AI and machine learning
In order to plan and teach an engaging lesson exploring AI and machine learning at the junior primary level, I would usually seek to draw on the knowledge of an outside expert. However, today I taught one of the most engaging and exciting lessons utilising the tools and lessons contained within code.org, leaving students with a sound understanding of how machine learning can be used to solve real world problems.
With the components of STEM as the central pillars of the lesson, I was keen to find a way that students could understand how technology can help us solve real world problems, within the inquiry context of ocean pollution.
The AI for Oceans resource from Code.org is so much more than coding. Not only does it teach students about machine learning and AI, it also explores the ethical implications of these.
The first activities in the lesson require students to teach their AI bot what is classed as a 'fish' and 'not a fish'. The more data the students give their bot, the more accurate it is. Excitement levels were high as students eagerly watched their machine classify each object, with a few squeals and objections as fish were placed into the trash pile! Back to training they went!
As the lesson progresses students are asked to teach their machine how to classify their fish based on adjectives - happy, awesome, wild etc. This is a great activity to explore perspective as students quickly come to realise that this isn't such as easy task. With half the class labelling one fish 'happy' due to it's smirk and the other class refuting this, it quickly opens the door to deeper conversations!
I highly recommend checking this resource out if you are looking to teach machine learning to your students or are after a resource to support the exploration of ocean pollution.
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