Abstract

:

Information mined from building information models as well as associated geographical data and Geographic Information System (GIS) analyses can increase the success of construction processes and asset management, including buildings, roads, and public facilities. The integration of information from both domains requires high expertise in both spheres. The existing B.Sc and M.Sc. programs linked to the built environment at the Technical University of Munich offer courses for the Building Information Model (BIM) and GIS that are distributed among study programs in Civil Engineering, Architecture, and Geomatics. Students graduating as professionals in one of these domains rarely know how to solve pre-defined technical problems associated with the integration of information from BIM and GIS. Students in such programs seldom practice skills needed for the integration of information from BIM and GIS at a level that is needed in working life. Conversely, the technologies in both domains create artificial boundaries that do not exist in reality—for example, water and electricity would not be of use if the utilities terminated in front of buildings. To bring a change and bridge the gap between BIM and GIS, a change in the teaching methods of BIM/GIS needs to be considered. The Technical University of Munich (TUM) has developed a master’s course (M.Sc. course) for students in Geoinformatics which focuses on competencies required to achieve BIM/GIS integration. This paper describes the course development process and provides a unique perspective on the curriculum and subjects. It also presents the course objective, course development, the selection and development of learning materials, and the assessment of the intended learning outcome of the course. The developed course is validated through a questionnaire, and feedback is provided by participants of the BIM/GIS integration workshop representing a panel of experts in the domain.

العنوان

ISPRS Int. J. Geo-Inf

الناشر

MDPI

بلد الناشر

ألمانيا

Indexing

Thomson Reuters

معامل التأثير

1,84

نوع المنشور

مطبوع فقط

المجلد

7

السنة

2018

الصفحات

319