AI - Human Teaming and The Scientific Method
The purpose of this lesson is to introduce SimuLab, which utilizes the scientific method with AI to generate simulated data sets, teach students about the role of AI in our world, educate them about AI biases and AI-generated fake news, and provide guidance on how to identify them.
Overview
Students learn the scientific method and practice teaming with AI to generate simulated data. The lesson opens with a short science mystery story and five videos covering each step, from forming a research idea to writing a scientific report. Students measure their lung capacity with a balloon, string, and rulers, identifying the hypothesis, variables, controls, and constants and analyzing results with the claim, evidence, reasoning method. After a peer review and a jigsaw on AI, deepfakes, and fake news, they use SimuLab to generate simulated data and graph it against their own. They present a report, slide show, or poster in a gallery walk. The plan schedules 45-minute class blocks: one each for Engage, Explain, and Elaborate, and two each for Explore and Evaluate.
Lesson Objectives
- The purpose of this lesson is to introduce SimuLab, which uses the scientific method with AI to generate simulated data sets, teach students about the role of AI in our world, educate students about AI biases and AI-generated fake news, and how to identify them. Students will practice using the scientific method through conducting a hands-on experiment and by teaming with AI to generate simulated data. Students will be able to understand and implement the scientific method in designing an experiment. Students will practice hands-on data collection and data analysis with AI-generated data, comparing the two.
Standards
NGSS · 4
- MS-ETS1-1Define the criteria and constraints of a design problem with sufficient precision to ensure a successful solution, taking into account relevant scientific principles and potential impacts on people and the natural environment that may limit possible solutions.
- MS-ETS1-2Evaluate competing design solutions using a systematic process to determine how well they meet the criteria and constraints of the problem.
- MS-ETS1-3Analyze data from tests to determine similarities and differences among several design solutions to identify the best characteristics of each that can be combined into a new solution to meet the criteria for success better
- HS-ETS1-4Use a computer simulation to model the impact of proposed solutions to a complex real-world problem with numerous criteria and constraints on interactions within and between systems relevant to the problem.
CCSS Math · 3
- HSS-ID.A.1Summarize, represent, and interpret data on a single count or measurement variable. Represent data with plots on the real number line (dot plots, histograms,
- 7.SP.B.3Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the centers by expressing it as a multiple of a measure of variability.
- 7.SP.B.4Use measures of center and measures of variability for numerical data from random samples to draw informal comparative inferences about two populations.
CCSS ELA · 2
- RI.6.7Integrate information presented in different media or formats (e.g., visually, quantitatively) as well as in words to develop a coherent understanding of a topic or issue.
- RI.9-10.7Analyze various accounts of a subject told in different mediums (e.g., a person’s life story in both print and multimedia), determining which details are emphasized in each account.