- Within the first part of lesson 1 students learn how to build digital environmental monitoring instruments, then we focus on how to use those instruments to undertake data gathering experiments.
- We look at subjective and objective data, observational error and bias. We formulate hypotheses and capture large data sets to test them.
- The data sets we collect are used to undertake a simple, but meaningful data analysis. Students learn data science skills whilst investigating their environment
- With the skills learned a number of cross-curricula experiments can be meaningfully undertaken.
The primary outcome of Module 1 is increased digital and data literacy
These lessons do not include any coding and are aimed at middle and high school students aged 11+.
Students build digital instruments and load them with pre-compiled code to create the tools that are used. The software required is listed in the table below.
There are four lessons in Module 1:
Investigate the common features of a circuit / computer then learn how to build one with xChips.
|Use an environmental monitoring instrument to gather data. Investigate lux and data sorting, perform basic analysis and learn about observational error.|
|Collect 24 hours worth of environmental data and analyse it. Learn about correlations, visualisation, trends and extrapolation.|
|Learn about surveys, objective and subjective data then undertake a project to link light levels with human behaviour.|
Everything you need to know about the lessons is listed in the PDFs, including outcomes, success criteria, ISTE linkage, preparation hints. The lesson workflow is divided into 3 or 4 sections, each of which are stand-alone topics with clear objectives, engaging content and evaluation milestones.
- Click to find out more about the Introduction to Physical Computing course, including what hardware is used and how to get it.
- Click to find out about Module 2.
What pre-knowledge do learners need?
- To work through Module 1 NO prior knowledge of electronic hardware or programming is required, and students from ages 11+ can learn a lot from these lessons.
- Some spreadsheet prior knowledge is required: students will need to have used Excel (or an equivalent) at a beginner level. In each lesson prior knowledge requirements are itemised in detail.