Abstract:

Large first-year engineering programs increasingly depend on project-based learning to support engagement, professional skill development, and authentic design experiences. At scale, however, these models face persistent technical challenges related to coordination across sections, mentoring workflows, assessment consistency, and the controlled integration of emerging digital tools such as generative artificial intelligence (GenAI). Existing work in technology-enhanced engineering education often emphasizes individual activities rather than the underlying systems required to support large cohorts.

This paper presents a technology-enabled practicum framework that leverages learning management systems, digital assessment tools, and structured data flows to orchestrate large-scale, project-based learning in first-year engineering. Informed by systems thinking and learning orchestration principles, the framework defines modular digital workflows for project scheduling, mentor–team interactions, formative assessment, and feedback delivery. Within this infrastructure, GenAI-supported design activities are embedded as governed components of the engineering design process, with explicit rules for access, prompting, verification, and reflection. GenAI is positioned as a decision-support technology rather than an automation tool, enabling students to interrogate, evaluate, and refine AI-generated outputs.

The framework has been implemented in a multi-section first-year engineering course involving numerous project teams and instructors. Technology-mediated artifacts, including rubric-based submissions, structured reflections, and engagement indicators, are used to support coordination and monitor participation across sections. Preliminary evidence from digital engagement patterns and student-generated artifacts indicates that the system supports scalable implementation while maintaining consistency, transparency, and instructor oversight.

The contribution of this work is a transferable, systems-level design framework for technology-enabled engineering practicums. The model offers practical guidance for institutions seeking to integrate learning technologies and GenAI into first-year project-based curricula while preserving pedagogical intent, ethical oversight, and scalability.

Keywords:

Project-based learning, generative artificial intelligence, learning orchestration, first-year engineering education, learning management systems, GenAI governance, scalable assessment, digital workflows, engineering design, technology-enhanced learning.