The complex demands of the Fourth Industrial Revolution require engineers capable of deep learning and critical thinking to synthesize modern manufacturing concepts, skills that passive, lecture-based curricula often fail to cultivate. In response to this challenge, this pilot study introduces a novel, integrated, active-learning pedagogical model for a senior electrical engineering technology class, specifically designed to immerse students in the convergence of automation and artificial intelligence. This action research project employs a three-stage, integrated learning experience designed to enhance conceptual understanding and cultivate essential soft skills. First, to scaffold the initial inquiry, students utilize a large language model to generate a structured research outline. This tool reduces the cognitive load of navigating unfamiliar concepts and provides a methodical path for exploration. Second, students are tasked with internalizing and synthesizing this AI-guided research by delivering a constrained presentation in a PechaKucha-style format (20 slides, 20 seconds each). Rooted in the cognitive theory of multimedia learning, this design compels students to distill complex information into its most essential components, thereby promoting knowledge retention. Finally, students engage in a critical reflection process using a photovoice methodology, taking and narrating photographs related to their personal connections to recent advances in manufacturing. This qualitative method is known to provide nuanced insights into students' conceptual understanding and serve as a powerful, authentic form of assessment. This multi-modal approach is hypothesized to not only facilitate deep exploration of technical knowledge but also to cultivate vital competencies such as communication, creativity, and interdisciplinary problem-solving. The findings of this pilot study are expected to provide a critical framework for future curriculum design, demonstrating how the thoughtful integration of technology and active-learning methodologies can cultivate the adaptable skill sets essential for exploring and succeeding in the modern workforce.
The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026