Interactive teaching tool: Efficiency wages, markets & tax incidence
Leveraging generative AI for teaching
An interactive tool I built for one-on-one economics teaching, covering the labor-discipline / efficiency-wage model, supply & demand, and tax incidence. Drag the sliders, switch scenarios, and watch the equilibria move. (Interface in German.)
I built it using generative AI (LLM-assisted coding) — from concept and model specification through to the finished single-file application. It’s a small, concrete example of the AI-assisted development workflow I use in my research.
How I built it
Developed with generative AI as a coding collaborator: I specified the economic models, the interaction design, and the didactic flow, then worked iteratively with an LLM to produce a single-file HTML application — no frameworks, no dependencies. Hand-tuned canvas rendering for the model curves, reactive sliders driving live recomputation of equilibria, scenario walkthroughs, and a tabbed interface covering three textbook models. Built to run anywhere a browser opens, including offline in a tutoring session.
The point isn’t just the tool — it’s the workflow: translating domain knowledge into a working, interactive artifact quickly by directing generative AI, the same approach I apply to research pipelines.
Citation
@article{samartzidis2026,
author = {Samartzidis, Lasare},
title = {Interactive Teaching Tool: {Efficiency} Wages, Markets \& Tax
Incidence},
journal = {In preparation},
date = {2026-07-11},
url = {https://lsmantiz.github.io/posts/econ-interactive-tool/},
langid = {en}
}