Early Reading, Foundational Learning: AI-Powered Solutions for a Changing World

Bridging learning gaps with AI

By: Nakul Jain (Director – Products and Design, Wadhwani Institute of Artificial Intelligence)

A world without technology is unimaginable today. After all, technology has become an integral part of every aspect of our lives, and the education sector—like others—has a lot of opportunities to leverage for impact. The Indian government’s recent budget allocation of ₹1.48 lakh crore towards education indicates a need to emphasize a future-ready workforce. We need a workforce that can use current technology and can constantly upskill with changing technology. Hence, the focus on Gen Alpha must be equally prioritized to ensure readiness. 

Foundational Learning and Its Long-Term Impact 

NIPUN Bharat aims to help every child in India read well and do basic math by the time they finish Grade 3. The goal is to equip children between 3 and 9 years old by 2026-27 by using engaging learning methods. With a keen focus on how children learn in their early years, NIPUN Bharat can help many children do better in school and keep learning throughout their lives. 

Various new technologies are being used to help make this initiative by the Ministry of Education work even better. AI tools are being piloted to give each child the help they need, especially with reading. Personalized tools that provide a tailored approach for students are more enabling than a one-size-fits-all approach, especially when it comes to oral reading fluency. Improving oral reading fluency boosts literacy rates and enhances cognitive development, critical thinking, and problem-solving skills essential for navigating today’s world.  

The Role of Technology and AI

Wadhwani AI’s Oral Reading Fluency solution is a prime example. It currently functions as an assessment tool that supports teachers and students with real-time feedback on reading fluency, giving them detailed analysis of reading patterns and comprehensive reports that could potentially help tailor precise interventions. The solution leverages advanced speech recognition models to assess reading, providing insights on words read correctly, misread, or missed, and calculating metrics like Correct Words Per Minute (CWPM).

In Gujarat, this AI solution has been implemented in government schools through the Vaachan Samiksha Chatbot App, part of the state’s digital education initiative. Thanks to the Government of Gujarat’s visionary approach in spearheading this technology, over 1 million students have benefitted, with more than 3 million assessments conducted to date.

A Vision for the Future 

Imagine an ecosystem where a child, irrespective of their socio-economic background, has access to the latest technology offerings in education. A tool that both they and their teachers can use to assess their current abilities, get tailored interventions, personalized practice material, and a clear trajectory of their growth. All of this is made available for basic reading skills and comprehension, speaking, and writing. Numeracy could also be easily embedded to make it a holistic foundational learning tool. A low-cost offering for the education ecosystem in multiple languages with capabilities not restricted by available infrastructure will be a game changer. Artificial intelligence has made all of this very much achievable. At Wadhwani AI multiple initiatives in this direction will ensure these offerings reach every child.

Investing in early literacy and AI solutions is no longer only about improving literacy rates on paper—it’s about building a solid foundation to ensure healthier, happier and more productive citizens. Solving for reading fluency will ensure individuals are confident and ready to take on the global competition and evolving demands of businesses.

Creating an environment where there is parity in the availability of learning resources will be the most critical.

  • Wadhwani AI

    We are an independent and nonprofit institute developing multiple AI-based solutions in healthcare and agriculture, to bring about sustainable social impact at scale through the use of artificial intelligence.

ML Engineer

ROLES AND RESPONSIBILITIES

An ML Engineer at Wadhwani AI will be responsible for building robust machine learning solutions to problems of societal importance; usually under the guidance of senior ML scientists, and in collaboration with dedicated software engineers. To our partners, a Wadhwani AI solution is generally a decision making tool that requires some piece of data to engage. It will be your responsibility to ensure that the information provided using that piece of data is sound. This not only requires robust learned models, but pipelines over which those models can be built, tweaked, tested, and monitored. The following subsections provide details from the perspective of solution design:

Early stage of proof of concept (PoC)

  • Setup and structure code bases that support an interactive ML experimentation process, as well as quick initial deployments
  • Develop and maintain toolsets and processes for ensuring the reproducibility of results
  • Code reviews with other technical team members at various stages of the PoC
  • Develop, extend, adopt a reliable, colab-like environment for ML

Late PoC

This is early to mid-stage of AI product development

  • Develop ETL pipelines. These can also be shared and/or owned by data engineers
  • Setup and maintain feature stores, databases, and data catalogs. Ensuring data veracity and lineage of on-demand pulls
  • Develop and support model health metrics

Post PoC

Responsibilities during production deployment

  • Develop and support A/B testing. Setup continuous integration and development (CI/CD) processes and pipelines for models
  • Develop and support continuous model monitoring
  • Define and publish service-level agreements (SLAs) for model serving. Such agreements include model latency, throughput, and reliability
  • L1/L2/L3 support for model debugging
  • Develop and support model serving environments
  • Model compression and distillation

We realize this list is broad and extensive. While the ideal candidate has some exposure to each of these topics, we also envision great candidates being experts at some subset. If either of those cases happens to be you, please apply.

DESIRED QUALIFICATIONS

Master’s degree or above in a STEM field. Several years of experience getting their hands dirty applying their craft.

Programming

  • Expert level Python programmer
  • Hands-on experience with Python libraries
    • Popular neural network libraries
    • Popular data science libraries (Pandas, numpy)
  • Knowledge of systems-level programming. Under the hood knowledge of C or C++
  • Experience and knowledge of various tools that fit into the model building pipeline. There are several – you should be able to speak to the pluses and minuses of a variety of tools given some challenge within the ML development pipeline
  • Database concepts; SQL
  • Experience with cloud platforms is a plus
mle

ML Scientist

ROLES AND RESPONSIBILITIES

As an ML Scientist at Wadhwani AI, you will be responsible for building robust machine learning solutions to problems of societal importance, usually under the guidance of senior ML scientists. You will participate in translating a problem in the social sector to a well-defined AI problem, in the development and execution of algorithms and solutions to the problem, in the successful and scaled deployment of the AI solution, and in defining appropriate metrics to evaluate the effectiveness of the deployed solution.

In order to apply machine learning for social good, you will need to understand user challenges and their context, curate and transform data, train and validate models, run simulations, and broadly derive insights from data. In doing so, you will work in cross-functional teams spanning ML modeling, engineering, product, and domain experts. You will also interface with social sector organizations as appropriate.  

REQUIREMENTS

Associate ML scientists will have a strong academic background in a quantitative field (see below) at the Bachelor’s or Master’s level, with project experience in applied machine learning. They will possess demonstrable skills in coding, data mining and analysis, and building and implementing ML or statistical models. Where needed, they will have to learn and adapt to the requirements imposed by real-life, scaled deployments. 

Candidates should have excellent communication skills and a willingness to adapt to the challenges of doing applied work for social good. 

DESIRED QUALIFICATIONS

  • B.Tech./B.E./B.S./M.Tech./M.E./M.S./M.Sc. or equivalent in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, Physics, Economics, or a relevant quantitative field. Work experience beyond the terminal degree will determine the appropriate seniority level.
  • Solid software engineering skills across one or multiple languages including Python, C++, Java.
  • Interest in applying software engineering practices to ML projects.
  • Track record of project work in applied machine learning. Experience in applying AI models to concrete real-world problems is a plus.
  • Strong verbal and written communication skills in English.
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