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“AlphAI”: Teaching AI Algorithms to K12 by Training Learning Robots and Visualizing How It Works

AAAI 2025 · Large language models › AI and society · approach: Teacher needs and AI curricula

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Presents AlphAI, an educational software resource that lets K-12 and university students train educational robots with supervised or reinforcement learning while visualizing neural networks, KNN, and Q-learning internals.

Problem

Teaching AI and machine learning concepts to K-12 students is often too abstract, while existing tools only teach using AI and do not reveal how the algorithms work inside.

Approach

Combine robot-based supervised and reinforcement learning with real-time visualization of AI internals (sensor digitization, neural network activity, 1D/2D decision graphs, Q-learning steps) and optional student-written Python AI code, so that students can "open the black box" of AI.

Key results

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Complete the AlphAI workshopAlphAI workshop for elementary school students · Elementary school grades 3–5correct answers: 39% to 65%Helped
Complete the AlphAI workshopAlphAI workshop for elementary school students · Elementary school grades 3–5agreement with perseverance statement: 65% to 81%Helped

Limitations

Experimental setup

Metrics: pre-test/post-test percentage of correct answers on AI knowl

Baselines: Teachable Machine Machine Learning for Kids Cognimates Vittascience

Builds on: AI4K12 Five Big Ideas in AI Teachable Machine Tensorflow Playground

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