The growing complexity of Industry 4.0 and Internet of Things environments requires engineering education to promote deep conceptual understanding rather than reliance on high-level abstractions. Traditional microcontroller instruction often obscures hardware-level processes, limiting students' ability to analyze, optimize, and ethically evaluate embedded systems. This study proposes a human-centered, two-phase pedagogical model designed to bridge this abstraction gap in mechatronics education. In the first phase, students develop foundational computational literacy through a custom 4-bit microcontroller simulation that reveals how low-level instructions affect registers, memory, and control flow. This transparency strengthens causal reasoning and supports ethical reflection on system design. In the second phase, students apply this knowledge to a real-world sustainability challenge by using the Arduino Explore IoT Kit to build a light-monitoring system for baby plants at Vivero Nochebuena. The system measures ambient illumination and generates alerts when light levels fall below optimal thresholds, connecting embedded-system design to environmental responsibility. A mixed-methods evaluation confirmed the model's effectiveness. Pre- and post-test comparisons revealed significant learning gains (t = 10.8566, p = 1.6 × 10-8; Cohen's d = 2.714). Survey results indicated high engagement, perceived usefulness, and ethical awareness. Qualitative reflections showed that students developed confidence and agency, transitioning from procedural operators to reflective designers. These findings demonstrate that coupling low-level transparency with purposeful application fosters deeper learning and supports human-centered engineering formation.
