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.

Representation and learning of visual information for pose recognition

Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.

ALEX:mobile language assistant for low-literacy adults

Basic literacy skills are fundamental building blocks of education, yet for a very large number of adults tasks such as understanding and using everyday items is a challenge. While research, industry, and policy-making is looking at improving access to textual information for low-literacy adults, the literacy-based demands of today's society are continually increasing. Although many community-based organizations offer resources and support to adults with limited literacy skills, current programs have difficulties reaching and retaining those that would benefit most from them. To address these challenges, the National Research Council of Canada is proposing a technological solution to support literacy programs and to assist low-literacy adults in today's information-centric society: ALEX© – Adult Literacy support application for EXperiential learning. ALEX© has been created together with low-literacy adults, following guidelines for inclusive design of mobile assistive tools. It is a mobile language assistant that is designed to be used both in the classroom and in daily life, in order to help low-literacy adults become increasingly literate and independent.

InfoStation-based Adaptable Provision of m Learning Services: Main Scenarios

This paper presents an adaptable InfoStation-based multi-agent system facilitating the mobile eLearning (mLearning) service provision within a University Campus. A horizontal view of the network architecture is presented. Main communications scenarios are considered by describing the detailed interaction of the system entities involved in the mLearning service provision. The mTest service is explored as a practical example. System implementation approaches are also considered.

A quiz-based game for addressing growing population issues:linking learning mechanics to the GROWTH serious game

This paper discusses the integration of quiz mechanism into digital game-based learning platform addressing environmental and social issues caused by population growth. 50 participants' learning outcomes were compared before and after the session. Semi-structured interview was used to gather participants' viewpoints regarding of issues presented in the game. Phenomenography was used as a methodology for data collection and analysis. Preliminary outcomes have shown that the current game implementation and quiz mechanism can be used to: (1) promote learning and awareness on environmental and social issues and (2) sustain players' attention and engagements.

Technology-Enhanced Learning: Review and Prospects

This paper is a reflection on the history and future of technology-enhanced learning. Over the last century various new technologies were introduced in education. Often, educational revolutions were proclaimed. Unfortunately, most of these new technologies failed to meet the high expectations. This paper reviews the rise and fall of various "revolutionary" learning technologies and analyses what went wrong. Three main driving factors are identified that influence the educational system: 1) educational practice, 2) educational research, and 3) educational technology. The role and position of these factors is elaborated and critically reviewed. Today, again many promising new technologies are being put in place for learning: gaming, social web, and mobile technologies, for example. Inevitably, these are once again proclaimed by its supporters to revolutionise teaching and learning. The paper concludes with identifying a number of relevant factors that substantiate a favourable future outlook of technology-enhanced learning.

Extending the GUIDE@HAND Tourist Guide Application with QR Codes for Museum Learning

The following paper attempts to encompass the opportunities for applying QR codes for museums and exhibits through the example of the Hungarian Museum of Environmental Protection and Water Management (Esztergom, Hungary). Besides providing interactivity in the museum for the mobile phone generation through the utilization of a device and a method that they are familiar with, it is important to explain how and why it is worthwhile to “adorn” the exhibits with these codes. In this paper we also touch upon the technical issues of how an existing mobile phone application can be incorporated into and used for the presentation of the museum.

Mobile Exploring of the Bulgarian Iconography through QR Codes in the GUIDE@HAND Tourist Guide Application

The following paper presents an application of QR code marking of digital iconographical collections for their outdoor mobile access and exploring through the GUIDE@HAND audio tourist guide.

A Bayesian Model for Learning Using Flashcards

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015

My Personal Trainer: applicazione di e-learning per il fitness su piattaforma Android

L’obiettivo della tesi è quello di mettere in pratica e approfondire le conoscenze acquisite durante il percorso universitario, al fine di avvicinarsi a quello che sarà poi il mondo del lavoro. Questa motivazione e la voglia di realizzare qualcosa di concreto hanno portato alla scelta di sviluppare un’applicazione per sistemi mobile, in questo modo è stato necessario affrontare le varie fasi di sviluppo di un software che comprendono in particolare la progettazione e l’implementazione. All'interno della tesi si darà uno sguardo al contesto in cui l’applicazione MyPersonalTrainer vuole andarsi ad inserire, si procederà con la descrizione della fase di progettazione che comprende l'analisi dei requisiti, poi si analizzerà la fase di implementazione e infine verranno effettuate delle considerazioni sui possibili sviluppi futuri.

The state of the nations:current and future developments in technology enhanced learning

Right across Europe technology is playing a vital part in enhancing learning for an increasingly diverse population of learners. Learning is increasingly flexible, social and mobile and supported by high quality multi-media resources. Institutional VLEs are seeing a shift towards open source products and these core systems are supplemented by a range of social and collaborative learning tools based on web 2.0 technologies. Learners undertaking field studies and those in the workplace are coming to expect that these off-campus experiences will also be technology-rich whether supported by institutional or user-owned devices. As well as keeping European businesses competitive, learning is seen as a means of increasing social mobility and supporting an agenda of social justice. For a number of years the EUNIS E-Learning Task Force (ELTF) has conducted snapshot surveys of e-learning across member institutions, collected case studies of good practice in e-learning see (Hayes, et al., 2009) in references, supported a group looking at the future of e-learning, and showcased the best of innovation in its e-learning Award. Now for the first time the ELTF membership has come together to undertake an analysis of developments in the member states and to assess what this might mean for the future. The group applied the techniques of World Café conversation and Scenario Thinking to develop its thoughts. The analysis is unashamedly qualitative and draws on expertise from leading universities across eight of the EUNIS member states. What emerges is interesting in terms of the common trends in developments in all of the nations and similarities in hopes and concerns about the future development of learning.

Learning and Exploiting Camera Geometry for Computer Vision

This work explores the use of statistical methods in describing and estimating camera poses, as well as the information feedback loop between camera pose and object detection. Surging development in robotics and computer vision has pushed the need for algorithms that infer, understand, and utilize information about the position and orientation of the sensor platforms when observing and/or interacting with their environment.

The first contribution of this thesis is the development of a set of statistical tools for representing and estimating the uncertainty in object poses. A distribution for representing the joint uncertainty over multiple object positions and orientations is described, called the mirrored normal-Bingham distribution. This distribution generalizes both the normal distribution in Euclidean space, and the Bingham distribution on the unit hypersphere. It is shown to inherit many of the convenient properties of these special cases: it is the maximum-entropy distribution with fixed second moment, and there is a generalized Laplace approximation whose result is the mirrored normal-Bingham distribution. This distribution and approximation method are demonstrated by deriving the analytical approximation to the wrapped-normal distribution. Further, it is shown how these tools can be used to represent the uncertainty in the result of a bundle adjustment problem.

Another application of these methods is illustrated as part of a novel camera pose estimation algorithm based on object detections. The autocalibration task is formulated as a bundle adjustment problem using prior distributions over the 3D points to enforce the objects' structure and their relationship with the scene geometry. This framework is very flexible and enables the use of off-the-shelf computational tools to solve specialized autocalibration problems. Its performance is evaluated using a pedestrian detector to provide head and foot location observations, and it proves much faster and potentially more accurate than existing methods.

Finally, the information feedback loop between object detection and camera pose estimation is closed by utilizing camera pose information to improve object detection in scenarios with significant perspective warping. Methods are presented that allow the inverse perspective mapping traditionally applied to images to be applied instead to features computed from those images. For the special case of HOG-like features, which are used by many modern object detection systems, these methods are shown to provide substantial performance benefits over unadapted detectors while achieving real-time frame rates, orders of magnitude faster than comparable image warping methods.

The statistical tools and algorithms presented here are especially promising for mobile cameras, providing the ability to autocalibrate and adapt to the camera pose in real time. In addition, these methods have wide-ranging potential applications in diverse areas of computer vision, robotics, and imaging.

Next generation e-learning platform: virtual laboratory simulations

Bioscience subjects require a significant amount of training in laboratory techniques to produce highly skilled science graduates. Many techniques which are currently used in diagnostic, research and industrial laboratories require expensive equipment for single users; examples of which include next generation sequencing, quantitative PCR, mass spectrometry and other analytical techniques. The cost of the machines, reagents and limited access frequently preclude undergraduate students from using such cutting edge techniques. In addition to cost and availability, the time taken for analytical runs on equipment such as High Performance Liquid Chromatography (HPLC) does not necessarily fit with the limitations of timetabling. Understanding the theory underlying these techniques without the accompanying practical classes can be unexciting for students. One alternative from wet laboratory provision is to use virtual simulations of such practical which enable students to see the machines and interact with them to generate data. The Faculty of Science and Technology at the University of Westminster has provided all second and third year undergraduate students with iPads so that these students all have access to a mobile device to assist with learning. We have purchased licences from Labster to access a range of virtual laboratory simulations. These virtual laboratories are fully equipped and require student responses to multiple answer questions in order to progress through the experiment. In a pilot study to look at the feasibility of the Labster virtual laboratory simulations with the iPad devices; second year Biological Science students (n=36) worked through the Labster HPLC simulation on iPads. The virtual HPLC simulation enabled students to optimise the conditions for the separation of drugs. Answers to Multiple choice questions were necessary to progress through the simulation, these focussed on the underlying principles of the HPLC technique. Following the virtual laboratory simulation students went to a real HPLC in the analytical suite in order to separate of asprin, caffeine and paracetamol. In a survey 100% of students (n=36) in this cohort agreed that the Labster virtual simulation had helped them to understand HPLC. In free text responses one student commented that "The terminology is very clear and I enjoyed using Labster very much”. One member of staff commented that “there was a very good knowledge interaction with the virtual practical”.

A Proposed Framework for Simulation Based Learning of Inheritance

Different types of serious games have been used in elucidating computer science areas such as computer games, mobile games, Lego-based games, virtual worlds and webbased games. Different evaluation techniques have been conducted like questionnaires, interviews, discussions and tests. Simulation have been widely used in computer science as a motivational and interactive learning tool. This paper aims to evaluate the possibility of successful implementation of simulation in computer programming modules. A framework is proposed to measure the impact of serious games on enhancing students understanding of key computer science concepts. Experiments will be held on the EEECS of Queen’s University Belfast students to test the framework and attain results.

The Impact of Student Response Systems on the Learning Experience of Undergraduate Psychology Students

Student response systems (SRS) are hand-held devices or mobile phone polling systems which collate real-time, individual responses to on-screen questions. Previous research examining their role in higher education has highlighted both advantages and disadvantages of their use. This paper explores how different SRS influence the learning experience of psychology students across different levels of their programme. Across two studies, first year students’ experience of using Turningpoint clickers and second year students’ experience of using Poll Everywhere was investigated. Evaluations of both studies revealed that SRS has a number of positive impacts on learning, including enhanced engagement, active learning, peer interaction, and formative feedback. Technical and practical issues emerged as consistent barriers to the use of SRS. Discussion of these findings and the authors’ collective experiences of these technologies are used to provide insight into the way in which SRS can be effectively integrated within undergraduate psychology programmes.