Evaluating the effects of indoor air quality on teacher performance using artificial neural network

Purpose A building's Indoor Air Quality (IAQ) has a direct impact on the health and productivity its occupants. Understanding effects of IAQ in educational buildings is essential both design construction phases for decision-makers. The purpose this paper to outline air quality occupants' performance, especially teachers students settings. Design/methodology/approach This study aims evaluate teachers' performances deliver requirements building information modelling-led school projects. methodology research approach used quasi-experiment through questionnaire surveys physical measurements indoor parameters associate correlation deduction. technical college Saudi Arabia was case study. developed an artificial neural network (ANN) model define predict relationships between performance IAQ. Findings contains detailed investigation into via (relative humidity, ventilation rates carbon dioxide) teacher performance. Research findings indicated optimal relative humidity with 65%, ranging 650 750 ppm CO 2 , 0.4 m/s rate. ratio considered optimum comfort Originality/value focuses ANN relationship There are few studies that focus very use data analysis.