Mining mobile apps reviews to support release planning

The mobile apps market is a tremendous success, with millions of apps downloaded and used every day by users spread all around the world. For apps’ developers, having their apps published on one of the major app stores (e.g. Google Play market) is just the beginning of the apps lifecycle. Indeed, in order to successfully compete with the other apps in the market, an app has to be updated frequently by adding new attractive features and by fixing existing bugs. Clearly, any developer interested in increasing the success of her app should try to implement features desired by the app’s users and to fix bugs affecting the user experience of many of them. A precious source of information to decide how to collect users’ opinions and wishes is represented by the reviews left by users on the store from which they downloaded the app. However, to exploit such information the app’s developer should manually read each user review and verify if it contains useful information (e.g. suggestions for new features). This is something not doable if the app receives hundreds of reviews per day, as happens for the very popular apps on the market. In this work, our aim is to provide support to mobile apps developers by proposing a novel approach exploiting data mining, natural language processing, machine learning, and clustering techniques in order to classify the user reviews on the basis of the information they contain (e.g. useless, suggestion for new features, bugs reporting). Such an approach has been empirically evaluated and made available in a web-­‐based tool publicly available to all apps’ developers. The achieved results showed that the developed tool: (i) is able to correctly categorise user reviews on the basis of their content (e.g. isolating those reporting bugs) with 78% of accuracy, (ii) produces clusters of reviews (e.g. groups together reviews indicating exactly the same bug to be fixed) that are meaningful from a developer’s point-­‐of-­‐view, and (iii) is considered useful by a software company working in the mobile apps’ development market.

La evaluación continua en la docencia del urbanismo: experiencia aplicada a través de Google Apps

El sistema tradicional de evaluación continua implica asumir, en muchas ocasiones, algunas dificultades en cuanto al seguimiento y valoración del trabajo del alumnado. La existencia de grupos numerosos y la necesidad de agilizar la comunicación profesor-alumno y entre alumnos, nos lleva a investigar las posibilidades que ofrecen las nuevas tecnologías con el fin de actualizar los métodos de aprendizaje y facilitar la valoración del trabajo de los alumnos dentro y fuera del aula. La presente experiencia docente se centra en estudiar las posibilidades que ofrece Google, a través de distintas aplicaciones web o Apps -Groups, Forms, Drive, Mail y Calendar- e incorporarlas como herramientas integradas en el trabajo del aula. Concretamente, se aplica simultáneamente esta metodología a dos asignaturas diferentes del área de Urbanística y Ordenación del Territorio -Urbanismo 2 y Urbanismo 4- en las que se integra al alumnado en un grupo virtual a través del cual, se realizan distintas actividades -resolución de dudas, intercambio de información, exámenes, etc.- que permiten al profesor gestionar y evaluar, de forma eficiente, cuestiones como la asistencia y la participación en la asignatura conociendo de forma inmediata la respuesta de los estudiantes ante los conceptos trabajados.

Participatory design with older adults for healthcare apps

The global population of people aged 60 years and older is growing rapidly [1]. Ongoing advances in mobile technologies have the potential to improve independence and quality of life of older adults by supporting the delivery of personalised and ubiquitous healthcare solutions. Suggested healthcare reforms reflect the need for a future model of healthcare delivery wherein older adults take more responsibility for their own healthcare in their own homes in an attempt to moderate healthcare costs without impairing healthcare quality. For such a paradigm shift to be realised, the supporting technology must address the needs of older patients efficiently and effectively to ensure technology acceptance and use. We argue this is not possible without employing participatory approaches for the informed and effective design and development of such technologies and outline recommendations for engaging in participatory design with older adults with impairments based on practical experience.

Towards a threat assessment framework for apps collusion

App collusion refers to two or more apps working together to achieve a malicious goal that they otherwise would not be able to achieve individually. The permissions based security model (PBSM) for Android does not address this threat, as it is rather limited to mitigating risks due to individual apps. This paper presents a technique for assessing the threat of collusion for apps, which is a first step towards quantifying collusion risk, and allows us to narrow down to candidate apps for collusion, which is critical given the high volume of Android apps available. We present our empirical analysis using a classified corpus of over 29000 Android apps provided by Intel Security.

Threats and thrills : pregnancy apps, risk and consumption

„Lernen durch Lehren“ in der Mathematik – Videotutorials und Apps im Praxistest

Das Fach Mathematik stellt Lehrende in vielfältiger Weise vor Herausforderungen: Die Inhalte fallen den meisten Studierenden schwer, die verschiedenen Lerntypen machen sich besonders deutlich bemerkbar und konventionelle Lehrmethoden erfordern hohe Selbstdisziplin, weil der Stoff hier kontinuierlich nachgearbeitet werden muss. Dies äußert sich in hohen Durchfall- und Abbruchquoten in einem Studienfach, das ausgezeichnete Arbeitsplatzchancen in Aussicht stellt und dessen Absolventen in der Wirtschaft und Industrie stark nachgefragt sind. Eine Überlegung, wie dieser Herausforderung zukünftig begegnet werden kann, besteht darin, Studierende mit Hilfe entsprechender Anreize mehr in die Lehrveranstaltungen einzubinden und auf diesem Weg eine tiefergehende Beschäftigung mit den Inhalten zu unterstützen. Dabei soll eine aktive und gleichzeitig im Semesterverlauf kontinuierliche Auseinandersetzung mit den mathematischen Inhalten angeregt und gefördert werden. In diesem Beitrag werden zwei Ideen vorgestellt, die sich an der didaktischen Methode „Lernen durch Lehren“ (LdL) orientieren und die eine Aktivierung sowie eine stärkere thematische Einbindung der Studierenden zum Ziel haben. (DIPF/Orig.)

Apps for IMproving FITness and increasing physical activity among young people: the AIMFIT pragmatic randomized controlled trial

BACKGROUND: Given the global prevalence of insufficient physical activity (PA), effective interventions that attenuate age-related decline in PA levels are needed. Mobile phone interventions that positively affect health (mHealth) show promise; however, their impact on PA levels and fitness in young people is unclear and little is known about what makes a good mHealth app. OBJECTIVE: The aim was to determine the effects of two commercially available smartphone apps (Zombies, Run and Get Running) on cardiorespiratory fitness and PA levels in insufficiently active healthy young people. A second aim was to identify the features of the app design that may contribute to improved fitness and PA levels. METHODS: Apps for IMproving FITness (AIMFIT) was a 3-arm, parallel, randomized controlled trial conducted in Auckland, New Zealand. Participants were recruited through advertisements in electronic mailing lists, local newspapers, flyers posted in community locations, and presentations at schools. Eligible young people aged 14-17 years were allocated at random to 1 of 3 conditions: (1) use of an immersive app (Zombies, Run), (2) use of a nonimmersive app (Get Running), or (3) usual behavior (control). Both smartphone apps consisted of a fully automated 8-week training program designed to improve fitness and ability to run 5 km; however, the immersive app featured a game-themed design and narrative. Intention-to-treat analysis was performed using data collected face-to-face at baseline and 8 weeks, and all regression models were adjusted for baseline outcome value and gender. The primary outcome was cardiorespiratory fitness, objectively assessed as time to complete the 1-mile run/walk test at 8 weeks. Secondary outcomes were PA levels (accelerometry and self-reported), enjoyment, psychological need satisfaction, self-efficacy, and acceptability and usability of the apps. RESULTS: A total of 51 participants were randomized to the immersive app intervention (n=17), nonimmersive app intervention (n=16), or the control group (n=18). The mean age of participants was 15.7 (SD 1.2) years; participants were mostly NZ Europeans (61%, 31/51) and 57% (29/51) were female. Overall retention rate was 96% (49/51). There was no significant intervention effect on the primary outcome using either of the apps. Compared to the control, time to complete the fitness test was -28.4 seconds shorter (95% CI -66.5 to 9.82, P=.20) for the immersive app group and -24.7 seconds (95% CI -63.5 to 14.2, P=.32) for the nonimmersive app group. No significant intervention effects were found for secondary outcomes. CONCLUSIONS: Although apps have the ability to increase reach at a low cost, our pragmatic approach using readily available commercial apps as a stand-alone instrument did not have a significant effect on fitness. However, interest in future use of PA apps is promising and highlights a potentially important role of these tools in a multifaceted approach to increase fitness, promote PA, and consequently reduce the adverse health outcomes associated with insufficient activity.