Tag: teaching tools

Class Saathi, Enabling The Critical Stakeholder: The Teacher

Posted on by clusterone 
“Yeh bachon ke padhayi ke level ko samajhne mein bohot zabardast hai aur woh bhi fataak se” (This device is too good at helping us understand student learning levels, and that too at lightning speed)

Mrs Meena, a Grade 5 math teacher in a Government School, Bhopal tells us even before presented with a question.

And this is precisely why we built Class Saathi. To enable existing teachers, who do not lack pedagogical knowledge, instead the hours lost in doing the administrative work.

Class Saathi gives these teachers that one smart tool, with no need for electricity or internet, that enables them to take well-informed data-backed decisions to increase student learning levels, engagement and attendance.

Happy students using Class Saathi clickers in Raj Bhavan School, Bhopal
Classroom engagement increased after using Class Saathi clickers

With more than 7 million students dropping out of the Indian education system and the context of public schools in India, it’s impossible for conventional smart school systems to reduce the learning gaps.

There is a dire need for a paradigm shift for teachers: from being Sage on the Stage, burdened by administrative tasks, to a side free from administrative tasks that allow strategic focus on learning outcomes.

Teachers and students benefiting from using Class Saathi clickers
Students and teachers benefit from Class Saathi

Class Saathi instantly connects all stakeholders and enables multiple feedback loops assisted by features using the power of AI. Enabled with a Learning Outcome Management System and Student Reports, students in a classroom learn effectively and increase teachers’ productivity.

In one of the early pilot tests with over 1000 students in the experimental group and over 500 students in the control group, we found that attendance and learning outcomes increased with Class Saathi in action by 10% and 8%, respectively, in just 30 days.

School girl using Class Saathi for quick assessment
School girl using Class Saathi for formative assessment

Motivated by the early success, Pankaj Agarwal (HBS Class of 2021) and his team at TagHive (a Samsung funded spin-off) have been doing multiple iterations while adding more features to empower teachers in transforming their role from “a sage on the stage” to that of “a guide on the side”.

Class Saathi Helps Students Feel Heard And Enables Teachers to Understand Them Better

Posted on by clusterone

Currently, in India, there is a gap of more than 20% between the literacy rates of folks from the tribal region, and the rest of the country. And with the context of public schools, it’s impossible for conventional smart school systems to reduce these learning gaps.

Class Saathi was created to do just this, to provide personalized education to students, irrespective of their demographics. It is a combination of a clicker for each student and a mobile app for teachers, parents and administrators.

Students in morning assembly in Haite Memorial Friendship School in Mualdam, Assam
Morning assembly at Haite Memorial Friendship School in Mualdam, Assam

Case in point, one of the tribal schools (Haite Memorial Friendship School) in Mualdam, Assam, serves 198 students from nearby ten villages, including a village of a rare and small tribe called Biate tribe.

Run by The Sunbird Trust, an organization that empowers schools in conflict regions in the Northeastern region of India; this is a school that we wanted to explore working with since it is situated in one of the most remote regions in the country.

TagHive demonstrated the ability of Class Saathi to take attendance and quizzes in the classroom that had no internet or electricity, with teachers of Maths and Science from the school.

Class Saathi orientation at Sunbird Trust school in Assam
Class Saathi orientation in a remote school

As teachers and students solved questions together, we saw teachers find the existing learning gaps and think about how they can plan their upcoming classes and strategies. While this happened, we noticed something beautiful happen parallelly. Students who were earlier shy to respond in a regular classroom were responding to questions by pressing the clicker.

In a way, Class Saathi created a safe space for them to feel heard and understood. It will build more confidence in the students to express their opinions, and just like that, the engagement within the classroom would increase.

Pankaj Agarwal (HBS Class of 2012) and his team at TagHive (a Samsung funded spin-off) are now excited about upcoming collaborations with Uttar Pradesh, Madhya Pradesh and Odisha state governments.

These collaborations will allow them to build this confidence in over 5 million students while enabling over 100,000 teachers and administrators to analyse and execute student-centric education.

TagHive is also keen to continue exploring collaboration with even more schools in need with Sunbird Trust, and we’re very excited to hear from teachers in that school:

Hudson Ngamlai, Science teacher at Haite Memorial Friendship School in Mualdam, Assam

Hudson Ngamlai (Science teacher) –

Class Saathi has helped me prepare homework and check prior knowledge of the class.

The AI-powered quizzes and concept notes allow us to understand a particular subject better.

Class Saathi works without internet or electricity, which will, in turn, help our students a lot.

Ruby Sam, Lead Teacher at Haite Memorial Friendship School in Mualdam, Assam

Ruby Sam (Lead Teacher) –

I’m excited to use Class Saathi in our school. It enables us to find each student’s learning gaps & progress in no time.

It brings an inclusive learning environment for all students and provides an equal opportunity for students to respond.

Our school is located in a highly remote location, but since Class Saathi works seamlessly in such sites, I’m excited to use it.

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.