Engineering Education Speaker Series

Details

Engineering Education Lecture Series: Understanding Self-Regulated Learning in Engineering Design: Patterns, Processes, and Performance

Self-regulated learning (SRL) is critical for success in engineering education, yet we know little about how students actually regulate their learning during complex design tasks. This talk presents findings from a multi-year research program investigating SRL in STEM engineering design contexts, revealing three interconnected dimensions of SRL in engineering design. The first dimension profiles distinct self-regulation behavioral patterns that emerge during design activities. Building on these behavioral profiles, the second dimension introduces temporal models that capture the dynamic and evolving nature of self-regulatory processes, elucidating how regulation unfolds and transforms across different phases of design projects. The third dimension extends this understanding by examining the complex interrelationships among prior knowledge, confidence, self-regulation, and learning outcomes, revealing how these factors synergistically influence both science knowledge acquisition and design competency development. The talk also addresses emerging technologies—including AI feedback and generative design tools—and their impact on students’ self-regulatory behaviors and learning experiences. The talk concludes with actionable recommendations for engineering educators seeking to leverage technology to develop more self-directed, reflective learners prepared for professional engineering practice.

Dr. Zheng is an assistant professor in the Teaching, Learning, and Technology program at Lehigh University and a recipient of the 2024 TICL Outstanding Early Career Researcher Award from the American Educational Research Association. She specializes in educational technology and learning sciences, with a focus on integrating artificial intelligence (AI) and computer simulations into STEM education.
Her research bridges self-regulated learning and engineering design in simulated environments, measuring students’ cognitive, metacognitive, and emotional processes through multiple methods including think-aloud protocols, self-reports, computer trace data, facial expressions, and physiological sensors. Most recently, her team is developing an NSF-funded intelligent tutoring system that helps students build AI literacy while strengthening their ability to set goals, adjust strategies, monitor progress, and reflect on their learning. Dr. Zheng has contributed over 50 peer-reviewed scholarly articles to the field of technology-enhanced STEM education.