Project 04
PART IV -2
THE CONCEPT OF AI SERIOUS GAMES IN AI EDUCATION FOR
LEARNING DIFFICULTIES BASED ON THE LEGO BOOSTER SENSOR AND POKEMON GAME
Case Study Structure: Executive Function Challenges
It is an existing, well-validated tangible platform with programmable sensors, motors, and platform with programmable sensors. Motors, and a Scratch-like visual programming layer- lower barrier to building a working sensing-layer prototype than custom hardware.
AI
interpretation Layer: Core Intelligence
Multimodal fusion (sensor x in-game behavior)
Fuses physical-sensor stream with software-interaction
stream on a shared timeline. A cross-attention or late-fusion architecture lets
the model weigh “did they hesitate physically” against “did they choose the
correct in-game option” -distinguishing a motor struggle from a cognitive one,
which matters enormously for EF diagnosis Multimodal fusion (sensor x in-game behavior)
Case Study Structure: Executive Function Challenges
Target skill:
Sequential
planning + working memory + inhibitory control (The common EF triad deficit in
ADHD/Dyspraxia)Story frame:
“Builder-hero” Building
up a village. Each building task=An EF exercise in disguise.Implementation AB: LEGO Boost/ Mindstorms Sensors
It is an existing, well-validated tangible platform with programmable sensors, motors, and platform with programmable sensors. Motors, and a Scratch-like visual programming layer- lower barrier to building a working sensing-layer prototype than custom hardware.
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