Tag: AI

AI is the Future of Education

Posted on by pankaj.harvard
Brain circuit
Brain technology photo created by rawpixel.com

The Covid-19 pandemic accelerated the shift to tech-enabled learning, even though it may not have been the most desirable driving force. However, the pandemic pushed tech integration into the field of education.

Companies across the world are happy about this since they can now show the world what technology can do if used in its most essential forms. Before we get into how AI technology plays a role in education, we will understand what AI means!

AI System definition, history, and the likes:

Manual effort in certain areas can drive very little change, especially on a larger scale. Automating some human tasks can maximize impact and reach a larger scale.

For all those tasks, we make use of Artificial Intelligence. While AI systems may perform tasks that we generally associate with humans, it is humans who build the framework that allows for AI principles to function!

AI is a determining tool that uses data to make recommendations, and decisions and also arrive at evidence-based research findings all in seconds. It can save time and a lot of valuable human resources that can be used in other domains of functioning. It can also help people make decisions based on risks and rewards. So, these are just a few of the vast capabilities that AI can power. 

With the right frameworks, AI can do things efficiently, very effectively, and on a massive scale.

Robotic hand
Robot hand photo created by rawpixel.com

AI in Education:

Keeping all the aforementioned points in mind there are a few things that we can be sure that AI does- 

  1. It helps teachers understand not just the needs of their students but also more personal things about their students. For instance, teachers can learn through AI where a student’s learning interests are.
  2. AI gives evidence-based reports to teachers rather quickly so teachers can foster collaboration with their students.
  3. AI is what is revamping and revolutionizing assessments right now. What AI does is use assessments as a diagnostic tool that reflects on a child’s learning needs instead of using it as an indicator of their capabilities.
  4. AI as a feedback tool is more reliable, free from bias and cancels out any human error in the estimation process. When feedback is based solely on a student’s performance, they tend to rely on it more than any other form of feedback.
  5. AI helps eliminate boundaries. AI does not see geographical boundaries. It can be used anytime anywhere, truly inspiring the idea that AI is a global experience.

There is a lot about AI that is still under research and development but what we have in the markets and in access these days makes use of some very optimal tools to give students an experience they will enjoy.

Innovation drives artificial intelligence, and with proper coaching, students learn to enjoy the methodology behind it. What AI also does is inspire and it is important now more than ever that students appreciate their opportunities to learn and act on them with performance, drive, and passion!

Learning Analytics in Class Saathi

Posted on by pankaj.harvard

The education sector has seen a lot of reformation in recent years. It is not unusual since it is one field where progressive values are incorporated and included without much doubt or hesitation. The education sector survived the pandemic and all the various turbulences it presented for this very reason.

Change is welcomed in the education sector, and technological integration plays a crucial role in embracing these changes. One instrument extensively researched and integrated into education today is “Learning Analytics.” 

Let us understand what Learning Analytics is and how Class Saathi incorporates it into its system.

Photo by Mikhail Nilov from Pexels

Learning analytics is a mechanism that collects vital data to assess key areas of learning and reports on it to drive impactful reformations. The logical framework that governs learning analytics is nothing new. It has been around for decades. So now why is it gaining so much novel attention?

The answer is simple, learning analytics makes use of artificial intelligence that uses data smartly in order to not just report findings but also suggest measures that can accurately predict future outcomes based on these numbers.

This hastens the process of data collection, interpretation and analysis and also gives educators tangible outcomes to work on so that change can be driven in the most efficient and minutest ways.

This takes us to the next part of this article – what are the learning analytic tools that Class Saathi incorporates into its system?

Class Saathi prides itself on being an app that gives personalised learning recommendations for every student that uses this app. This may sound like a tall claim but it is one that is rightly justified by the system that our developers in South Korea have worked so hard to build. For the purpose of this report, we spoke to the people who creatively built this system and this is what they had to say:

Personalised learning is at the heart of Class Saathi’s operations and we built an app that benefits every student who uses it. For this purpose, our developers built a system with three main components:

A. Knowledge Level
A system records and analyzes every response based on factors like difficulty level and skills. The app first records the comfortable learning level of the student and gives them questions based on the recorded level and pushes them to gradually move up.

B. Updated Difficulty Level
The difficulty level for each skill or question is assigned based on the number of students who get it right in the first attempt. If there are more students who get one question or skill right, then the question is deemed easy and difficult if it is vice versa. This keeps changing with improved student learning outcomes.

C. Solve Interval Data
This is the most revolutionary data tool that we use. What this does is record questions that a student gets wrong consistently and recommend quizzes to help them learn the concepts attached to these questions.

The system does this for a while and then gives the student the same question to see if they have learnt the concept and moved up the levels of difficulty. This prepares students to reach higher order levels or learning without making it a difficult process.

As you can see, the logical framework that governs the app uses very complicated metrics and building that can only have been the product of genius minds. It is no easy task to standardise a product for students with globally varying learning levels. 

Having said all of this, we must also remember that learning analytics can not be 100% accurate because it is constantly evolving. It can however predict the most probable outcomes for maximum benefit and maximum reformation.

According to our developers, matching reality to the learning level recorded by the system is challenging due to various variables that can interfere with accurate readings. However, the idea is to perfect a system by recognising the gaps, much as we do for our students.

The key is to continually strive for perfection, aiming to eliminate gaps from our system and obtain outcomes that do not hinder a deeper understanding of student behavior and learning.