Using mobile devices to enhance undergraduate field research

Mobile devices can enhance undergraduate research projects and students’ research capabilities. The use of mobile devices such as tablet computers will not automatically make undergraduates better researchers, but their use should make investigations, writing, and publishing more effective and may even save students time. We have explored some of the possibilities of using “tablets” and “smartphones” to aid the research and inquiry process in geography and bioscience fieldwork. We provide two case studies as illustration of how students working in small research groups use mobile devices to gather and analyze primary data in field-based inquiry. Since April 2010, Apple’s iPad has changed the way people behave in the digital world and how they access their music, watch videos, or read their email much as the entrepreneurs Steve Jobs and Jonathan Ive intended. Now with “apps” and “the cloud” and the ubiquitous references to them appearing in the press and on TV, academics’ use of tablets is also having an impact on education and research. In our discussion we will refer to use of smartphones such as the iPhone, iPod, and Android devices under the term “tablet”. Android and Microsoft devices may not offer the same facilities as the iPad/iphone, but many app producers now provide versions for several operating systems. Smartphones are becoming more affordable and ubiquitous (Melhuish and Falloon 2010), but a recent study of undergraduate students (Woodcock et al. 2012, 1) found that many students who own smartphones are “largely unaware of their potential to support learning”. Importantly, however, students were found to be “interested in and open to the potential as they become familiar with the possibilities” (Woodcock et al. 2012). Smartphones and iPads could be better utilized than laptops when conducting research in the field because of their portability (Welsh and France 2012). It is imperative for faculty to provide their students with opportunities to discover and employ the potential uses of mobile devices in their learning. However, it is not only the convenience of the iPad or tablet devices or smartphones we wish to promote, but also a way of thinking and behaving digitally. We essentially suggest that making a tablet the center of research increases the connections between related research activities.

Student perceptions of iPads as mobile learning devices for fieldwork

This paper reports findings from six field courses about student’s perceptions of iPads as mobile learning devices for fieldwork. Data were collected through surveys and focus groups. The key findings suggest that the multi-tool nature of the iPads and their portability were the main strengths. Students had some concerns over the safety of the iPads in adverse weather and rugged environments, though most of these concerns were eliminated after using the devices with protective cases. Reduced connectivity was found to be one of the main challenges for mobile learning. Finally, students and practitioners views of why they used the mobile devices for fieldwork did not align.

Next generation mobile marketing: how young consumers react to Bluetooth-enabled advertising

Mobile devices are attractive media for directly communicating with consumers who have become busier and more difficult to reach. While SMS (short message service) advertising has received some attention in the literature, Bluetooth-enabled advertising is still unexplored. This research aims to investigate younger consumers’ acceptance of Bluetooth-delivered advertising. Although the majority of the respondents were willing to accept this form of advertising, they needed both to be in control of the frequency with which they receive messages and also to be reassured that the medium could ensure privacy and security. The research further indicated that peers influence the acceptance of Bluetooth-driven advertising.

Pocket data mining: towards collaborative data mining in mobile computing environments

Pocket Data Mining (PDM) is our new term describing collaborative mining of streaming data in mobile and distributed computing environments. With sheer amounts of data streams are now available for subscription on our smart mobile phones, the potential of using this data for decision making using data stream mining techniques has now been achievable owing to the increasing power of these handheld devices. Wireless communication among these devices using Bluetooth and WiFi technologies has opened the door wide for collaborative mining among the mobile devices within the same range that are running data mining techniques targeting the same application. This paper proposes a new architecture that we have prototyped for realizing the significant applications in this area. We have proposed using mobile software agents in this application for several reasons. Most importantly the autonomic intelligent behaviour of the agent technology has been the driving force for using it in this application. Other efficiency reasons are discussed in details in this paper. Experimental results showing the feasibility of the proposed architecture are presented and discussed.

Behavioral economics, wearable devices, and cooperative games: results from a population-based intervention to increase physical activity

Background: Health care literature supports the development of accessible interventions that integrate behavioral economics, wearable devices, principles of evidence-based behavior change, and community support. However, there are limited real-world examples of large scale, population-based, member-driven reward platforms. Subsequently, a paucity of outcome data exists and health economic effects remain largely theoretical. To complicate matters, an emerging area of research is defining the role of Superusers, the small percentage of unusually engaged digital health participants who may influence other members. Objective: The objective of this preliminary study is to analyze descriptive data from GOODcoins, a self-guided, free-to-consumer engagement and rewards platform incentivizing walking, running and cycling. Registered members accessed the GOODcoins platform through PCs, tablets or mobile devices, and had the opportunity to sync wearables to track activity. Following registration, members were encouraged to join gamified group challenges and compare their progress with that of others. As members met challenge targets, they were rewarded with GOODcoins, which could be redeemed for planet- or people-friendly products. Methods: Outcome data were obtained from the GOODcoins custom SQL database. The reporting period was December 1, 2014 to May 1, 2015. Descriptive self-report data were analyzed using MySQL and MS Excel. Results: The study period includes data from 1298 users who were connected to an exercise tracking device. Females consisted of 52.6% (n=683) of the study population, 33.7% (n=438) were between the ages of 20-29, and 24.8% (n=322) were between the ages of 30-39. 77.5% (n=1006) of connected and active members met daily-recommended physical activity guidelines of 30 minutes, with a total daily average activity of 107 minutes (95% CI 90, 124). Of all connected and active users, 96.1% (n=1248) listed walking as their primary activity. For members who exchanged GOODcoins, the mean balance was 4,000 (95% CI 3850, 4150) at time of redemption, and 50.4% (n=61) of exchanges were for fitness or outdoor products, while 4.1% (n=5) were for food-related items. Participants were most likely to complete challenges when rewards were between 201-300 GOODcoins. Conclusions: The purpose of this study is to form a baseline for future research. Overall, results indicate that challenges and incentives may be effective for connected and active members, and may play a role in achieving daily-recommended activity guidelines. Registrants were typically younger, walking was the primary activity, and rewards were mainly exchanged for fitness or outdoor products. Remaining to be determined is whether members were already physically active at time of registration and are representative of healthy adherers, or were previously inactive and were incentivized to change their behavior. As challenges are gamified, there is an opportunity to investigate the role of superusers and healthy adherers, impacts on behavioral norms, and how cooperative games and incentives can be leveraged across stratified populations. Study limitations and future research agendas are discussed.

Ability of students to recognize the relationship between using mobile apps for learning during fieldwork and the development of graduate attributes

The increasing importance of employability in Higher Education curricula and the prevalence of using mobile devices for fieldbased learning prompted an investigation into student awareness of the relationship between the use of mobile apps for learning and the development of graduate attributes (GAs) (and the link to employability). The results from post-fieldwork focus groups from four field courses indicated that students could make clear links between the use of a variety of mobile apps and graduate attribute development. The study suggests a number of mobile apps can align simultaneously with more than one graduate attribute. Furthermore, prior experience and the context of use can influence students’ perceptions of an app and its link with different GAs.

Quality time [QoS in 802.11e]

Wireless local area networks (WLANs) based on the IEEE 802.11 standard are now widespread. Most are used to provide access for mobile devices to a conventional wired infrastructure, and some are used where wires are not possible, forming an ad hoc network of their own. There are several varieties at the physical or radio layer (802.11, 802.11a, 802.11b, 802.11g), with each featuring different data rates, modulation schemes and transmission frequencies. However, all of them share a common medium access control (MAC) layer. As this is largely based on a contention approach, it does not allow prioritising of traffic or stations, so it cannot easily provide the quality of service (QoS) required by time-sensitive applications, such as voice or video transmission. In order to address this shortfall of the technology, the IEEE set up a task group that is aiming to enhance the MAC layer protocol so that it can provide QoS. The latest draft at the time of writing is Draft 11, dated October 2004. The article describes the yet-to-be-ratified 802.11e standard and is based on that draft.

An introduction to television studies. 3rd edition.

This is a comprehensive textbook for students of Television Studies, now updated for its third edition. The book provides students with a framework for understanding the key concepts and main approaches to Television Studies, including audience research, television history and broadcasting policy, and the analytical study of individual programmes. The book includes a glossary of key terms used in the television industry and in the academic study of television, there are suggestions for further reading at the end of each chapter, and chapters include suggested activities for use in class or as assignments. The case studies in the book include analysis of advertisements, approaches to news reporting, television scheduling, and challenges to television in new contexts of viewing on computers and mobile devices. The topics of individual chapters are: studying television, television histories, television cultures, television texts and narratives, television genres and formats, television production, television quality and value, television realities and representation, television censorship and regulation, television audiences, and the likely future for television.

Distributed hoeffding trees for pocket data mining

Collaborative mining of distributed data streams in a mobile computing environment is referred to as Pocket Data Mining PDM. Hoeffding trees techniques have been experimentally and analytically validated for data stream classification. In this paper, we have proposed, developed and evaluated the adoption of distributed Hoeffding trees for classifying streaming data in PDM applications. We have identified a realistic scenario in which different users equipped with smart mobile devices run a local Hoeffding tree classifier on a subset of the attributes. Thus, we have investigated the mining of vertically partitioned datasets with possible overlap of attributes, which is the more likely case. Our experimental results have validated the efficiency of our proposed model achieving promising accuracy for real deployment.

Homogeneous and heterogeneous distributed classification for pocket data mining

Pocket Data Mining (PDM) describes the full process of analysing data streams in mobile ad hoc distributed environments. Advances in mobile devices like smart phones and tablet computers have made it possible for a wide range of applications to run in such an environment. In this paper, we propose the adoption of data stream classification techniques for PDM. Evident by a thorough experimental study, it has been proved that running heterogeneous/different, or homogeneous/similar data stream classification techniques over vertically partitioned data (data partitioned according to the feature space) results in comparable performance to batch and centralised learning techniques.

An organisational semiotics inspired information architecture: pervasive healthcare as a case study

Information architecture (IA) is defined as high level information requirements of an organisation. It is applied in areas such as information systems development, enterprise architecture, business processes management and organisational change management. Still, the lack of methods and theories prevents information architecture becoming a distinct discipline. Healthcare organisation is always seen as information intensive organisation, moreover in a pervasive healthcare environment. Pervasive healthcare aims to provide healthcare services to anyone, anywhere and anytime by incorporating mobile devices and wireless network. Information architecture hence plays an important role in information provisioning within the context of pervasive healthcare in order to support decision making and communication between clinician and patients. Organisational semiotics is one of the social technical approaches that contemplate information through the norms or activities performed within an organisation prior to pervasive healthcare implementation. This paper proposes a conceptual design of information architecture for pervasive healthcare. It is illustrated with a scenario of mental health patient monitoring.

Market research and the ethics of big data

The term 'big data' has recently emerged to describe a range of technological and commercial trends enabling the storage and analysis of huge amounts of customer data, such as that generated by social networks and mobile devices. Much of the commercial promise of big data is in the ability to generate valuable insights from collecting new types and volumes of data in ways that were not previously economically viable. At the same time a number of questions have been raised about the implications for individual privacy. This paper explores key perspectives underlying the emergence of big data, and considers both the opportunities and ethical challenges raised for market research.

Big data architecture for pervasive healthcare: a literature review

Pervasive healthcare aims to deliver deinstitutionalised healthcare services to patients anytime and anywhere. Pervasive healthcare involves remote data collection through mobile devices and sensor network which the data is usually in large volume, varied formats and high frequency. The nature of big data such as volume, variety, velocity and veracity, together with its analytical capabilities com-plements the delivery of pervasive healthcare. However, there is limited research in intertwining these two domains. Most research focus mainly on the technical context of big data application in the healthcare sector. Little attention has been paid to a strategic role of big data which impacts the quality of healthcare services provision at the organisational level. Therefore, this paper delivers a conceptual view of big data architecture for pervasive healthcare via an intensive literature review to address the aforementioned research problems. This paper provides three major contributions: 1) identifies the research themes of big data and pervasive healthcare, 2) establishes the relationship between research themes, which later composes the big data architecture for pervasive healthcare, and 3) sheds a light on future research, such as semiosis and sense-making, and enables practitioners to implement big data in the pervasive healthcare through the proposed architecture.

Obstacle avoidance routing scheme through optimal sink movement for home monitoring and mobile robotic consumer devices

In recent years, ZigBee has been proven to be an excellent solution to create scalable and flexible home automation networks. In a home automation network, consumer devices typically collect data from a home monitoring environment and then transmit the data to an end user through multi-hop communication without the need for any human intervention. However, due to the presence of typical obstacles in a home environment, error-free reception may not be possible, particularly for power constrained devices. A mobile sink based data transmission scheme can be one solution but obstacles create significant complexities for the sink movement path determination process. Therefore, an obstacle avoidance data routing scheme is of vital importance to the design of an efficient home automation system. This paper presents a mobile sink based obstacle avoidance routing scheme for a home monitoring system. The mobile sink collects data by traversing through the obstacle avoidance path. Through ZigBee based hardware implementation and verification, the proposed scheme successfully transmits data through the obstacle avoidance path to improve network performance in terms of life span, energy consumption and reliability. The application of this work can be applied to a wide range of intelligent pervasive consumer products and services including robotic vacuum cleaners and personal security robots1.

Improving CS-4 user data rate in GPRS enabled devices by using a BLER co-processor

The General Packet Radio Service (GPRS) was developed to allow packet data to be transported efficiently over an existing circuit switched radio network. The main applications for GPRS are in transporting IP datagram’s from the user’s mobile Internet browser to and from the Internet, or in telemetry equipment. A simple Error Detection and Correction (EDC) scheme to improve the GPRS Block Error Rate (BLER) performance is presented, particularly for coding scheme 4 (CS-4), however gains in other coding schemes are seen. For every GPRS radio block that is corrected by the EDC scheme, the block does not need to be retransmitted releasing bandwidth in the channel, improving throughput and the user’s application data rate. As GPRS requires intensive processing in the baseband, a viable hardware solution for a GPRS BLER co-processor is discussed that has been currently implemented in a Field Programmable Gate Array (FPGA) and presented in this paper.