Estudios y herramientas para la evaluación y la mejora de la motivación en la ingeniería del software

Comprender y estimular la motivación resulta crucial para favorecer el rendimiento de los estudiantes universitarios y profesionales de diversos ámbitos de conocimiento, como el de la Ingeniería del Software. Actualmente, este sector está demandando soluciones científico-tecnológicas para trabajar de una manera práctica y sistemática sobre elementos motivacionales como la satisfacción por el estudio y el trabajo, el aprendizaje activo o las relaciones interpersonales. El objetivo de esta Tesis Doctoral es definir y validar soluciones para evaluar y mejorar la motivación de los estudiantes y profesionales en Ingeniería del Software. Para ello, se han creado instrumentos, metodologías y tecnologías que se han aplicado con un total de 152 estudiantes y 166 profesionales. Esta experiencia empírica ha servido para mejorar de manera continua dichas aportaciones, así como para comprobar en un entorno real su validez y utilidad. Los datos recogidos revelan que las soluciones provistas han resultado eficaces para comprender y estimular la motivación tanto en el ámbito académico como en el profesional. Además, a raíz de los datos recogidos se han podido explorar aspectos de interés sobre las características y particularidades motivacionales asociadas a la Ingeniería del Software. Por tanto, esta Tesis Doctoral resulta de interés para las universidades y empresas de este sector sensibilizadas con el desarrollo motivacional de sus estudiantes y trabajadores. Abstract It is crucial to understand and encourage the motivation of students and professionals in order to enhance their performance. This applies to students and professionals from diverse fields such as Software Engineering. Currently this sector is demanding scientific–technological solutions to work on motivational elements in a pragmatic and systematic way. Such elements are among others study and work satisfaction, active learning or interpersonal relationships. This Doctoral Thesis objective is to establish and validate solutions to evaluate and improve the motivation in the Software Engineering field. To achieve this goal, resources, methods and technologies have been created. They have been applied to 152 students and 166 professionals. This empirical experience served to, on one hand, enhance in a continuous way the provided contributions, and on the other hand, to test in a real environment their validity and utility. The collected data reveal that the provided solutions were effective to understand and encourage motivation both in the academic and in the professional area. In addition, the collected data enable to examine interesting aspects and motivational special features associated with Software Engineering. Therefore this Doctoral Thesis is relevant to universities and firms from this field which are aware of the significance of the motivational development of their students and employees.

Improving flexible databases searches using machine learning

El objetivo principal de este proyecto ha sido introducir aprendizaje automático en la aplicación FleSe. FleSe es una aplicación web que permite realizar consultas borrosas sobre bases de datos nítidos. Para llevar a cabo esta función la aplicación utiliza unos criterios para definir los conceptos borrosos usados para llevar a cabo las consultas. FleSe además permite que el usuario cambie estas personalizaciones. Es aquí donde introduciremos el aprendizaje automático, de tal manera que los criterios por defecto cambien y aprendan en función de las personalizaciones que van realizando los usuarios. Los objetivos secundarios han sido familiarizarse con el desarrollo y diseño web, al igual que recordar y ampliar el conocimiento sobre lógica borrosa y el lenguaje de programación lógica Ciao-Prolog. A lo largo de la realización del proyecto y sobre todo después del estudio de los resultados se demuestra que la agrupación de los usuarios marca la diferencia con la última versión de la aplicación. Esto se basa en la siguiente idea, podemos usar un algoritmo de aprendizaje automático sobre las personalizaciones de los criterios de todos los usuarios, pero la gran diversidad de opiniones de los usuarios puede llevar al algoritmo a concluir criterios erróneos o no representativos. Para solucionar este problema agrupamos a los usuarios intentando que cada grupo tengan la misma opinión o mismo criterio sobre el concepto. Y después de haber realizado las agrupaciones usar el algoritmo de aprendizaje automático para precisar el criterio por defecto de cada grupo de usuarios. Como posibles mejoras para futuras versiones de la aplicación FleSe sería un mejor control y manejo del ejecutable plserver. Este archivo se encarga de permitir a la aplicación web usar el lenguaje de programación lógica Ciao-Prolog para llevar a cabo la lógica borrosa relacionada con las consultas. Uno de los problemas más importantes que ofrece plserver es que bloquea el hilo de ejecución al intentar cargar un archivo con errores y en caso de ocurrir repetidas veces bloquea todas las peticiones siguientes bloqueando la aplicación. Pensando en los usuarios y posibles clientes, sería también importante permitir que FleSe trabajase con bases de datos de SQL en vez de almacenar la base de datos en los archivos de Prolog. Otra posible mejora basarse en distintas características a la hora de agrupar los usuarios dependiendo de los conceptos borrosos que se van ha utilizar en las consultas. Con esto se conseguiría que para cada concepto borroso, se generasen distintos grupos de usuarios, los cuales tendrían opiniones distintas sobre el concepto en cuestión. Así se generarían criterios por defecto más precisos para cada usuario y cada concepto borroso.---ABSTRACT---The main objective of this project has been to introduce machine learning in the application FleSe. FleSe is a web application that makes fuzzy queries over databases with precise information, using defined criteria to define the fuzzy concepts used by the queries. The application allows the users to change and custom these criteria. On this point is where the machine learning would be introduced, so FleSe learn from every new user customization of the criteria in order to generate a new default value of it. The secondary objectives of this project were get familiar with web development and web design in order to understand the how the application works, as well as refresh and improve the knowledge about fuzzy logic and logic programing. During the realization of the project and after the study of the results, I realized that clustering the users in different groups makes the difference between this new version of the application and the previous. This conclusion follows the next idea, we can use an algorithm to introduce machine learning over the criteria that people have, but the problem is the diversity of opinions and judgements that exists, making impossible to generate a unique correct criteria for all the users. In order to solve this problem, before using the machine learning methods, we cluster the users in order to make groups that have the same opinion, and afterwards, use the machine learning methods to precise the default criteria of each users group. The future improvements that could be important for the next versions of FleSe will be to control better the behaviour of the plserver file, that cost many troubles at the beginning of this project and it also generate important errors in the previous version. The file plserver allows the web application to use Ciao-Prolog, a logic programming language that control and manage all the fuzzy logic. One of the main problems with plserver is that when the user uploads a file with errors, it will block the thread and when this happens multiple times it will start blocking all the requests. Oriented to the customer, would be important as well to allow FleSe to manage and work with SQL databases instead of store the data in the Prolog files. Another possible improvement would that the cluster algorithm would be based on different criteria depending on the fuzzy concepts that the selected Prolog file have. This will generate more meaningful clusters, and therefore, the default criteria offered to the users will be more precise.

Ambientes tecno-pedagógicos para o desenvolvimento de competências transversais para a inovação em engenharia.

Muito se fala na crescente velocidade de inovações tecnológicas que se apresenta ao mundo e que vai se acelerando. Antes, gerações se passavam para termos uma evolução tecnológica. Hoje, uma mesma geração presencia vários saltos tecnológicos. Neste contexto de inovações frequentes, surge a preocupação sobre como formar um profissional responsável, ético e que consiga acompanhar e ser protagonista de tais mudanças. O trabalho desenvolvido nesta tese busca colaborar na discussão sobre a formação do engenheiro, com foco na engenharia elétrica e de computação, revisitando as definições de conceitos como educação em engenharia, aprendizagem ativa, inovação, Design Thinking e competências transversais, e definindo, como contribuição de pesquisa, os conceitos de tecno-pedagogia e ambientes tecno-pedagógicos, como pressuposto de convergência de estruturas tecnológicas, estratégias pedagógicas e métodos de avaliação em aprendizagem ativa para a inovação. Apresenta um método para identificar e quantificar o grau de ênfase das competências transversais para a inovação a partir da demanda de mercado para engenheiros eletricistas e da computação; e um método de observação, coleta e análise de dados sobre o desenvolvimento de competências transversais na participação em duas experiências de aula: na disciplina global ME310 da Universidade de Stanford; e na disciplina 030-3410 da Escola Politécnica da Universidade de São Paulo. Com isso, foi possível elaborar um método para auxiliar no planejamento de disciplinas e cursos com foco em inovação, identificando as competências transversais que devem ser incentivadas e relacionando tais competências com estratégias de ensino e aprendizagem e sugerindo a estrutura tecnológica e método de avaliação a serem adotados.

Validation of a Spanish version of the Distance Education Learning Environments Survey (DELES) in Spain

The aim of this study was to examine the validity of the Spanish version of the Distance Education Learning Environments Survey (Sp-DELES). This instrument assesses students’ perceptions of virtual learning environments using six scales: Instructor Support, Student Interaction and Collaboration, Personal Relevance, Authentic Learning, Active Learning, and Autonomy. Further, the Sp-DELES includes an additional scale that assesses students’ Satisfaction with their classes. The original DELES has been used in at least 27 independent studies with strong reliability and validity. For this study, we sampled 265 students from the University of Alicante enrolled in various hybrid and distance education courses taught by the Department of Health Psychology. We analysed the Sp-DELES for validity using principal component factor analysis with varimax rotation, and for reliability using Cronbach’s alpha. The Sp-DELES exhibited good reliability (Cronbach’s alpha for the scales ranging from 0.86 to 0.97) and the original six-factor structure was replicated and accounted for 72.9 % of the total variance. Overall the results are consistent with those of the original English-language version of the instrument. The Sp-DELES has proven to be a reliable and valid instrument for assessing psychosocial learning environments in tertiary-level hybrid and distance-education settings.

Dynamic, convex, and robust optimization with Bayesian learning for response-guided dosing

Thesis (Ph.D.)--University of Washington, 2016-08

Approaches and Strategy for Cancer Research and Surveillance Data: Integration, Information Pipeline, Data Models, and Informatics Opportunities

Thesis (Ph.D.)--University of Washington, 2016-04

System for foreign exchange trading using genetic algorithms and reinforcement learning

Foreign exchange trading has emerged recently as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. A major issue for traders in the deregulated Foreign Exchange Market is when to sell and when to buy a particular currency in order to maximize profit. This paper presents novel trading strategies based on the machine learning methods of genetic algorithms and reinforcement learning.

Problem-based learning: a case study in providing e-health education using the Internet

The current trend among many universities is to increase the number of courses available online. However, there are fundamental problems in transferring traditional education courses to virtual formats. Delivering current curricula in an online format does not assist in overcoming the negative effects on student motivation which are inherent in providing information passively. Using problem-based learning (PBL) online is a method by which computers can become a tool to encourage active learning among students. The delivery of curricula via goal-based scenarios allows students to learn at different rates and can successfully shift online learning from memorization to discovery. This paper reports on a Web-based e-health course that has been delivered via PBL for the past 12 months. Thirty distance-learning students undertook postgraduate courses in e-health delivered via the Internet (asynchronous communication). Data collected via online student surveys indicated that the PBL format was both flexible and interesting. PBL has the potential to increase the quality of the educational experience of students in online environments.

The design and evaluation of distributed virtual environment to support learning in global operations management

The primary goal of this research is to design and develop an education technology to support learning in global operations management. The research implements a series of studies to determine the right balance among user requirements, learning methods and applied technologies, on a view of student-centred learning. This research is multidisciplinary by nature, involving topics from various disciplines such as global operations management, curriculum and contemporary learning theory, and computer aided learning. Innovative learning models that emphasise on technological implementation are employed and discussed throughout this research.

Knowledge acquisition in international strategic alliances among Malaysian manufacturing firms

This thesis examines the process of knowledge acquisition by Malaysian manufacturing firms through their involvement in international strategic alliances. The strategic alliances can be with or without equity involvement. Firms involved with a foreign partner with equity involvement are joint venture firms while non-equity involvement are firms that engaged in contractual agreements. Using empirical evidence from 65 international alliances gathered through a survey conducted in high-technology manufacturing sectors, several factors that influence the process of knowledge acquisition are examined. The factors are: learning capacity, experience, goals, active involvement and accessibility to the foreign knowledge. Censored regression analysis and ordered probit analysis are used to analyse the effects of these factors on knowledge acquisition and its determinant parts, and the effects of knowledge acquisition and its determinants on the performance of the alliances. A second questionnaire gathered evidence relating to the factors, which encouraged tacit knowledge transfer between the foreign and Malaysian partners in international alliances. The key findings of the study are: knowledge acquisition in international strategic alliances is influenced by five determining factors; learning capacity, experience, articulated goals, active involvement and accessibility; new technology knowledge, product development knowledge and manufacturing process knowledge are influenced differently by the determining factors; knowledge acquisition and its determinant factors have a significant impact on the firm’s performance; cultural differences tend to moderate the effect on the firm’s performance; acquiring tacit knowledge is not only influenced by the five determinant factors but also by other factors, such as dependency, accessibility, trust, manufacturing control, learning methods and organisational systems; Malaysian firms involved in joint ventures tend to acquire more knowledge than those involved in contractual agreements, but joint ventures also exhibit higher degrees of dependency than contractual agreements; and the presence of R&D activity in the Malaysian partner encourages knowledge acquisition, but the amount of R&D expenditure has no effect on knowledge acquisition.

National system of innovation and technological learning:an integrated framework for understanding technological capability development in the Russian forestry sector

One of the issues in the innovation system literature is examination of technological learning strategies of laggard nations. Two distinct bodies of literature have contributed to our insight into forces driving learning and innovation, National Systems of Innovation (NSI) and technological learning literature. Although both literatures yield insights on catch-up strategies of 'latecomer' nations, the explanatory powers of each literature by itself is limited. In this paper, a possible way of linking the macro- and the micro-level approaches by incorporating enterprises as active learning entities into the learning and innovation system is proposed. The proposed model has been used to develop research hypotheses and indicate research directions and is relevant for investigating the learning strategies of firms in less technologically intensive industries outside East Asia.

E-Support for English Language Course to Enhance University Students’ Learning.

The peculiarities of English language teaching for students at higher educational establishment using some elements of distance learning, developed by the author, are described in this article. The results of students’ questioning, received at the end of the experimental teaching, are suggested and analyzed. The conclusions are formulated and the further ways of teaching English with e-support are outlined.

e-Learning, e-Practising and e-Tutoring: an Integrated Approach

In this paper is described a didactic methodology combining current e-learning methods and the support of Intelligent Agents technologies. The aim is to favor the synthesis among theoretical approach and based practical approach using the so-called Intelligent Agent, software that exploits the Artificial Intelligence and that operates as tutor, facilitating the consumers in the training operations. The paper illustrates how such new Intelligent Agent algorithm (IA) is used in the training of employees working in the transportation sector, thanks to the experience gained with the PARMENIDE project - Promoting Advanced Resources and Methodologies for New Teaching and Learning Solutions in Digital Education.

A Comparative Analysis of Predictive Learning Algorithms on High-Dimensional Microarray Cancer Data

This research evaluates pattern recognition techniques on a subclass of big data where the dimensionality of the input space (p) is much larger than the number of observations (n). Specifically, we evaluate massive gene expression microarray cancer data where the ratio κ is less than one. We explore the statistical and computational challenges inherent in these high dimensional low sample size (HDLSS) problems and present statistical machine learning methods used to tackle and circumvent these difficulties. Regularization and kernel algorithms were explored in this research using seven datasets where κ < 1. These techniques require special attention to tuning necessitating several extensions of cross-validation to be investigated to support better predictive performance. While no single algorithm was universally the best predictor, the regularization technique produced lower test errors in five of the seven datasets studied.