Purpose of the study: This research article talks about the Learning by Designing (LbD) pedagogy where students get engaged in small tasks which are hands-on, timed and in class. With evolution of Artificial intelligence (AI) in the teaching learning process it is important to develop strategies where students develop higher order thinking with unique projects and reduce temptations to rely on AI. Methodology: Fifteen students engaged in a three-day design-based activity to monitor solar panel performance using temperature, light, and current sensors connected to an Arduino microcontroller. Unlike traditional demonstrations, this hands-on design task emphasized critical thinking, collaboration, and reflection. The Arduino controls all these sensors and allows quantifying the readings for aforementioned parameters, which can be displayed on a computer screen and finally stored. Main Findings: This experiment is done by a group of students and their learning experiences are discussed. A mixed-methods approach was used: technical data analysis complemented by qualitative reflection and questionnaires assessing cognitive development. Findings indicate measurable improvement in analytical reasoning (87% of students), practical problem-solving (80%), and creativity through iterative prototyping. Novelty/Originality of this study: This study proposes a Learning by Design framework integrating Arduino–IoT experiments in solar energy optimization to explore how such activities promote higher-order thinking, problem-solving, and academic authenticity in an AI-rich educational landscape. While many studies emphasize technical success, few have examined how such IoT-integrated, design-based experiments enhance cognitive and metacognitive growth.