Context is Key!
By making A.I. relevant and providing a ‘real-life’ context, you can create meaningful learning experiences for your students!
The most common questions you will get asked by your students when undertaking a new topic or subject are:
- Why are we doing this?
- Will this help me pass my course?
- When will I ever use this?
- Will this help me get a job?
In other words, how is it relevant?
Contextualisation is not about changing the learning outcomes or objectives. It’s about modifying the learning materials so that they have relevance to the students. To make A.I. relevant for your students, ask yourself the following questions:
- Does this relate to students’ aspirations?
- Can it be related to students’ common interests?
- Can it help students to understand how computing is relevant when making future career choices?
- Does it involve skills that can be used in the workplace?
- Can it be linked to popular culture?
- Does it relate to a recent newsworthy event?
Whilst we have tried to provide as many examples as possible, relating to both AI for Good and industry, the list can never be exhaustive! We therefore recommend that both you and your students spend some time researching examples of A.I. in your designated subject / field. We also highly recommend that you challenge your students to research AI applications in other areas / subjects and explore how these could be used in their own subject / field.
Computer vision is widely used for facial recognition (being able to identify and map a range of facial features)! How could computer vision, in particular facial recognition technology, be used to help identify the best beauty treatment for a client?