Evaluation of Team Quality

Competitive pressure and increasing market size have forced organizations to rely more on teams. This study has three objectives: to structure a list of attributes affecting the overall quality of a team; to use a survey tool to determine the significant ones among those attributes; and to compare between manufacturing and healthcare sectors. The data gathered were from employees working in teams in USA and China. A one-way analysis of variance and stepwise regression analysis was performed on the responses to determine team quality attributes. The ANOVA results for attributes versus teams revealed team efficacy, team trust, personality and skills & knowledge as significant. The stepwise regression analysis for team quality versus other attributes (for all the teams combined) showed that job satisfaction and team trust were significantly affecting the overall team quality. Analyses showed differences between China and USA. 

Far but Near or Near but Far?: The Effects of Perceived Distance on the Relationship between Geographic Dispersion and Perceived Diversity

Geographic dispersion has been proposed as one means to promote cooperation and coordination in teams high in perceived diversity. However, research has found mixed support for this assertion. This study proposes that the inclusion of perceived distance helps to explain these mixed results. To test this assertion, we examined 121 teams—62 collocated and 59 geographically dispersed. Results demonstrate that perceived distance explains when geographic dispersion benefits teams high in perceived diversity. Results also indicate that the type of perceived diversity matters (surface-level vs. deep-level diversity). This study contributes to our understanding of distance and diversity in teams.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/116792/1/paper2483 (Final Submission).pdfDescription of paper2483 (Final Submission).pdf : Main Articl

Designing a Web Application for Simple and Collaborative Video Annotation That Meets Teaching Routines and Educational Requirements

Video annotation and analysis is an important activity for teaching with and about audiovisual media artifacts because it helps students to learn how to identify textual and formal connections in media products. But school teachers lack adequate tools for video annotation and analysis in media education that are easy-to-use, integrate into established teaching organization, and support quick collaborative work. To address these challenges, we followed a design-based research approach and conducted qualitative interviews with teachers to develop TRAVIS GO, a web application for simple and collaborative video annotation. TRAVIS GO allows for quick and easy use within established teaching settings. The web application provides basic analytical features in an adaptable work space. Key didactic features include tagging and commenting on posts, sharing and exporting projects, and working in live collaboration. Teachers can create assignments according to grade level, learning subject, and class size. Our work contributes further insights for the CSCW community about how to implement user demands into developing educational tools

Medidas de productividad en los proyectos de desarrollo de software: una aproximación por puestos de trabajo

La productividad es una medida, principalmente económica, creada a finales del siglo XVIII. Desde entonces, numerosas modificaciones se han realizado sobre la definición inicial y se han incorporando a diversas áreas de conocimiento. Dentro de la Ingeniería del Software (IS), la productividad comenzó a ser objeto de estudio a finales de los años 70, casi de forma paralela a la concepción de la misma y al inicio del estudio de conceptos relacionados, tales como la estimación de esfuerzo. La medición de la productividad en IS ha sido ampliamente analizada a nivel de proyecto y organización, sin embargo a nivel de puesto de trabajo no ha sido tan investigada. En estos escasos estudios, las medidas utilizadas suelen ser las mismas medidas que las empleadas en niveles superiores de medición. En concreto, las medidas empleadas suelen ser ratios entre una medida de tamaño de producto (p. ej., líneas de código o puntos función) y una medida de esfuerzo o tiempo (p. ej., horas-hombre u horas). Este tipo de medidas son muy específicas y no reflejan la realidad del trabajo desempeñado en todo el proceso de desarrollo, ya que no tienen en cuenta las características inherentes a cada puesto de trabajo. Así pues, la eficacia de estas medidas, en este nivel de medición, parece estar en entredicho y la realización de estudios que aporten nuevas medidas de productividad en IS a nivel de puesto de trabajo cobra sentido. En la presente tesis doctoral se ha analizado la situación actual de la medición de la productividad en IS a nivel de puesto de trabajo con el objetivo de crear nuevas medidas. Para conseguir este objetivo se ha realizado un estudio del estado de la cuestión utilizando una metodología clásica de revisión de referencias junto con una revisión sistemática de la literatura. Una vez analizado el estado de la cuestión se ha planteado un conjunto de hipótesis relacionadas con la construcción de nuevas medidas de productividad: Hipótesis 1. En los puestos de trabajo involucrados en la ejecución de proyectos de desarrollo de software se emplean otras entradas, además del tiempo y el esfuerzo. Hipótesis 2. Las entradas utilizadas son distintas para cada puesto de trabajo involucrado en la ejecución de proyectos de desarrollo de software. Hipótesis 3. En los puestos de trabajo involucrados en la ejecución de proyectos de desarrollo de software se producen otras salidas, además de líneas de código y funcionalidad. Hipótesis 4. Las salidas producidas son distintas para cada puesto de trabajo involucrado en la ejecución de proyectos de desarrollo de software. Hipótesis 5. Las medidas de productividad más utilizadas a nivel de puesto de trabajo en los proyectos de desarrollo de software tienen una eficacia limitada para medir la productividad real de los trabajadores. Hipótesis 6. Es posible medir de forma más eficaz la productividad de los puestos de trabajo en los proyectos de desarrollo de software con nuevas medidas que combinen varios elementos: entradas, salidas y factores. Tras el análisis del estado de la cuestión, se ha realizado una fase de investigación cualitativa mediante el empleo de entrevistas a trabajadores de IS y un posterior análisis de contenido, con el fin de obtener información suficiente para: (1) contrastar las cuatro primeras hipótesis con información cualitativa, y (2) construir el medio de recogida de información para la siguiente fase de la investigación. Con respecto al primer objetivo, ha sido posible contrastar dos hipótesis (H1 y H3). En la segunda fase, mediante una metodología cuantitativa, se han contrastado las cuatro primeras hipótesis planteadas. Para la recogida de información se ha utilizado un formulario construido a partir de los resultados de la fase cualitativa. Los resultados de esta fase indican que en los puestos de trabajo analizados (programador, analista, consultor, y jefe de proyecto): se utilizan otros recursos además del tiempo, se producen otras salidas además del código fuente y la funcionalidad entregada al cliente. Además, se han encontrado diferencias en el grado de uso de las entradas y en la producción de las salidas, por lo que el uso de una misma medida de productividad para todos los puestos bajo estudio es, en principio, ilógico. Para contrastar las dos, y últimas, hipótesis se han construido nuevas medidas de productividad, teniendo en cuenta los resultados previos. En concreto, se ha utilizado Data Envelopment Analysis (DEA) como metodología personalizable para medir la productividad; y se han realizado cuatro casos de estudio empleando dicha metodología. Los resultados tras los casos de estudio indican que mediante DEA es posible medir la productividad de los puestos de trabajo vinculados con los proyectos de desarrollo y mantenimiento de software de forma más eficaz que con las medidas más utilizadas. Además, esta metodología permite conocer los puntos de mejora para que los trabajadores menos productivos aumenten su productividad, lo que supone una gran ventaja frente a otras medidas de productividad si el objetivo de medir, como es lógico suponer, es mejorar la productividad, y no simplemente evaluarla. Así pues, se contrastan las dos últimas hipótesis y se insta, entre otras futuras líneas de investigación, a continuar con nuevos estudios que comparen el uso de DEA con otras medidas de productividad. Finalmente, se concluye que la medición de la productividad en los puestos de trabajo vinculados con los proyectos de desarrollo y mantenimiento de software continua siendo un reto. Para reducir la dificultad de éste, la presente tesis doctoral arroja luz aportando un marco de trabajo para analizar y plantear nuevas medidas de productividad, tanto en estos puestos de trabajo como en otros. ------------------------------Productivity is mainly an economic measure, created in the late eighteenth century. Since then, many changes have been made on its initial definition and have been incorporated into various areas of knowledge. Within Software Engineering (SE), productivity began to be studied in the late '70s. These efforts ran parallel to SE developments, such as effort estimation. Measuring productivity in SE has been extensively analyzed at the project and organization level; however job level has not been investigated with the same depth. In these few studies, the measures used are often the same ones than those used in higher levels of measurement. Specifically, the measures employed are usually ratios between a measure of product size (e.g., lines of code or function points) and a measure of effort or time (e.g., man-hours or hours). Such measures do not reflect the reality of the work performed throughout the development process because they do not take into account the inherent characteristics of each job. Thus, the effectiveness of these measures, in this measurement level, seems to be in question and studies that provide new measures of productivity at job level make sense. In this thesis we have analyzed the current state of productivity measurement at job level within SE with the goal of creating new measures. In order to achieve this objective a study of the state of the art has been carried out with a classical methodology along with a systematic review of the literature. After analyzing the state of the art, a number of hypotheses related to the construction of new productivity measures have been stated: Hypothesis 1. In the jobs involved in the implementation of software development projects other inputs are used in addition to time and effort. Hypothesis 2. The inputs used are different for every job involved in software development projects. Hypothesis 3. In the jobs involved in the implementation of software development projects other outputs are produced in addition to source code lines and functionality. Hypothesis 4. The outputs produced are different for every job involved in software development projects. Hypothesis 5. The most used productivity measures at job level in software development projects have limited effectiveness for measuring real productivity of workers. Hypothesis 6. It is possible to measure more effectively the productivity of jobs in software development projects with new measures that combine several elements: inputs, outputs and factors. After analyzing the state of the art, a qualitative phase has been performed using interviews with SE workers and a subsequent content analysis of them in order to obtain pertinent information: (1) to test the first four hypotheses with qualitative information, and (2) to build the information gathering instrument for the next phase of research. Regarding the first objective, it has been possible to test two hypotheses (H1 and H3). In the second phase, using a quantitative method, the first four hypotheses have been contrasted and accepted. For the information gathering a form constructed from the results of the qualitative phase has been used. The results of this phase indicate that the analyzed job positions (programmer, analyst, consultant, and project manager): use other resources in addition to time, and deliver other outputs in addition to source code and functionality delivered to the client. Also some differences in the degree of use of inputs and production of outputs have been found. Therefore, the use of the same measure of productivity for all positions under study is, in principle, illogical. To contrast the last two hypotheses new productivity measures have been built taking into account the previous results. Specifically, a customizable methodology for measuring productivity such as Data Envelopment Analysis (DEA) was used in four case studies. The results after these studies indicate that using DEA is a mean to measure the productivity of job level for job positions related to the development and maintenance of software projects in a more effectively way. Furthermore, this methodology allows knowing the points for improvement for the least productive workers in order to increase their productivity. This knowledge is a great advantage over other productivity measures if the goal of measuring, as is logical to assume, is to improve productivity, not simply to evaluate it. So the last two hypotheses has been supported. Consequently we call, among other future research, to continue with further studies comparing the use of DEA with other measures of productivity. Finally, it is concluded that the measurement of productivity in job positions related with software development and maintenance projects remains a challenge. To reduce this difficulty, this thesis sheds some light on the topic by providing a framework to analyze and propose new measures of productivity for SE job roles.Presidente: María Belén Ruiz Mezcua; Vocal: Rafael Valencia García; Secretario: Edmundo Tovar Car

Techniques for improving routing by exploiting user input and behavior

University of Minnesota Ph.D. dissertation. October 2014. Major: Computer Science. Advisor: Loren Terveen. 1 computer file (PDF); xiii, 106 pages.This dissertation explores innovative techniques for improving the route finding process. Instead of focusing on improving the algorithm itself, I aim to improve the other factors that make the route finding experience better: personalization, map data, and presentation. I do so by making extensive use of user input (both explicit and implicit) and crowdsourcing strategies. This research uses Cyclopath, a geowiki for cyclists in the Twin Cities, MN, as a case study for the various techniques explored.The first challenge is the lack of personalization in route finding algorithms. Aside from start and end points, algorithms usually know very little about users. However, user preferences can greatly affect their ideal routes. I studied the use of community-shared tags that allow users to specify preferences for those tags instead of doing so for each individual road segment, allowing them to easily express preference for a large number of roads with little effort. Correlation between individual road segment ratings and ratings deduced from tag preferences was evidence of the utility of this technique for making personalization easier.The second challenge is missing data. The best routing algorithm is only as good as the map data underneath it. Unfortunately, maps are often incomplete. They might not have updates on the latest construction, might be missing roads in rural areas or might not include detailed information such as lanes, trails, and even shortcuts. I present an HMM-based map matching algorithm that uses GPS traces recorded by users to generate potential new road segments. Tests within Cyclopath confirmed the abundance of missing roads and the ability of this algorithm to detect them.Finally, I look at the issue of unnatural presentation of routes. The way computers relay route directions is very different from humans, who use landmarks most of the time. However, gathering useful landmarks can be difficult and is often limited to points of interest. In this research, I tested methods for crowdsourcing different types of landmarks. I show that POIs are not sufficient to represent landmarks and that there is no objective truth regarding which landmarks are more useful to users

FeatureIT : a platform for collaborative software development

The development of enterprise software is a complex activity that requires a diverse set of stakeholders to communicate and coordinate in order to achieve a successful outcome. In this dissertation I introduce a high-level physical architecture for a platform titled FeatureIT that has the goal of supporting the collaboration between stakeholders throughout the entire Software Development Life Cycle (SDLC). FeatureIT is the result of unifying the theoretical foundations of the multi-disciplinary field of Computer Supported Cooperative Work (CSCW) with the paradigm and associated technologies of Web 2.0. The architecture was borne out a study of literature in the fields of CSCW, Web 2.0 and software engineering, which facilitated the identification of functional and non-functional requirements necessary for the platform. The design science research methodology was employed to construct this architecture iteratively to satisfy the requirements while validating its efficacy against a comprehensive set of scenarios that typically occur in the SDLC.ComputingM. Sc. (Information Systems