In an exclusive interview with Edarabia, GESS Dubai Speaker Anupama Muraleedharan, Vice President of Data Science at Educational Initiatives, explains why it is important for educators to cut through the noise, brought by the high influx of data, and gain insights into their students’ performance and learning gaps.
Currently, there is a huge gap in what a student wants to become and how he/she is learning in school. For example, if a student aspires to become a space scientist or a musician, there are no ways in which we can track his/her progress and determine exactly where and how the student needs to improve in order to reach his/her goal. However, with data, we can track their performance and learning gaps in an efficient way and can influence their future learning path. Imagine a world where each student learns with a better understanding and accomplishes their dreams.
This is the era of data, for sure. However, it is very easy to get lost in the colossal data that is in your face every day. Data is the noise, but to hear the music from the noise, it is essential to understand data. Teachers don’t want data, they wouldn’t know what to do with it – they want insights out of data. Over the past few years, as we started gathering more and more data about students, their performance and learning patterns, we have started providing alerts and nudges to teachers, such as, who are those students not completing a topic, who are struggling on a particular question, who are those students not serious in practicing, etc. These inputs enable teachers to understand their class better, optimize their lesson plans and provide interventions to students at the right time.
There are two key challenges that I have observed in India, one is the technology infrastructure. For schools, adopting a data-driven approach would mean having the means to adopt it – hardware, systems, servers, cloud, etc. It becomes a gigantic infrastructural project for a school. Thus, they would shy away from even considering a data-driven approach. Second, data analysis of student learning is still in its nascent stages. Most of the schools do very high-level score comparisons, however, getting to the nitty-gritty and pinpointing the areas of focus at a subject/topic level is still a challenge.
How do we resolve this? For the first concern, we do engage schools that are challenged in technology infrastructure by providing support at a minimal cost, also our Mindspark application can be accessed offline. For the second concern, we have developed multiple applications that can enable teachers at various levels. Teachers can monitor students’ real-time when they work on Mindspark and intervene when they struggle. Teachers get recommendations regarding where they need to focus if the data shows many children showing misconceptions. We also provide frequent and periodic reports and training to school stakeholders on how to use and benefit from these applications.
I am super excited to be at GESS and consider this as a great opportunity to interact with brighter brains who are making a difference in education. I will be talking about the journey of student data at Educational Initiatives over the past 18 years and how we are able to diagnose student learning gaps and enhance teaching methods using this data and machine learning techniques.
We at EI’s Data Science team have only started to scratch the surface and yet, the impact it started making in student learning is amazing. My presentation will answer the question, ’How can Machine Learning impact Human Learning?’ There will be a hands-on demo to showcase how quickly and efficiently a teacher can diagnose the knowledge level of each student in a class of 20-25 students on a specific topic. I will also take the audience through a solution that can provide continuous insights about students’ performance through grades sent to teachers, and how through score predictions we can help students achieve their goals.
Anupama Muraleedharan is a hands-on data scientist with extensive experience in deploying machine learning solutions for various domains. As Vice President, Data Science at EI, Anupama works on the latest and the most appropriate techniques in the field of machine learning to develop personalized learning solutions for students. Anupama is keen to apply augmented intelligence to bring a visible difference in the way children understand and learn. She has been working with schools in India to enable teachers to gain more insights about their students by harnessing the power of data and AI. Anupama is an alumnus of Indian Institute of Technology.
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Excellent Article.
By K K Bhatnagar (Mar, 2019) |