FarmBeats for Students curriculum overview

FarmBeats for Students is a hands-on STEM program designed to introduce students to the concepts of precision agriculture.

Program components

There are three program components in FarmBeats for Students that provide rich learning opportunities for students.

Curriculum

The FarmBeats for Students curriculum is free and downloadable from the Microsoft Learn Educator Center: www.aka.ms/FBFS. The curriculum includes teacher resources (containing a teacher guide which has a 20-day instructional sequence, teacher background knowledge, and detailed lesson plans), PowerPoint presentations, student activities, and additional support videos.

FarmBeats for Students consists of three curriculum units, known as sections. Each section provides students with direct hands-on learning experiences in precision agriculture. All of the curriculum is free to download as a zip file containing all necessary materials for that specific section.

• Section 1: Gathering Data through Sensors (suitable for grades 6+/ages 11+) - Students gather data through sensors. They assemble a plant monitoring kit, consisting of a micro:bit equipped with sensors. The kit enables them to gather data about their plants and view it live in Microsoft MakeCode. Then, using Microsoft Excel, they see firsthand how data yields deeper insights.
• Section 2: Analyzing Big Data (suitable for grades 9+/ages 14+) - Students are introduced to data visualization tools in Excel. They engage with big data sets to extract intelligence and make decisions about the best locations for a greenhouse.
• Section 3: Unlocking Data Insights with AI (suitable for grades 9+/ages 14+) - Students explore AI by building their own machine learning models, which help detect nutrient imbalances in their plants and identify pests in their garden. The section also introduces Microsoft’s Responsible AI principles and presents discussions around some of the challenges raised by AI.

This video provides a step-by-step tutorial on how to access the curriculum resources available for FarmBeats for Students.

Hardware

The FarmBeats for Students program utilizes physical hardware. The necessary hardware kit includes a micro:bit. There are different options available for purchase: the Starter Kit, the Students Club Pack, and the Students Classroom Pack. You can purchase according to how many individuals participate in FarmBeats for Students.

Software

Within the curriculum, there are two sections that require the use of software. Section 1, Gathering Data through Sensors, utilizes Microsoft MakeCode, a free platform that runs on any device with a web browser. Make sure you have access to MakeCode on whatever devices students use.

Section 3, Unlocking Insights with Machine Learning and AI, uses a free, web-based program called GenAI Teachable Machine. There are two activities that use the GenAI Teachable Machine application. Work with GenAI Teachable Machine before introducing it to your students. It can be used in a web browser or saved locally.

Program connections

AI is the ability of a computer or other machine to perform activities normally thought to require intelligence. AI technologies are increasingly close to human intelligence and to how we sense and experience the world around us.

AI is now almost everywhere-it's important to understand what it is, how it works, and how it's being utilized in everyday life.

The FarmBeats for Students curriculum is built around the Five Big Ideas in AI, which are fundamental to understanding AI and its importance in agriculture.

Big Idea One is Perception, which has to do with how computers get to know their environment, for example soil, air, and water.

Once our machines are connected to the land, they need the ability to reason and interact with it, as explored in Big Idea Two: Representation and Reasoning. In this curriculum, we built a system that tests soil moisture levels and alerts us when irrigation is needed, demonstrating how machines develop a representational understanding of the environment to make informed decisions.

Big Idea Three is about Learning—teaching computers how to learn. Machine Learning is a core concept in the curriculum and in AI in general. This is how we teach machines to do amazing things like seeing, hearing, and reading. When we use a streaming video service, machines can learn about our viewing preferences and use that information to recommend what we might want to see next. In agriculture, AI-powered systems learn to detect crop diseases by analyzing images, while automated tractors use machine learning to improve planting and harvesting efficiency based on past performance and real-time conditions.

Once we have a smart machine, we need it focused on Natural Interaction with humans, which is what Big Idea Four is all about. Machines can learn to recognize our appearance, understand our speech patterns, and communicate with us in our own language. Voice assistants like Siri and Alexa listen to our requests and respond in our language. In agriculture, AI-powered virtual assistants help farmers by providing real-time weather updates, pest control recommendations, and insights on soil health. Some farm equipment now responds to voice commands, allowing farmers to operate machinery hands-free while working in the field.

Finally, really smart machines create opportunities for really big mistakes. Big Idea Five is about the Societal Impact of AI and how it can work as a force for good. Smart cities provide huge opportunities for security, but this can require facial recognition. A city that always knows where you are poses significant privacy concerns. Similarly, in agriculture, AI-driven surveillance can monitor fields and livestock to improve security and efficiency, but constant monitoring of workers raises ethical concerns.

All five big ideas, brought to you in the context of agriculture on the farm and in the greenhouse, give you a solid foundation for the next generation of technology in farming: AI.