K-12 Education

Designing the future of school learning in the age of AI, grounded in the realities of Indian classrooms and systems.

In the age of AI, Indian K-12 education confronts four fundamental questions: What should students learn? How should teachers teach? How do students learn most effectively? And how should learning be evaluated?

CETLS designs and studies technology-enabled interventions that address these questions with scientific rigor and practical relevance. Our work is rooted in the distinctive conditions of Indian schooling — multilingual classrooms, large public systems, teacher capacity constraints, foundational literacy and numeracy priorities, and the ambitions of NEP 2020 — while generating knowledge that advances the global learning sciences.

What students should learn

Curriculum frameworks, learning progressions, and competency models that balance foundational knowledge with the capabilities required in an AI era: critical thinking, problem-solving, collaboration, digital and AI literacy, creativity, and ethical reasoning — developed for Indian languages and contexts.

How teachers should teach

AI-supported and human-centered pedagogical tools and practices that amplify teacher expertise. This includes intelligent orchestration systems, classroom analytics, and professional learning models that work at scale in real Indian schools.

How students learn

Adaptive learning environments, multilingual tools, and scaffolds that promote deeper understanding, self-regulated learning, and learner agency. Research examines how students actually interact with these systems in classroom and home settings.

How learning is evaluated

Next-generation assessment approaches that remain valid when AI can generate traditional answers — formative systems, process data, authentic tasks, and feedback mechanisms that support both equity and continuous improvement.

Supported by

Learning Middleware →