As a Gen Z and a digital native in one of the most technologically advanced countries, I have experienced a variety of learning technologies growing up. I’ve always had some kind of cutting-edge technology in the education I was provided. Because of technology, my classrooms looked drastically different from what I heard from my parents that they had, and apparently classrooms these days are also quite unlike mines. Here I want to name two major ones that make them dissimilar.
Hardware - Mobile Devices
The biggest difference between learning technology back in my childhood and now is that personalization hasn’t happened then. First, hardware-wise. I remember having a desktop and a big screen/monitor connected to it in the classroom, and sometimes a smartboard too. But they weren’t only for me. Imagine tens of kids singing along a chant video on a big monitor that the teacher played on her desktop. We had the technology, but we shared it.
This is what a typical elementary school classroom in Korea looks like.
A desktop on the desk and a big monitor.
As time goes by, students’ individuality becomes more and more important and it seems like newly developed technologies are supporting that. We’re seeing personal devices in the field of education now. Clickers are the simplest examples. And then there are devices like smartphones and tablets, which enable more complicated personalization in learning.
Software - Adaptive Learning
This is something I had not experienced in my regular K-12 education since I graduated before this concept was technologically available. People’s interest in AI (Artificial Intelligence)—the key technology of personalized learning—started to soar with the Google DeepMind Challenge Match, where Lee, a Korean Go champion, fought against AlphaGo, an AI specialized to play Go. Soon after the match, adaptive learning became a hot topic in the domain of education. Thus, it is fairly recently that content-wise personalization became a thing.
AI (Artificial Intelligence) is the key technology of personalized learning. It analyzes your learning data and recommends you what to learn next that perfectly fits you.
Frankly, I don’t have a particular educational app other than Class Saathi that I’ve used to a degree where I can say that I know well about it. But as a big fan of YouTube’s AI-based suggestion algorithm, I am sure that a good adaptive learning app can make study much more fun and effective. Also just saying, I could logically explain how AI technologies can improve learning outcomes with my Communication degree—I read quite a bit of research papers on communication technology!
I didn’t go further to details of each technology I’ve experienced, simply because I couldn’t choose one out of many. I feel very privileged to be able to say that I’ve had many learning technologies that made my study better because I know it is not the case for a lot of learners in the world. Good learning technology usually requires a big amount of time, effort and money to be commonly used.
When I found TagHive, it didn’t take long for me to decide to apply for the internship, because I saw its endeavor for educational equality. I found it captivating that the company is trying to build a learning technology that can bring better education for all closer. I believe in TagHive’s vision of making the world a better place through Class Saathi, and that’s the main source of my enjoyment for my work here.
I hope you are as interested in the company’s journey as I do. If you are, stay connected with us. Keep your eyes on how Class Saathi evolves. It’s going to be fun watching the little steps we make towards building a great app.