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Why I'm building an AI math tutor for dyscalculia — and grounding it in 30 years of ITS research
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Why I'm building an AI math tutor for dyscalculia — and grounding it in 30 years of ITS research

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5 min read
Closing the feedback loop: how mistake classification drives adaptive problem selection in NumPath
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Closing the feedback loop: how mistake classification drives adaptive problem selection in NumPath

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3 min read
Why teachers need explainable AI, not just accurate AI — building the KC dashboard
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Why teachers need explainable AI, not just accurate AI — building the KC dashboard

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3 min read
Attempt history in the teacher dashboard — the scalar subquery pattern
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Attempt history in the teacher dashboard — the scalar subquery pattern

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4 min read
Prompt engineering for teacher insights with Claude — structured JSON and graceful fallbacks
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Prompt engineering for teacher insights with Claude — structured JSON and graceful fallbacks

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4 min read
Bayesian Knowledge Tracing in 37 lines of Python — how NumPath models what a student knows
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Bayesian Knowledge Tracing in 37 lines of Python — how NumPath models what a student knows

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4 min read
Building a FastAPI + Vue 3 research platform: the 4 bugs that almost broke Phase 1
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Building a FastAPI + Vue 3 research platform: the 4 bugs that almost broke Phase 1

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5 min read
Building a mistake taxonomy for dyscalculia — 8 error patterns, rule-based, no ML required
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Building a mistake taxonomy for dyscalculia — 8 error patterns, rule-based, no ML required

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5 min read
From Bayesian to deep knowledge tracing — upgrading NumPath's student model with a PyTorch LSTM
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From Bayesian to deep knowledge tracing — upgrading NumPath's student model with a PyTorch LSTM

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5 min read
Clean Architecture in a FastAPI + Vue 3 monorepo
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Clean Architecture in a FastAPI + Vue 3 monorepo

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5 min read
60 hand-crafted math problems: what I learned writing seed data for an adaptive tutor
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60 hand-crafted math problems: what I learned writing seed data for an adaptive tutor

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5 min read
Making LLM outputs auditable: the provider abstraction pattern
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Making LLM outputs auditable: the provider abstraction pattern

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5 min read