to more efficient and sustainable farming practices.

CS Practice(s):

• Fostering an Inclusive Computing Culture: Students ensure that all group members have opportunities to engage with the technology, promoting a collaborative and inclusive environment.

• Creating Computational Artifacts: Students use physical computing tools (such as sensors) to collect data on plant growth and environmental conditions, creating a computational artifact that captures the data in real time.

• Testing and Refining Computational Artifacts: Students refine their data collection systems, testing how well the sensors track environmental factors and adjusting their code for accuracy.

• Communicating about Computing: After collecting and analyzing the data, students present their findings and the role of their computational tools to the class.

Standard(s):

• CA NGSS MS-LS1-5

• CA CS 6-8.DA.8