Measuring the Usability and Capability of App Inventor to Create Mobile Applications

MIT App Inventor is a web service that enables users with little to no previous programming experience to create mobile applications using a visual blocks language. We analyze a sample of 5,228 random projects from the corpus of 9.7 million and group projects by functionality. We then use the number of unique blocks in projects as a metric to better understand the usability and realized capability of using App Inventor to implement specific functionalities. We introduce the notion of a usability score and our results indicate that introductory tutorials heavily influence the usability of App Inventor to implement particular functionalities. Our findings suggest that the sequential nature of App Inventor’s learning resources results in users realizing only a portion of App Inventor’s capabilities and propose improvements to these learning resources that are transferable to other programming environments and tools.Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Google Research and Innovation Scholarship

Towards helping end-user programmers’ information foraging by manipulating information features in a patch

Software maintenance tasks often require finding information within existing code, which is time-consuming and difficult even for professional programmers. For example, programmers may need to know what code implements certain functionality or what is the purpose of certain code. In response, researchers have developed tools to help programmers find information during programming tasks. The empirical success of these tools can be explained by Information Foraging Theory (IFT), which predicts how people will seek information by navigating through virtual patches in an information system. In the case of programming, these patches are often chunks of code (e.g., functions), with navigable links for moving among methods. IFT predicts people will perceive cues (such as words or symbols) associated with navigable links, select links that seem relevant to their information needs, and attempt to obtain the needed information by maximizing the rate of information gained relative to the cost of navigating and understanding patches. Many existing tools accelerate foraging by decreasing the cost associated with navigating from one patch to another. IFT suggests that the visual weight of the information features in a patch can have a strong effect on a predator’s foraging choices and, consequently, on how well the predator succeeds in maximizing the rate of information gain. In an ideal situation, visual weight will efficiently lead the predator to the needed information; on the other hand, if visual weight leads the predator astray, then this could lead the predator to process more patches than necessary (increasing cost and reducing the rate of information gain). Therefore, it is anticipated that increasing the relative weight of important information features with respect to unimportant information features will aid an end-user programmer’s foraging effort. Towards this end, two prototypes were implemented: each of these uses an existing algorithm to identify the most important lines of code in a function. One prototype increases the relative weight of important information features by highlighting important lines of code; the other prototype decreases the relative weight of unimportant information features by hiding unimportant lines of code. This research's focus is end-user programmers, who have received minimal attention in prior work. An empirical study evaluated the effectiveness of the prototypes relative to the baseline (no information feature modification). These results indicate that increasing the relative weight of important information features by highlighting important statements had a significant effect on the amount of information foraged and the rate of information gained; on the other hand, decreasing the relative weight of unimportant information features by hiding unimportant statements had a significant effect on the rate of information gained, but not on the amount of information foraged. Neither approaches seemed to have any effect on the amount of time spent on information foraging or patch-to-patch navigation

A Comprehensive Field Study of End-User Programming on Mobile Devices

Abstract—TouchDevelop represents a radically new programming environment that enables users to develop mobile applications directly on mobile devices. TouchDevelop has successfully drawn a huge number of end users, who have published thousands of TouchDevelop scripts online. To enhance end-user programming on mobile devices, we conduct the first comprehensive field study of 17322 TouchDevelop scripts and 4275 users. Our study consists of an overall study on the characteristics of scripts (e.g., structural features, code reuse) and users (e.g., expertise), and a longitudinal study on how they evolve over time. Our study results show important characteristics of scripts such as dense external method calls, high code reuse ratio, and also reveal interesting evolution patterns of users. The findings and implications in our study provide valuable guidelines for improving tool support or services for end users and increasing the popularity of end-user programming on mobile devices. I

Un enfoque orientado a usuarios finales para el desarrollo de aplicaciones de aumentación web móvil

La información existente en la Web podría utilizarse para resolver una amplia gama de problemas de diferentes dominios, pero dicha información no siempre se encuentra reunida en un mismo contexto y resulta difícil encontrar una manera de relacionarla para satisfacer necesidades que, a veces, son requeridas por una minoría de usuarios. Los sitios Web son diseñados para un único usuario, sino más bien enfocados en un conjunto de ellos con características similares y para llevar a cabo tareas específicas, que pueden diferir de las que un usuario particular necesita. Aquí es donde la Aumentación Web se presenta como un medio para lograr la adaptación de los recursos Web existentes de acuerdo con los requisitos del usuario, tanto en contenido como en comportamiento, estructura y/o forma. Por su parte, la tendencia hacia el uso activo de los dispositivos móviles ha hecho posible que la Web sea concebida no sólo como un espacio de información, sino también como una plataforma omnipresente donde sus usuarios realizan todo tipo de tareas. Sin embargo, pese a su uso, muchas aplicaciones Web aún no tienen una contraparte móvil que haga uso de sus características, e incluso algunas ni siquiera responden a un diseño Web responsive. La información del contexto permite mejorar la experiencia del usuario. Por ejemplo, permite filtrar y solo presentar aquella información que coincide con la posición del usuario, la presión sonora en el ambiente o un rango horario determinado. La Aumentación Web Móvil puede ayudar a agregar incorporar características, y mediante técnicas de Desarrollo por Usuarios Finales es posible convertir a las personas que poseen tal necesidad, en los autores de su propia solución de aumentación. Aunque algunos enfoques existen para aumentar aplicaciones Web, incluso con características móviles, los mismos son dirigidos y limitados a personas con –al menos– conocimiento en programación. También existe un gran número de herramientas de autoría que permiten la creación de aplicaciones móviles desde entornos de escritorio, nativos o móviles, pero ninguna de ellas genera aplicaciones Web puras; ejecutables en un navegador Web móvil convencional y sin depender de algún componente nativo para su ejecución. En esta obra se presenta un nuevo enfoque para permitir que los usuarios finales mejoren sus sitios Web preferidos con características móviles. El proceso de autoría es asistido por formularios, y un paso final que combina live programming y composición mediante widgets visuales. El enfoque fue evaluado mediante el uso de una herramienta de soporte, por 21 usuarios finales, y sus resultados demuestran que el enfoque es viable y prometedor, puesto que los usuarios finales fueron capaces de completar, en promedio, el 84% de los requerimientos del experimento.Tesis digirida por los Dres. Gustavo Rossi y Sergio Firmenich.Facultad de Informátic