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Five-level pyramid hierarchy for AI-integrated engineering curricula based on scaffolded instruction

Design · All designs
Evidence · no claims cited

Description

The MLME course is organized as a pyramid representing scaffolded instruction, in which guidance is gradually reduced as students gain mastery. The article states the course "is a project -based course designed according to the principles of scaffolded instruction [44], i.e., gradually reducing guidance as students gain mastery, which is represented as a pyramid in Fig. 2." The levels are, from the base: curiosity and self-motivation as the foundational attitude; foundational STEM knowledge provided just-in-time within each project; an introduction level teaching core ML theories and techniques; an application level practicing algorithms on publicly available datasets; and an advanced level covering thermal theory topics and the four integrative projects.

Design Implications

Context

Requirements

  • Foundational STEM knowledge must be provided before more complex concepts, with basic matrix operations and programming syntax introduced in the first project and later material given just-in-time aligned with the problem at hand

Constraints

Target Learners

  • mechanical engineering students with limited AI and programming background

Learning Goals

  • progressive mastery of ML concepts and their application to thermal engineering problems

Claims

Examples

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Key Sources

  • Changgen Li, Han Hu, Christy Dunlap, Nathaniel House, and Jonathan Wai. (2025). Giving Mechanical Engineers Intelligent Tools: A Project-Based AI Education Curriculum in Thermal Engineering. https://github.com/hanhuark/machine-learning-for-engineers
Page metadata
Field Value
type design
id mlme-pyramid-scaffolded-hierarchy
title Five-level pyramid hierarchy for AI-integrated engineering curricula based on scaffolded instruction
description The MLME course is organized as a pyramid representing scaffolded instruction, in which guidance is gradually reduced as students gain mastery.
status review
generated by process:settle-candidates on 2026-10-11
trust unverified — no one has confirmed this page's content
sources 1 — changgen-li-2025

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