A Model-Driven Framework for Enabling Flexible and Robust Mobile Data Collection Applications

In the light of the ubiquitous digital transformation, smart mobile technology has become a salient factor for enabling large-scale data collection scenarios. Structured instruments (e.g., questionnaires) are frequently used to collect data in various application domains, like healthcare, psychology, and social sciences. In current practice, instruments are usually distributed and filled out in a paper-based fashion (e.g., paper-and-pencil questionnaires). The widespread use of smart mobile devices, like smartphones or tablets, offers promising perspectives for the controlled collection of accurate data in high quality. The design, implementation and deployment of mobile data collection applications, however, is a challenging endeavor. First, various mobile operating systems need to be properly supported, taking their short release cycles into account. Second, domain-specific peculiarities need to be flexibly aligned with mobile application development. Third, domain-specific usability guidelines need to be obeyed. Altogether, these challenges turn both programming and maintaining of mobile data collection applications into a costly, time-consuming, and error-prone endeavor. The Ph.D. thesis at hand presents an advanced framework that shall enable domain experts to transform paper-based instruments to mobile data collection applications. The latter, in turn, can then be deployed to and executed on heterogeneous smart mobile devices. In particular, the framework shall empower domain experts (i.e., end-users) to flexibly design and create robust mobile data collection applications on their own; i.e., without need to involve IT experts or mobile application developers. As major benefit, the framework enables the development of sophisticated mobile data collection applications by orders of magnitude faster compared to current approaches, and relieves domain experts from manual tasks like, for example, digitizing and analyzing the collected data

Further on Down the Digital Road: narrative design and reading pleasure in five New Media Writing Prize narratives.

A review, supported by reader responses, of five highly regarded interactive digital narratives.The five selected pieces have all been winners or shortlisted for the interactional new Media Writing Prize. This paper discusses whether developments in narrative design, around interface, use of media, and narrative structures, have enhanced reader satisfaction. Issues identified in earlier reader-response studies are found to be still present, but several aspects present less obstruction for readers. Some indications are noted: writers may be using more familiar interface design conventions, narrative structures are becoming less fractured and hyper-link dependent; multi-media are better integrated into the narrative design

SecondLook: A Prototype Mobile Phone Intervention for Digital Dating Abuse

Digital dating abuse is a form of interpersonal violence carried out using text messages, emails, and social media sites. It has become a significant mental health crisis among the college-going population, nearly half (43%) of college women who are dating report experiencing violent and abusive dating behaviors. Existing technology and non-technology based intervention programs do not provide assistance at the onset of abuse. The overall goal of this dissertation is to create a mobile phone application that consists of a detection tool that classifies abusive digital content exchanged between partners, an educational component that provides information about healthy relationships, and a list of nearby resources for users to locate help. For the user-interface design of this application, we conducted a focus group study and incorporated the themes generated from the study to create our Android prototype. We used this prototype to conduct a usability study to evaluate the overall user-interface design and the effectiveness of the features we incorporated into the app. Due to the lack of a publicly available dataset that could be used to create training and testing sets for the classifiers to detect abusive vs non-abusive text messages in the context of digital dating abuse, we first created and validated a dataset of abusive text messages. This dissertation describes the dataset creation, validation process and the results of an evaluation of different classification and feature extraction techniques. The combination of linear support vector machine, unigram input and tf-idf feature extractor with an accuracy of 91.6% was the most balanced classifier, classifying abusive and non-abusive text messages equally well. Finally, we conducted a user study to investigate different visualization paradigms that will assist users to trust the feedback regarding the possible abusive nature of their online communication. Three different visualization techniques were evaluated using survey questionnaires to understand which one is the most effective in invoking user trust and encourages them to access resources for help

Conservation of Limited Resources: Design Principles for Security and Usability on Mobile Devices

Mobile devices have evolved from an accessory to the primary computing device for an increasing portion of the general population. Not only is mobile the primary device, consumers on average have multiple Internet-connected devices. The trend towards mobile has resulted in a shift to “mobile-first” strategies for delivering information and services in business organizations, universities, and government agencies. Though principles for good security design exist, those principles were formulated based upon the traditional workstation configuration instead of the mobile platform. Security design needs to follow the shift to a “mobile-first” emphasis to ensure the usability of the security interface. The mobile platform has constraints on resources that can adversely impact the usability of security. This research sought to identify design principles for usable security for mobile devices that address the constraints of the mobile platform. Security and usability have been seen as mutually exclusive. To accurately identify design principles, the relationship between principles for good security design and usability design must be understood. The constraints for the mobile environment must also be identified, and then evaluated for their impact on the interaction of a consumer with a security interface. To understand how the application of the proposed mobile security design principles is perceived by users, an artifact was built to instantiate the principles. Through a series of guided interactions, the importance of proposed design principles was measured in a simulation, in human-computer interaction, and in user perception. The measures showed a resounding difference between the usability of the same security design delivered on mobile vs. workstation platform. It also reveals that acknowledging the constraints of an environment and compensating for the constraints yields mobile security that is both usable and secure. Finally, the hidden cost of security design choices that distract the user from the surrounding environment were examined from both the security perspective and public safety perspective

Balancing privacy needs with location sharing in mobile computing

Mobile phones are increasingly becoming tools for social interaction. As more phones come equipped with location tracking capabilities, capable of collecting and distributing personal information (including location) of their users, user control of location information and privacy for that matter, has become an important research issue. This research first explores various techniques of user control of location in location-based systems, and proposes the re-conceptualisation of deception (defined here as the deliberate withholding of location information) from information systems security to the field of location privacy. Previous work in this area considers techniques such as anonymisation, encryption, cloaking and blurring, among others. Since mobile devices have become social tools, this thesis takes a different approach by empirically investigating first the likelihood of the use of the proposed technique (deception) in protecting location privacy. We present empirical results (based on an online study) that show that people are willing to deliberately withhold their location information to protect their location privacy. However, our study shows that people feel uneasy in engaging in this type of deception if they believe this will be detected by their intended recipients. The results also suggest that the technique is popular in situations where it is very difficult to detect that there has been a deliberate withholding of location information during a location disclosure. Our findings are then presented in the form of initial design guidelines for the design of deception to control location privacy. Based on these initial guidelines, we propose and build a deception-based privacy control model. Two different evaluation approaches are employed in investigating the suitability of the model. These include; a field-based study of the techniques employed in the model and a laboratory-based usability study of the Mobile Client application upon which the DPC model is based, using HCI (Human Computer Interaction) professionals. Finally, we present guidelines for the design of deception in location disclosure, and lessons learned from the two evaluation approaches. We also propose a unified privacy preference framework implemented on the application layer of the mobile platform as a future direction of this thesis

MailTrout:a machine learning browser extension for detecting phishing emails

The onset of the COVID-19 pandemic has given rise to an increase in cyberattacks and cybercrime, particularly with respect to phishing attempts. Cybercrime associated with phishing emails can significantly impact victims, who may be subjected to monetary loss and identity theft. Existing anti-phishing tools do not always catch all phishing emails, leaving the user to decide the legitimacy of an email. The ability of machine learning technology to identify reoccurring patterns yet cope with overall changes complements the nature of anti-phishing techniques, as phishing attacks may vary in wording but often follow similar patterns. This paper presents a browser extension called MailTrout, which incorporates machine learning within a usable security tool to assist users in detecting phishing emails. MailTrout demonstrated high levels of accuracy when detecting phishing emails and high levels of usability for end-users

Empowering vulnerable people with serious games and gamification

Although many people will associate games with entertainment and leisure, games can also aim more serious purposes, such as training or education. Games with such goals are called serious games. In addition, gamification means that a (serious) task is enhanced with game elements. Examples of serious games and gamification can be seen in many aspects of daily life. Loyalty programs of stores, educational games in schools, fitness wearables and their gamified applications, rehabilitation games, and so on. In this dissertation, the focus is on a specific domain in which serious games and gamification can create societal benefit, namely by using them to empower vulnerable target groups. In the first part of this dissertation, a literature review is performed to understand the domain of serious games and gamification for vulnerable target groups. Based on this review, research gaps can be identified. Moreover, the review resulted in a taxonomy that is used throughout the dissertation to classify different games and applications. In the following parts of the dissertation, projects addressing two different target groups and in total three vulnerabilities are discussed. The first target group is older adults, who are vulnerable in different ways. In this dissertation, safety risks for doorstep scams and health risks through malnutrition are addressed. The first vulnerability is addressed by a serious game using interactive scenarios of doorstep scams. A diet tracking system that was used to support participants in a diet trial addressed the latter vulnerability. The second target group is young adults, which is an age group with a vulnerable mental well-being. The last part of this dissertation aims to study how gamification can be used to enhance self-compassion among young adults via an online 6-weeks training program, to increase their resilience in the face of mental well-being difficulties. Artificial Intelligence (AI) technologies can be used to personalize and adapt the experience of a game to users. Tone of voice analysis was used to influence the progression in scenarios of the serious game about doorstep scams, and it gave players the possibility to assess the assertiveness of their voice. Machine learning algorithms were used to create personalized meal recommendations that can be used to improve the user experience of the diet tracking system for older adults. These algorithms base their recommendations on information about the historical intake of users to suggest meals and to additional items during meal editing. This makes the process of registering a meal less time-consuming. Sentiment analysis is used to adapt responses of the system in an exercise from the self-compassion training program. In addition, a topic detection algorithm was designed to assign one topic from a predefined set of topics to a note by a user of the training program. With this information, users can choose different types of situations to use in the exercises: frequently or rarely discussed topics. Aside from those techniques, knowledge representation is used in all projects, which is important for serious games/gamified applications since they are often based on expert and/or domain knowledge. This dissertation contributes to understanding the domain of serious games and gamification to empower vulnerable groups. The work also contributes to the research on the development of applications within that domain. On top of that, it contributes to understanding how AI techniques can be used to offer (personalized) features that enrich serious games or gamified applications. Finally, for each of the project centered parts, the results that are found in those parts contribute to the research in those specific fields

The human controller : usability and accessibility in video game interfaces

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (leaves 41-43).Despite the advances in user interfaces and the new gaming genres, not all people can play all games - disabled people are frequently excluded from game play experiences. On the one hand this adds to the list of discriminations disabled people face in our society, while on the other hand actively including them potentially results in games that are better for everyone. The largest hurdle to involvement is the user interface, or how a player interacts with the game. Analyzing usability and adhering to accessibility design principles makes it both possible and practical to develop fun and engaging game user interfaces that a broader range of the population can play. To demonstrate these principles we created AudiOdyssey, a PC rhythm game that is accessible to both sighted and non-sighted audiences. By following accessibility guidelines we incorporated a novel combination of features resulting in a similar play experience for both groups. Testing AudiOdyssey yielded useful insights into which interface elements work and which don't work for all users. Finally a case is made for considering accessibility when designing future versions of gaming user interfaces, and speculative scenarios are presented for what such interfaces might look like.by Eitan M. Glinert.M.Eng