Lessons learned through a case study of IAQ monitoring and participatory design in learning spaces

Indoor environmental quality, particularly indoor air quality (IAQ), significantly influences students’ cognitive performance, comfort, and well-being. This study explores the integration of low-cost micro-electromechanical systems (MEMS) sensors and participatory design methods to monitor and improve learning environments. The research addresses key questions: How effectively can affordable MEMS sensors measure environmental factors in real-time classroom conditions? How do students with and without sensory sensitivities perceive these environmental factors? Which environmental stressors most significantly impact concentration and well-being? Using a five-phase mixed-methods framework, the study deployed MEMS-based sensors microcontrollers to monitor temperature, humidity, lighting, noise, and particulate matter. Simultaneously, tailored questionnaires gathered student feedback on comfort, concentration, and perceived environmental quality. Despite the system’s cost-effectiveness and real-time capability, several limitations emerged. Low student participation, particularly among neurodivergent individuals, limited the inclusiveness and representativeness of the qualitative data. Additionally, the uniformity of the deployed learning environments—mostly standard classrooms and labs—restricted the ability to generalize results across diverse spatial typologies. Nevertheless, preliminary findings revealed correlations between elevated noise levels, poor air quality, and reported discomfort or difficulty concentrating. The study also emphasized that student engagement in environmental assessment can foster greater awareness and inclusive decision-making. Lessons learned underscore the importance of involving diverse user groups, deploying sensors in differentiated learning settings, and refining technical tools for educational applications. This research contributes practical insights for educators, designers, and policymakers aiming to create responsive, student-centered learning spaces. Future work will focus on enhancing participation, broadening environmental diversity, and improving sensor accuracy to inform inclusive, data-driven design strategies.