A teaching idea, evolving
Physics Through Computational Thinking
What if you could see physics before you prove it?
Physics Through Computational Thinking is a new way to learn physics — building deep physical intuition through visualization, simulation, and hands-on code, in Python and Mathematica, before formal derivations ever appear. What began as a single course has grown, over several years, into a pioneering studio classroom, a national MOOC, and now a book.
The life of an idea
A new way to learn physics
Reimagine the undergraduate classroom around how a working physicist actually thinks — a four-step habit that works on any problem: define, translate, compute, interpret. Intuition first, proof second.
The first course taught in Studio AIR
It became the first course taught in Studio AIR, pioneering the use of India's first adaptive-immersive-responsive classroom — and setting an example others would follow.
From one classroom to thousands
Co-taught with Auditya Sharma on NPTEL / SWAYAM using Wolfram Language, the course reached 5,000+ learners across the country. View the course →
Becoming a book Current
The ideas refined across course and MOOC are being written into a full undergraduate textbook — the manuscript is complete in draft and in review.
A living companion
In development: a companion library of 250+ interactive explorations that pair with the book section by section — so the page you're reading and the simulation in your hand stay in step.
The book
Physics Through Computational Thinking, by Ambar Jain and Auditya Sharma†, is a new kind of undergraduate textbook that builds deep physical intuition through visualization, simulation, and hands-on code — in Python and Mathematica — before formal derivations ever appear.
From reading the story hidden in a graph, to fitting real experimental data, to Monte Carlo methods, random walks, and planetary orbits, every concept is developed the way working physicists actually think — define, translate, compute, interpret.
The manuscript is complete in draft and currently in proofreading and review. We welcome conversations with publishers and collaborators.
† Auditya Sharma is a faculty member in the Department of Physics at IISER Bhopal — faculty page ↗.
Computational thinking, in four steps
Computational thinking isn't really about writing code. A gifted programmer can still be a poor computational thinker — much as a fast typist isn't automatically a good writer. The skill lives in the thinking, not the tool.
Define
Pin down the real question first — what you're trying to find, what you can measure or control, and what you're assuming. Most mistakes are made here, long before any math.
Translate
Recast the question as a model — the relationships and equations that capture it. This is the bridge from a physical story to mathematics.
Compute
Hand the heavy lifting to the machine — solve, simulate, and plot. Work that once took weeks now takes seconds.
Interpret
Read the answer back. Is it sensible? Does it address what you actually asked? What does it reveal, what's missing, and what comes next?