For many respiratory diseases, a primary mode of transmission is inhalation via aerosols and droplets. The COVID-19 pandemic has accelerated studies of aerosol dispersion in indoor environments. Most studies of aerosol dispersion present computational fluid dynamics results, which rarely include detailed experimental verification, and many of the computations are complex, making them hard to scale to larger spaces. This study presents a comparison of computational simulations and measurements of aerosol dispersion within a typical ventilated classroom. Measurements were accomplished using a custom-built low-cost sensor network composed of 15 commercially available optical particle sizers, which provided size-resolved information about the number concentrations and temporal dynamics of 0.3–40 µm diameter particles. Measurement results are compared to the computed dispersal and loss rates from a steady-state Reynolds-Averaged Navier–Stokes k-epsilon model. The results show that a newly developed aerosol-transport-model can accurately simulate the dispersion of aerosols and faithfully predict measured aerosol concentrations at different locations and times. The computational model was developed with scalability in mind such that it may be adapted for larger spaces. The experiments highlight that the fraction of aerosol recycled in the ventilation system depends on the aerosol droplet size and cannot be predicted by the recycled-to-outside air ratio. Moreover, aerosol recirculation is not negligible, as some computational approaches assume. Both modeling and measurements show that, depending on the location within the room, the maximum aerosol concentration can be many times higher than the average concentration, increasing the risk of infection.