I remember the day I experienced artificial intelligence (AI) for the first time in education. It was the late 90s, and I was a math teacher in a London school described as having “difficult circumstances”.
I looked at my students, eyes stuck on their computer screens, the ears covered with helmets, all operating in silence using an adaptive mathematics program. While amazing by the rare moment of tranquility, I also wondered: if students learned from technology, what was the interest that I am there? After all, I was a teacher and quite good (if I say it myself!).
Using data on the learning results of the students generated by the Educational Technology program (EDTECH), I divided the class into two groups according to their skills: I taught half, while the others worked Quietly on their computers, then we changed. I continued to use the data generated by the program to shed light on my teaching and, over time, the students’ results have improved. Technology technology and students have contributed to our mathematics results being 2% added value in England!
Quick advance for today: AI generative technology is breathtaking, with great potential to exploit for teaching and learning. In a world where Seven out of 10 children born in a low and intermediate income country cannot read at the age of 10The AI could help fill the gaps in equity of spectacular learning. But this work needs careful reflection.
I have known many Edtech locations over the years, but only a few impressed me. Most are either too focused on technology, or on a large number of students, without considering pedagogy, or they fail to meet the challenges and obstacles to which poorly served students are confronted with access and ‘Use of technology, especially in low and average income contexts.
In addition, it is too rare to see evidence of impact on learning results. (If you do not show an impact, I suppose there are none!)
Some Edtech solutions combine evidence and the best of human expertise and wisdom with the advantages that technology can afford, in particular in data analysis. And with the recent advances in AI, in particular in natural language treatment, speech recognition and computer vision, I saw pitchs that have breathtaking me – they really make me wish that I teaches again.
Here are three problems with which students and teachers around the world face, as well as AI -based solutions that could help, if they are implemented with meticulous reflection, informed by data and focused on equity ::
For a glossary of technical terms. See below.
Problem 1: Many students do not have access to high -quality learning resources that are adapted to their needs, interest and learning levels.
Students may find it difficult to learn from their starting point and at their own pace, receive comments in a timely and constructive time, or have trouble finding the motivation and support for their learning goals. If they are late, they are likely to stay late and abandon, failing to acquire significant life skills.