Most AI-driven systems deliver content via screens to the student and then dashboards to the teacher. But there is a third way – hybrid AI/AR/Teacher systems that give the teacher enhanced powers to see what they can’t see with their own eyes. No teacher has eyes in the back of their heads but, like self-driving cars, you can have eyes everywhere, that recognise individual students, read their expressions, identify their behaviours and provide personalised learning experiences and feedback. You become a more powerful teacher by seeing more, getting and giving more feedback and having less admin and paperwork to do. The promise is that such hybrid systems allow you to do what you do best – teach, especially addressing the needs of struggling students.
AI/AR in classroom
I’ve written about the use of 3D video in teacher training before but this AR (Augmented Reality) idea struck me as clever. Many uses of AI lie outside of the classroom. This augments the strengths of the teacher by integrating dashboards, personal symbols and other AR techniques into the classroom and the practice of teaching.
Ken Holstein, at Carnegie Mellon, seems like an imaginative and creative researcher, and has been looking at hybrid teacher-AR - AI systems that present adaptive software but also highlight each individual student's progress, whether they’re attentive, struggling, need help and so on. Symbols appear above the heads of each student. The teacher needs glasses that can display this information, linked to a back-end system that gathers data about each student’s performance.
It does, of course, seem all very Big Brother, to some even monstrous, especially those comfortable with traditional classroom teaching. However, as results seem to have plateaued in K12 education, we may need to make teachers more effective by being able to focus on the students who are having difficulties. These ideas make personalised learning possible not by replacing the teacher (the idea behind most AI/adaptive systems) but by giving the teacher individual feedback over the heads of each student, so that personalised learning can be realised.
Face recognition in the classroom
Let’s up the stakes with this face recognition system used in China. It recognises student faces instantly, as they arrive for school, so no need for registration. In the classroom it scans the students every 30 seconds, recognising seven different expressions like neutral, happy, sad, disappointed, angry and surprised, as well as six types of behaviour, such as reading, writing, distracted and so on. So it helps the teacher manage registration, performance and behaviour.
They also claim that it helps teacher improve by adapting to the feedback and statistical analysis they receive from the system. When I’ve shown people this system, some react with horror but if we are to reduce teacher workload, should we consider such systems to help with problems around non-teaching paperwork, student feedback and classroom behaviour?
They also claim that it helps teacher improve by adapting to the feedback and statistical analysis they receive from the system. When I’ve shown people this system, some react with horror but if we are to reduce teacher workload, should we consider such systems to help with problems around non-teaching paperwork, student feedback and classroom behaviour?
Conclusion
What seems outlandish today often turns out to be normal in the future – internet, smart phones, VR. Combinations of technology are often more effective than single approaches - witness the smartphone or self-driving car. These adaptive AR/AI hybrid systems may turn out to be very effective by being sensitive to both teacher and student needs. The aim, is not to replace but enhance the teacher's skills, giving them real-time data, personal feedback on all students in their class and data to reflect on their own skills. Let’s not throw the advantages out before we’ve had time to consider the possibilities.
1 comment:
Very well written
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