Obtaining crowdedness level and crowd movement trends on campus can help in understanding campus dynamics, and therefore, improve campus management efficiency and increase faculty and student satisfaction. Given the limitations of traditional data collection methods that heavily rely on fixed IoT (Internet of Things) devices or mobile sensors, this research turns to crowdsourcing as an alternative approach, capitalizing on the widespread use of mobile devices and web technology. This work introduces a mobile crowdsourcing approach for capturing campus dynamics within universities. We included three HCI (Human-Computer Interaction) modes for mobile crowdsourcing – passive mode, questionnaire mode, and dialogue mode. The passive mode collects the user's movement trajectory upon user’s approval. The questionnaire mode asks for campus dynamics in-formation such as the user's current activity location, activity time, and activity type through a pre-designed questionnaire. The dialogue mode collects the same information as the questionnaire mode, however, through dialogues between chatbots and users. We tested the feasibility of the proposed crowdsourcing approach on a university campus. We found that in the passive mode, the participants perceived the lowest cognitive workload. The questionnaire mode and the dialogue mode can not only produce valuable subjective perception and evaluation of campus dynamics, but also provide acceptable output quality of objective data compared to the passive mode. The dialogue mode outperforms the questionnaire mode in terms of output quality. This work provides valuable implications in designing crowdsourcing apps and improving university management.