Understanding the WiFi usage of university students

In this work, we analyze the use of a WiFi network deployed in a large-scale technical university. To this extent, we leverage three weeks of WiFi traffic data logs and characterize the spatio-temporal correlation of the traffic at different granularities (each individual access point, groups of access points, entire network). The spatial correlation of traffic across nearby access points is also assessed. Then, we search for distinctive fingerprints left on the WiFi traffic by different situations/conditions; namely, we answer the following questions: Do students attending a lecture use the wireless network in a different way than students not attending a lecture?, and Is there any difference in the usage of the wireless network during architecture or engineering classes? A supervised learning approach based on Quadratic Discriminant Analysis (QDA) is used to classify empty vs. occupied rooms and engineering vs. architecture lectures using only WiFi traffic logs with promising results

Navigating MazeMap: indoor human mobility, spatio-logical ties and future potential

Global navigation systems and location-based services have found their way into our daily lives. Recently, indoor positioning techniques have also been proposed, and there are several live or trial systems already operating. In this paper, we present insights from MazeMap, the first live indoor/outdoor positioning and navigation system deployed at a large university campus in Norway. Our main contribution is a measurement case study; we show the spatial and temporal distribution of MazeMap geo-location and wayfinding requests, construct the aggregated human mobility map of the campus and find strong logical ties between different locations. On one hand, our findings are specific to the venue; on the other hand, the nature of available data and insights coupled with our discussion on potential usage scenarios for indoor positioning and location-based services predict a successful future for these systems and applications.Comment: 6 pages, accepted at PerMoby Workshop at IEEE PerCom 201

Report on the Evaluation of EVS Usage and Trends at the University of Hertfordshire : February to June 2014

The Electronic Voting Systems (EVS) evaluation project for iTEAM has investigated the current level of engagement in the use of EVS across the institution in 2014. It has built on the work and outputs of the JISC supported Evaluating Electronic Voting Systems (EEVS) project in 2011-12 and the work of the iTEAM project through 2011-2013. It offers an up-to-date examination of the trends in EVS adoption and the breadth and nature of EVS use across the different academic schools. The project adopted a mixed-methods approach to evaluate usage and engagement. The starting point was a desk study to examine the existing data on numbers of EVS handsets purchased by academic schools in 2011, 2012 and 2013 and registered across the University and to explore the details from the School reports previously submitted to iTEAM. Sources of data included Information Hertfordshire and the iTEAM archive. Quantitative surveys were drawn up and information requests for student numbers were made to Senior Administrative Managers (SAM). A series of interviews were held with School-based academics including EVS Champions and Associate Deans for Learning and Teaching. Three purchasing trends for EVS handsets by different Schools were found:- slow decrease in HUM, LAW and PAM, moderate increase in BS, EDU and HSK and rapid increase in CS, ET and LMS. In terms of levels of EVS usage in 2013 -14 four different patterns emerged among the schools. These showed: slow increase (CS, LMS and PAM), slow decrease (BS, ET, EDU and HUM), rapid decrease (LAW) and no change (CA and HSK). The EVS purchasing and usage trends comply with the figures given by Rogers for his technology adoption model. Some schools are characterised by successful ongoing EVS use over several years while other school strategies for EVS, which had showed promise early on, have faltered in their use. There was some evidence that academics in STEMM subjects are more likely to engage willingly with EVS use where larger groups are taught, but this is not yet in evidence across all the STEMM groups at this university. Furthermore good practice exists and flourishes across non-STEMM subjects as well. The strategies for successful School-based EVS embedding and continued use include the following three hallmarks:- •Top-down management support for purchasing of handsets and including training for academics and administrators, and alignment with the School teaching and learning strategy. •The existence of a core of innovators and early adopters of technology including the local EVS champions, who are willing to actively engage with their fellow colleagues in sharing the potential of EVS technology. •An engagement with the pedagogical implications for changing and developing practice that the greater use of formative or summative polling and questioning requires. The immediate future of classroom technologies such as EVS offers two main directions. Firstly, there is the continuation of adopting ‘institutionally provided’ handheld devices. This is a low-cost method that can be used easily and flexibly. The other options for classroom polling rely on sufficient wifi availability in the teaching rooms and/or mobile phone signal strength/network availability and capacity. It is anticipated that the capacity issue will present fewer barriers for adoption in future, and that the future of the classroom response systems is inevitably linked to the widespread use of mobile technologies by students

Analyzing the Impact of Covid-19 Control Policies on Campus Occupancy and Mobility via Passive WiFi Sensing

Mobile sensing has played a key role in providing digital solutions to aid with COVID-19 containment policies. These solutions include, among other efforts, enforcing social distancing and monitoring crowd movements in indoor spaces. However, such solutions may not be effective without mass adoption. As more and more countries reopen from lockdowns, there remains a pressing need to minimize crowd movements and interactions, particularly in enclosed spaces. This paper conjectures that analyzing user occupancy and mobility via deployed WiFi infrastructure can help institutions monitor and maintain safety compliance according to the public health guidelines. Using smartphones as a proxy for user location, our analysis demonstrates how coarse-grained WiFi data can sufficiently reflect indoor occupancy spectrum when different COVID-19 policies were enacted. Our work analyzes staff and students' mobility data from three different university campuses. Two of these campuses are in Singapore, and the third is in the Northeastern United States. Our results show that online learning, split-team, and other space management policies effectively lower occupancy. However, they do not change the mobility for individuals transitioning between spaces. We demonstrate how this data source can be put to practical application for institutional crowd control and discuss the implications of our findings for policy-making.Comment: 25 pages, 18 figure

To take or not to take the laptop or tablet to classes, that is the question

In recent decades, so-called mobile learning or m-learning has become a new paradigm in education as a consequence of technological advances and the widespread use of mobile devices to access information and for communication. In this context, this paper analyzes different profiles depending on students’ preferences for taking mobile devices (specifically tablets and/or laptops) to economics classes at the University of Seville (Spain). A survey-based field study of a sample of 412 students and the application of bivariate probit models show a low level of mobile device integration in teaching (devices taken to class by only 29.8% of respondents) with a slight predominance of laptops. The results also show differences between users of the two types of devices. Students who take their laptops to class usually live at home with their family, have already used them in pre-university levels, and are concerned about recharging their devices in class. However, although users who take their tablets to class also live with their parents, they are much more active on social network sites and more concerned about the quality of the internet connection. These findings enable the design of strategies to encourage students to attend class with their own mobile devices

Current and Potential Future use of Facilities on the Crichton Estate by Students Attending Academic Institutions located on, and adjacent to, it

No abstract available

Learning IoT without the "I" - Educational Internet of Things in a Developing Context

To provide better education to children from different socio-economic backgrounds, the Thai Government launched the "One Tablet PC Per Child" (OTPC) policy and distributed 800,000 tablet computers to first grade students across the country in 2012. This initiative is an opportunity to study how mobile learning and Internet of Things (IoT) technology can be designed for students in underprivileged areas of northern Thailand. In this position paper, we present a prototype, called OBSY (Observation Learning System) which targets primary science education. OBSY consists of i) a sensor device, developed with low-cost open source singled-board computer Raspberry Pi, housed in a 3D printed case, ii) a mobile device friendly graphical interface displaying visualisations of the sensor data, iii) a self-contained DIY Wi-Fi network which allows the system to operate in an environment with inadequate ICT infrastructure