AI-Enhanced PBL and Experiential Learning for Communication and Career Readiness: An Engineering Pilot Course
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The integration of artificial intelligence (AI) in engineering education presents transformative potential for developing next-generation competencies, yet requires careful pedagogical design to maximize learning outcomes. This study investigates an AI-enhanced instructional model combining problem-based learning (PBL) and content-language integrated learning (CLIL) for 180 telecommunications engineering students. The intervention incorporated AI tools (Grammarly, Lumen5, LaTeX) within a scaffolded PBL framework, using role-based tasks and SCRUM methodology to optimize language proficiency, computational thinking, and collaborative problem-solving. Results revealed AI tools contributed significantly to skill development, with 50% of students reporting high utility (Likert ≥4) and measurable improvements in English proficiency (30-33% gain to C1 level) and abstract reasoning (37% increase). AI-supported workflows particularly enhanced research documentation and multimedia content creation, though technical prototyping outcomes (12%) suggested need for complementary hands-on experiences. The findings demonstrate AI's capacity to augment human-centric pedagogies when strategically embedded in curriculum design, validating Luckin's [17] framework for meaningful AI integration in education. Based on these outcomes, a Proyecto de Innovación Educativa will implement this AI-PBL-CLIL model at Universidad Politécnica de Madrid (2025-2026), with planned dissemination through European digital education initiatives. This research provides empirical evidence for AI's role in addressing key engineering education challenges while highlighting the importance of balanced implementation that preserves essential practical competencies. Future studies should explore adaptive AI systems for personalized scaffolding and longitudinal impacts on professional skill retention.