  We conducted a field study at a K-12 private school in the suburbs of
Melbourne, Australia. The data capture contained two elements: First, a 5-month
longitudinal field study In-Gauge using two outdoor weather stations, as well
as indoor weather stations in 17 classrooms and temperature sensors on the
vents of occupant-controlled room air-conditioners; these were collated into
individual datasets for each classroom at a 5-minute logging frequency,
including additional data on occupant presence. The dataset was used to derive
predictive models of how occupants operate room air-conditioning units. Second,
we tracked 23 students and 6 teachers in a 4-week cross-sectional study
En-Gage, using wearable sensors to log physiological data, as well as daily
surveys to query the occupants' thermal comfort, learning engagement, emotions
and seating behaviours. Overall, the combined dataset could be used to analyse
the relationships between indoor/outdoor climates and students'
behaviours/mental states on campus, which provide opportunities for the future
design of intelligent feedback systems to benefit both students and staff.
