Developing a Smart Tool for Campus User Alignment

Developing a Smart Tool for Campus User Alignment

ter Veer, Sven (TU Delft Architecture and the Built Environment)

den Heijer, A.C. (mentor)
de Graaf, R.P. (mentor)
Smit, M.J. (graduation committee)

Delft University of Technology

Architecture, Urbanism and Building Sciences | Management in the Built Environment

Smart Real Estate Management

2018-07-05

Context Digitalisation enables students to study virtually everywhere. However, demand for study space on the campus remains high and is even increasing. Additionally, students place higher demands on the quality and availability of facilities (Valks, Arkesteijn, den Heijer, & Van de Putte,  2016, p. 15). However, recent research on Dutch campuses (Campus NL, 2016) shows several problems were identified regarding the alignment of campus space. (1) The unpredictable nature of demand for campus space makes it difficult to align demand with supply. (2) Another reason for not being able to comply with campus space demand is a result of problems in finding a suitable study space. Objective Preference Function Modelling already proved its potential in designing accommodation strategies. Furthermore, there is the need to involve a greater number of stakeholders and a need to improve the usability of the modelling technique. A smart tool presents opportunities to improve the user involvement in the management of design accomodation. As a result of the scientific gap, this thesis will explore these opportunities by developing a smart tool which provides information on study space while simultaneously generating information to support campus management.MethodsFor this thesis an engineering design process is used. Literature research is used in this research to gain understanding of the design problem and its users. With this knowledge, a smart tool will be developed along a iterative sequence of prototype evaluations to support the design process. Design user involvement will be established by two prototype evaluations evaluations with the use of interviews. For the evaluation of the proposed smart tool an assisted approach is utilized. In this evaluation, the data collection methods Task load index and Post-Experience interview are used. A Task Load Index (TLX) measures cognitive workload by assessing how much mental effort a user expends whilst using a prototype or deployed system. While individual Post-Experience interviews are a quick and inexpensive way to obtain subjective feedback from users.ResultsAs a result of the first user interviews it was established that users had difficulty with understanding how the system works and which values needed to be entered. Therefore, the primary focus for version 2 was finding ways to improve understandability and usability of the system. One implementation of this, was to improve navigation by having all the input fields on the same tab in excel. Therefore, User forms were used, allowing to have a better overview of the system by preventing the need to switch between tabs. The database structure represent the storage (back end) of information which is needed to operate the proposed Smart Tool. To visualize this an Entity Relationship (ER) model has been constructed in MySQL workbench. The ER model shows all the tables relevant to the proposed Smart Tool. A wireframe model is constructed with use of the program Balsamiq. A wireframe is chosen in this stage of the design because it does not distract users with commenting on stylistic issues (i.e. colour schemes or transitions). Balsamiq allows users to interact with the screens, allowing them to get an idea of the workflow and how to navigate the mobile application.It was made clear that using Preference function modelling is not designed for users on this scale but rather in making complex decisions and by generating alternatives. The purest form of the method is not desired from a user perspective as it was shown users need considerable (mental) effort to determine their preference values. However, if these values only need to be input once the strain on the user is significantly reduced and acceptable. Users clearly showed that once they became familiar with the system they were able to more easily adapt their preferences. This indicates that there is a level of intuitiveness in the use of the smart tool.ConclusionIt can be argued that hypothesis is confirmed and that the described problem can be solved by providing information about study spaces with the use of smart tools. The findings from the interviews suggest that the proposed smart tool can potentially add much value for both the user and campus management. The users generally reacted very positive to the concept of the smart tool. This shows that the smart tool will have significant value in supporting study space findability when executed correctly. To achieve this, usability of the smart tool is crucial for ultimate use. As this research comprises a design problem, it is important to realize that design problems can be solved in numerous ways, each leading to various results. Therefore, this can be seen as one of the possible ways a smart tool is able to support users in finding a suitable study space. 

Smart Real Estate Management
Smart Buildings
Smart tools
Real Estate Management
Campus management
Study Space

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Student theses

master thesis

© 2018 Sven ter Veer