Students investigate how different controlled growing systems affect radish growth by designing and building a mica-radish farm with setups such as soil, hydroponic, or wick-based systems, then comparing which conditions produce the strongest results. They use digital tools to collect, organize, break down, analyze, and present data through spreadsheets, statistics, and visual displays, and apply algorithmic thinking to create simple automated monitoring or testing routines that support problem-solving and decision-making. With support from OSU Extension, students connect plant biology, chemistry, environmental science, and data analysis to the question, How do different controlled environments change radish growth, and which data tells us the most about success? Through critique, revision, reflection on what was good, bad, missing, or confusing, and a public exhibition for community members, staff, Master Gardeners, FFA, and families, students show how their findings could inform local farming decisions and future growth trials.

Students will design and build a mica-radish farm with multiple controlled growing trials, then use digital tools to collect, organize, and analyze data on variables such as light, water delivery, temperature, nutrients, and plant growth to answer which conditions lead to the most successful radish production. They will apply statistics, chemistry, environmental science, plant biology, data collection, data analysis, and spreadsheet creation to identify key information, interpret patterns, and make evidence-based decisions that could inform local farming practices. Students will use algorithmic thinking and technology-assisted tools such as timers, sensors, and spreadsheet formulas to create simple automated systems, test solutions, revise their setups through peer critique and teacher feedback, and prepare data for presentation. They will also strengthen collaboration, self-direction, reflection, and effective communication by sharing team roles, responding to peer reviews and a mock exhibition, and presenting radish samples, graphs, and community impact statements to community members, staff, Master Gardeners, FFA, families, and OSU Extension partners.

Students will create a mica-radish farm in teams, along with digital data collection tools, spreadsheets, and simple automated monitoring or testing systems using sensors, timers, or microcontrollers. Throughout the project, they will produce kickoff video messages, weekly growth logs, photo documentation, data dashboards, comparison charts, peer review notes, mock exhibition materials, and reflection updates that address what was good, bad, missing, confusing, and the possible impact on farming communities and beyond. Teams will also develop a tested decision-making model or simple algorithm that uses collected data to compare controlled environments and identify which measurements best show success. By the end, they will present radish samples, cleaned datasets, graphs, community impact statements, and a final research poster or slide deck for community members, staff, Master Gardeners, FFA, families, and OSU Extension partners.

Launch the project with a Controlled Environment Challenge in which small groups rotate through radishes grown in soil, hydroponic, wick-based, and the mica-radish farm setup, taste and inspect samples, and record a kickoff video explaining what success in radish growth might look like for local farmers. Students use digital tools to photograph evidence, collect baseline data on light, moisture, temperature, pH, and plant size, and organize it in shared spreadsheets so they can begin comparing which variables and data points matter most. Invite an OSU Extension agent to co-launch the investigation by helping teams compare controlled-environment variables, pose questions about community farming impact, and preview how data analysis and automated testing systems can guide decisions. Close with teams drafting initial testable claims, assigning collaboration roles, and completing a quick reflection on what was good, what was bad, what was missing, and what was confusing.

Host a community showcase where teams present their mica-radish farm, radish samples, spreadsheets, graphs, and digital dashboards to community members, staff, Master Gardeners, FFA, families, and OSU Extension partners. Students should explain their controlled-environment trials, how they used digital tools to collect and break down data, and any simple automated system they built to test solutions, then share community impact statements about how their findings could inform local farming decisions and future growth trials. Include a midterm mock exhibition and use feedback from two peer reviews, OSU Extension conversations, and final teacher review to strengthen displays and presentations before the final event. Add a reflection component in which teams answer: What was good, what was bad, what was missing, what was confusing, and what impact can this have on the farming community and beyond?