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Project-based robotics + AI curriculum structured by P3 Task Taxonomy with backward design

Design · All designs
Evidence · no claims cited

Description

The curriculum comprised 10 lessons followed by a robotics engineering design challenge, aligned with K-12 CS standards and structured using Barak and Assal's P3 Task Taxonomy: Practice tasks with predefined solutions, Problem Solving tasks allowing multiple approaches, and Project tasks as complex student-driven endeavors. It was developed with backward design, starting from the design challenge and working backward to essential learning objectives.

Design Implications

Context

Requirements

  • mBot robotics kits with the mBlock block-based coding platform including AI/ML extensions
  • alignment with K-12 CS standards

Constraints

  • Sensor-based programming relied on student-written rules rather than data-driven learning, serving as a conceptual foundation for AI

Target Learners

  • high school students
  • ninth and tenth graders

Learning Goals

  • programming concepts
  • sensor-based robotics
  • machine learning via image recognition
  • engineering design process

Claims

Examples

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Key Sources

  • G. McLaughlin, E. Novak, S. Ahmadi, J. Li, Y. Guo, R. Liu, & L. Borgerding. (2026). Pathways to learning: exploring high school students' learning of AI-powered educational robotics. Education Tech Research Dev. https://doi.org/10.1007/s11423-026-10651-w
Page metadata
Field Value
type design
id p3-taxonomy-robotics-ai-curriculum
title Project-based robotics + AI curriculum structured by P3 Task Taxonomy with backward design
description The curriculum comprised 10 lessons followed by a robotics engineering design challenge, aligned with K-12 CS standards and structured using Barak and Assal's P3 Task Taxonomy: Practice tasks with predefined solutions...
status review
generated by process:settle-candidates on 2026-10-10
trust unverified — no one has confirmed this page's content
sources 1 — g-mclaughlin-2026

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