The pandemic has in no doubt super-charged the need for the education sector to embrace the use of artificial intelligence (AI) in the classroom. New technology can help to educate children, based on their specific needs, as well as to assist educators in providing the best opportunities and environments for their students to learn.
With the prospect of schools closing across the country due to the new Omicron variant, and the latest Ofsted report stating that nearly all children in England have fallen behind in their education as a result of the pandemic, it’s time to look to the future and embrace a change in educational practice that best suits these new circumstances.
Though it should not replace the physical classroom, online learning has become a viable option during lockdowns and has given parents and teachers alike a taste of how digital tools can be used to help teach pupils. With this newly gained trust, it’s time to delve deeper, through extensive research, to see how other new technologies can be applied to learning.
AI vs the human teacher
Despite this increased trust in digital tools, just 33% of parents are in favour of AI being used in their child’s education, according to our 2021 Education Report which we carried out with Kantar, and only 18% of schools in the UK are currently using AI-based teaching solutions.
Equally, though, when asked about what AI should be used for, 59% of UK parents said AI should create a learning environment based on children’s needs – which can be achieved by introducing AI technology to the classroom.
One blocker towards the use of AI in schools could be a lack of understanding and a fear that it will replace human teachers. This is understandable; however, you can rest assured that AI will not take over the role of the human teacher. Professor Rose Lukin of the Learner Centred Design at UCL recently stated at the Cambridge Summit of Education that though we’ve entered the early stages of what she calls “the fourth industrial revolution”, where some sectors are choosing automated systems over human workers, it’s safe to say that “we’re not about to automate education”.
The human teacher has the ability to tap into their own social intelligence and adapt to individual and group circumstances, ensuring that their students are engaged and interested in learning. These are skill sets that can only be carried out by humans, as AI does not yet have the ability to understand itself, or know how to empathise with others, which is an important trait for teachers.
The education sector needs to work out how to unite the best attributes of both AI and human teachers so that they can work together to benefit students and educators. AI can help drive efficiency and reduce the amount of daily admin that teachers have to trawl through, so that they can spend their valuable time more productively in the classroom. It can additionally give students the ability to learn at their own pace, allowing them time to absorb information better and not be overwhelmed by school work.
Using AI for education
During her previously mentioned talk, Professor Lukin summed up the solution nicely, saying that there are three routes for AI to impact education: using AI to tackle big educational challenges, educating people about AI so that they can use it safely and efficiently, and finally, changing education so that we focus on human intelligence and prepare people for an AI world. This doesn’t mean we have to get more people working in developing AI – it means we need to further understand and embrace the capabilities of new technology.
Unfortunately in education, it is often overlooked that there isn’t enough measurement of data in the offline world. Education tries to offer treatment without a thorough diagnosis, and seeing as data currently isn’t measured properly, it is hard to improve on it. At GoStudent, we are using AI and data collection to better understand what the ideal learning environment looks like. That way we can collate and measure the data and look at what makes a great lesson, what makes a great teacher, and what triggers high engagement with the student.
Highly skilled teachers have a positive effect on the performances of their students, so the education sector needs to focus on development and training opportunities.
This year, we carried out two pilot studies using the intelligent emotion tracking tool, iMotions, which measures 32 points on the face in order to analyse emotions, to see which emotions are prevalent in the classroom, how they correlate between tutors and students, and which emotions can be beneficial for a successful learning environment.
With the first study, which was done over an eight-week period involving over 100 online tutoring sessions between 16 teacher-student pairings, we found that emotions transfer from teacher to student, and if the emotions are positive the students are more attentive. Interestingly we also found that strict teachers received higher levels of engagement as they were able to grab the attention of their students, as long as it was in a positive manner.
For our second study, we wanted to further understand how emotions affect teaching, and see which emotional set creates a better learning environment and can contribute to academic improvement. Across more than 900 tutoring sessions, the following factors were examined: tutor emotions, length of the session, time in the day that the session took place, length of the collaboration between tutor and a student, and the subject taught.
What we found was that the positive emotions of the tutor correlated with those of the student, and that ‘joy’ was the most prevalent emotion during the sessions. Additionally, the best time of the day to hold an online tutoring session is between 1pm – 3pm, as opposed to 4pm – 7pm when attention spans were lower. The most productive sessions were when the speaking time of the tutor was similar to the student’s.
What these two studies show is that AI can be used to make educational practices more measurable and quantifiable. It allows us to take the knowledge learnt from the analysed sessions to help train teachers and adjust lessons accordingly. The results can additionally be used in recruiting the best tutors and matching them with the student that suits their skill set.
In time, and once research has been carried out on a far larger scale, these learnings could, in theory, be used to restructure the school day. For example, if we learn when students are most receptive to learning, we can then shape their schedules around these insights to optimise their educational experience.
Our research is just the tip of the iceberg. There is so much potential for AI to be used to support education, ranging from virtual mentors to a more universal learning system that supports the specific needs of each individual child. The education sector might be a bit slow and cautious about embracing AI as a solution, but thankfully changes are happening.
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