UKZN Westville students’ use of on-campus Wi-Fi and their perceptions of quality of service.
| dc.contributor.advisor | Price, Catherine Susan. | |
| dc.contributor.author | Mbonye, Vicent. | |
| dc.date.accessioned | 2020-03-30T14:24:11Z | |
| dc.date.available | 2020-03-30T14:24:11Z | |
| dc.date.created | 2019 | |
| dc.date.issued | 2019 | |
| dc.description | Masters Degree. University of KwaZulu-Natal, Durban. | en_US |
| dc.description.abstract | As Higher Learning Institutions set up Wi-Fi infrastructure in different locations on-campus, they need to provide high quality services to support students’ learning. However, there has been little effort to ascertain how students use Wi-Fi on-campus, and how they perceive the quality of Wi-Fi in specific campus locations. Most research provides general information which makes it hard for Wi-Fi implementers to pinpoint the exact locations where services may need to be improved. This study follows a mixed method approach to present quantitative results from a representative sample of 373 students on UKZN Westville campus to understand how they use of Wi-Fi and their perceptions of service quality in different locations on-campus. It also presents qualitative information from interviews with two ICS administrators to understand Wi-Fi deployment strategies adopted on-campus and what Wi-Fi related problems students report. The most-used Wi-Fi locations were the on-campus residences (29.2%), the library (24.1%), computer LANs (17.4%) and lecture venues (17.2%). The worst Wi-Fi quality was reported in the Cafeteria (36.3%), the library (20.6%), and the Quad (15.4%). The best Wi-Fi quality was found in the computer LANs (34.2%), lecture venues (21.8%) and on-campus residences (11.8%). The Wi-Fi usage patterns are described according to the students’ accommodation type, as these patterns are very different. Best and worst times for using Wi-Fi in various locations is also given. The study showed that while students used various Wi-Fi devices to access Wi-Fi services on campus, the majority of them did not know the Wi-Fi standards, memory and speeds supported by their devices. When students faced difficulties, they stopped using Wi-Fi (38.6%), changed location (25.4%) or changed position in the same location (14.9%). Very few (8.6%) reported it to ICS. 86.3% did not know how to log a call with ICS. On-campus residence students reported Wi-Fi difficulties the most to ICS and they experienced the least difficulties in their residences. This shows that the ICS training for these students has paid off. The study bases its conceptual framework on the Brady & Cronin Jr. (2001) service quality model, which includes factors of outcome quality, physical environment quality and interaction quality. Outcome quality was used to understand students’ perception of the stability, availability reliability and timeliness of Wi-Fi services. Physical environment quality was used to understand the ambient conditions, social factors and design of the locations in which Wi-Fi is used. Interaction quality was used to understand the students’ perceptions of the behaviour, attitude and expertise quality of their interactions with ICS administrators. Overall, students rated the perceived Wi-Fi quality at just over 4.5 on a 7 point Likert scale. While this is greater than neutral, it can be improved. In a regression analysis of the constructs as a whole, the constructs account for 59.5% (R2 = .595) of the variance of service quality, F (3, 369) = 180.527, p<.0005. Outcome quality (β=.667, p<.0005), and interaction quality (β=.402, p=<.0005) are both significant predictors of service quality. However, physical environment quality is not. When regression models were generated for individual locations, for the most part, the R2 value improved. This study can be used by ICS to improve the Wi-Fi quality of service on campus, especially in areas where students use it the most, like in the library. ICS can also improve awareness of call logging amongst students, and how their choice of devices could affect their perceived Wi-Fi quality. The model could be used iteratively in future to test and monitor the quality of Wi-Fi services on campus, as well as in other environments, e.g. hospitals, hotels and airports. | en_US |
| dc.identifier.uri | https://researchspace.ukzn.ac.za/handle/10413/17220 | |
| dc.language.iso | en | en_US |
| dc.subject.other | Wi-Fi devices. | en_US |
| dc.subject.other | Elements of communication on a Wi-Fi network. | en_US |
| dc.subject.other | Implementing Wi-Fi access points. | en_US |
| dc.subject.other | The Wi-Fi electromagnetic spectrum. | en_US |
| dc.title | UKZN Westville students’ use of on-campus Wi-Fi and their perceptions of quality of service. | en_US |
| dc.type | Thesis | en_US |