Mr. Anand sharma

Architecting Scalable Data-Driven Assessment Systems for Adaptive Learning in Education

Abstract:

 

In today’s rapidly evolving digital education landscape, building scalable, flexible, and intelligent assessment systems is critical. This talk explores how data science principles are embedded into the architectural design of cloud-native assessment platforms to enable personalized, real-time evaluation of learners.
Drawing from real-world implementation in a large-scale EdTech project, we’ll walk through a modular, clean architecture that leverages structured educational data, student performance metrics, and metadata-driven decision models. The system dynamically generates adaptive assessments tailored to individual learning paths—reducing manual effort by 70% and accelerating template rollout by 90%.

We will discuss the integration of NoSQL (DynamoDB) and relational (SQL Server) databases, the use of AWS Lambda and SQS for scalable ingestion and processing, and how student learning data feeds a feedback loop for continuous content optimization.

The session highlights the convergence of software architecture and data science to create systems that are not just reactive, but predictive and adaptive—paving the way for next-generation intelligent educational platforms.

Profile:  

With over 18 years of experience in software engineering, enterprise architecture, system design, cloud-native solutions and technical strategy across industries such as financial service, insurance, education and semiconductor, I am confident that my expertise aligns well with your needs.

Throughout my career, I have designed and implemented microservice based platforms, reusable architectural components and modernization blueprints that scaled across multiple business units. My experience spans developing scalable, data-driven solutions for large-scale organizations, focusing on performance, cost optimization, and security.

Though my background has been in software architecture and cloud platforms, I started transitioning into the machine learning and data science world. I am actively upskilling through targeted study and experiments in areas such as predictive modeling, natural language, computer vision, and generative AI for intelligent document analysis, particularly with applications to real world system and enterprise platforms.

I have had the privilege to lead high impact projects such as reusable Generic Search Framework for a over $10B annual revenue leading insurance company, which accelerate application delivery and reduce development efforts across the teams, And an enterprise Assessment Toolkit in the education sector that improved content scalability, reduce operational costs, and enhance platform performance 

I hold a Bachelor’s in Computer Science, certified in TOGAF 9.2, Azure and .Net. I am skilled in leveraging technologies like .Angular/ReactJS, Net, C#, Rest/GraphQL APIs, SQL and NoSQL databases, AWS, Azure, Python, among others. This solid academic foundation, paired with my extensive hands-on experience, has equipped me to evaluate and contribute to cutting-edge research with both technical depth and creative insight.