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An important skill required for students in Construction Engineering and Architecture is to understand what the major components are and how the whole system and its components function. Students typically learn to understand HVAC equipment by reviewing two-dimensional (2D) CAD drawings, images and site visits. With latest developments in 3D game engines for facilitating interactive learning, it is now possible for students to experience three-dimensional (3D) environments of HVAC systems. While this technology is still at an early stage in learning application, it has the potential to significantly enhance the capability of students to study, comprehend and gain experience designing HVAC systems. While there were many studies on 3D game-assistant learning, systematic evaluation of the learning effectiveness of complex 3D engineering system is needed to further understand the students’ learning mechanism. In this thesis the author presented some preliminary results in learning of HVAC systems through the use of 3D modelling and game engines. For the purpose of the pilot study, a 3D game environment of an existing whole-building HVAC system was developed to enable students to interactively visualize and operate typical HVAC systems on computer monitors. The learning effectiveness of the developed 3D game was tested with two groups of students, who were expected to learn the same knowledge on HVAC system: (a) an experimental group with 24 students using Unity 3D game environment; (b) the control group only used traditional 2D drawings. A questionnaire designed on the concepts of structure, behavior and function was distributed to and collected from the students right after the class. A descriptive analysis of results obtained from observations and quiz sessions showed a significant difference or improvement in behavioral and functional understanding of HVAC system when Unity 3D model was used compared to using 2D drawings only. However, the test also showed that the difference in structural understanding the HVAC system was not significant in the results from the two groups.
Advisor: Zhigang Shen