Speeding up Design and Making to Reduce Time-to-Project and Time-to-Market: An AI-Enhanced Approach in Engineering Education

2025-03-20

AIxEDU@AI*IA

AI Summary

Embedded systems courses often suffer from prolonged project development cycles and high barriers to engineering practice. Method: This study proposes an AI-augmented pedagogical paradigm that deeply integrates ChatGPT and GitHub Copilot into software architecture instruction, enabling students to implement real-world, hardware-in-the-loop projects—such as SLAM-based robots—within a structured, AI-enhanced workflow. Crucially, AI is explicitly framed as a human decision-support tool—not a replacement—and a systematic human–AI co-design guidance mechanism is established. Contribution/Results: Empirical evaluation demonstrates a 40% reduction in average development time, significant improvement in problem-solving proficiency, and concurrent increases in project complexity and implementation quality; all student teams successfully delivered fully functional systems. The work provides a replicable, evidence-based framework for AI-integrated engineering education.

Technology Category

• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Machine Learning: Hardware-aware ML
• Intelligent Robots: Embodied AI

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems

Abstract

This paper explores the integration of AI tools, such as ChatGPT and GitHub Copilot, in the Software Architecture for Embedded Systems course. AI-supported workflows enabled students to rapidly prototype complex projects, emphasizing real-world applications like SLAM robotics. Results demon-started enhanced problem-solving, faster development, and more sophisticated outcomes, with AI augmenting but not replacing human decision-making.

Problem

• Integrating AI tools in engineering education
• Reducing project and market time with AI
• Enhancing student problem-solving and development speed

Innovation

• AI tools integration in education
• Rapid prototyping with AI support
• Enhanced problem-solving and development