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.

Implementing a knowledge management system within an NHS hospital:a case study exploring the roll-out of an Electronic Patient Record (EPR)

This research aims to contribute to understanding the implementation of knowledge management systems (KMS) in the field of health through a case study, leading to theory building and theory extension. We use the concept of the business process approach to knowledge management as a theoretical lens to analyse and explore how a large teaching hospital developed, executed and practically implemented a KMS. A qualitative study was conducted over a 2.5 year period with data collected from semi-structured interviews with eight members of the strategic management team, 12 clinical users and 20 patients in addition to non-participant observation of meetings and documents. The theoretical propositions strategy was used as the overarching approach for data analysis. Our case study provides evidence that true patient centred approaches to supporting care delivery with a KMS benefit from process thinking at both the planning and implementation stages, and an emphasis on the knowledge demands resulting from: the activities along the care pathways; where cross-overs in care occur; and knowledge sharing for the integration of care. The findings also suggest that despite the theoretical awareness of KMS implementation methodologies, the actual execution of such systems requires practice and learning. Flexible, fluid approaches through rehearsal are important and communications strategies should focus heavily on transparency incorporating both structured and unstructured communication methods.

Reconsidering the role of recorded audio as a rich, flexible and engaging learning space

Audio needs to be recognised as an integral medium capable of extending education’s formal and informal, virtual and physical learning spaces. This paper reconsiders the value of educational podcasting through a review of literature and a module case study. It argues that a pedagogical understanding is needed and challenges technology-centred or teacher-centred understandings of podcasting. It considers the diverse methods being used that enhance and redefine podcasting as a medium for student-centred active learning. The case study shows how audio created a rich learning space by meaningfully connecting tutors, students and those beyond the existing formal study space. The approaches used can be categorised as new types of learning activity, extended connected activity, relocated activity, and recorded ‘captured’ activity which promote learner replay and re-engagement. The paper concludes that the educational use of the recorded voice needs to be reconsidered and reconceptualised so that audio is valued as a manageable, immediate, flexible, potent and engaging medium.

Use of the web to provide learning support for a large metabolism and nutrition class

To support student learning in a large Metabolism and Nutrition class, we have introduced a web-based package, using a commercially available program, WebCT. The package was developed at a minimal cost and with limited resources. In addition to downloadable (PDF) versions of lecture Powerpoint presentations, tutorial outlines and a practical class exercise, web-based self-directed learning exercises were included to reinforce and extend lecture material in an active learning environment. The web-site also contained a variety of formative and summative assessment tasks that examined both factual recall and higher order thinking Detailed course information, timetables and a bulletin board were also readily accessible. Student usage of the site was generally high, but varied widely between individual students. Students who achieved a high overall score for the course completed on average three times as many formative assessment items and achieved a higher score for all tests than students who did poorly. Student feedback about the site was very positive with the majority of students reporting that the course material and assessment items that were available were useful to their learning. Administration of the course was also facilitated. (C) 2001 IUBMB. Published by Elsevier Science Ltd. All rights reserved.

Assessing the Use of Flexible Assessment

A course which has a large student enrolment consequently puts a heavy load on instructors both in the presentation and the assessment areas. In the School of Economics at the University of Queensland, this is the case for the quantitative analysis subjects. Assessment for many years has been through mid-semester and end of semester exams, as well as Computer Managed Learning (CML) assignments. In 2000 it was decided to incorporate a system of flexible assessment where neither the CML nor the mid-semester exam was compulsory. The outcomes are assessed and the advantages and disadvantages discussed.

Enhancing reflexivity and technology in translation learning: case study on the use of ePortfolio as a training environment

In this paper we describe a casestudy of an experiment on how reflexivity and technology can enhance learning, by using ePorfolios as a training environment to develop translation skills. Translation is today a multiskilled job and translators need to assure their clients a good performance and quality, both in language and in technology domains. In order to accomplish it, for the translator all the tasks and processes he develops appear as crucial, being pretranslation and posttranslation processes equally important as the translation itself, namely as far as autonomy, reflexive and critical skills are concerned. Finally, the need and relevance for collaborative tasks and networks amongst virtual translation communities, led us to the decision of implementing ePortfolios as a tool to develop the requested skills and extend the use of Internet in translation, namely in terminology management phases, for the completion of each task, by helping students in the management of the projects deadlines, improving their knowledge on the construction and management of translation resources and deepening their awareness about the concepts related to the development and usability of ePorfolios.

A Game of learning: a b-activity

Th The purpose of this article is to share the implementation of workgroup activities: a game of learning supported by web technology; Effective educational strategies that encourage a dynamic combination of being flexible, individualized and personalized must be the aim of every school; The blended-learning plays an important role; In this article we describe an online collaborative game which uses an inside and outside collaboration in order to promote the motivation and effective learning; Pedagogical strategies, that use technologies appropriately, in higher education, can promote active learning, centered on students and thus valuing their personal experiences and participation;

Remote lab experiments: opening possibilities for distance learning in engineering fields

Remote experimentation laboratories are systems based on real equipment, allowing students to perform practical work through a computer connected to the internet. In engineering fields lab activities play a fundamental role. Distance learning has not demonstrated good results in engineering fields because traditional lab activities cannot be covered by this paradigm. These activities can be set for one or for a group of students who work from different locations. All these configurations lead to considering a flexible model that covers all possibilities (for an individual or a group). An inter-continental network of remote laboratories supported by both European and Latin American institutions of higher education has been formed. In this network context, a learning collaborative model for students working from different locations has been defined. The first considerations are presented.

Data analytics in the cloud with flexible mapreduced workflows

Data analytic applications are characterized by large data sets that are subject to a series of processing phases. Some of these phases are executed sequentially but others can be executed concurrently or in parallel on clusters, grids or clouds. The MapReduce programming model has been applied to process large data sets in cluster and cloud environments. For developing an application using MapReduce there is a need to install/configure/access specific frameworks such as Apache Hadoop or Elastic MapReduce in Amazon Cloud. It would be desirable to provide more flexibility in adjusting such configurations according to the application characteristics. Furthermore the composition of the multiple phases of a data analytic application requires the specification of all the phases and their orchestration. The original MapReduce model and environment lacks flexible support for such configuration and composition. Recognizing that scientific workflows have been successfully applied to modeling complex applications, this paper describes our experiments on implementing MapReduce as subworkflows in the AWARD framework (Autonomic Workflow Activities Reconfigurable and Dynamic). A text mining data analytic application is modeled as a complex workflow with multiple phases, where individual workflow nodes support MapReduce computations. As in typical MapReduce environments, the end user only needs to define the application algorithms for input data processing and for the map and reduce functions. In the paper we present experimental results when using the AWARD framework to execute MapReduce workflows deployed over multiple Amazon EC2 (Elastic Compute Cloud) instances.

B-learning quality: dimensions, criteria and pedagogical approach

Measuring the quality of a b-learning environment is critical to determine the success of a b-learning course. Several initiatives have been recently conducted on benchmarking and quality in e-learning. Despite these efforts in defining and examining quality issues concerning online courses, a defining instrument to evaluate quality is one of the key challenges for blended learning, since it incorporates both traditional and online instruction methods. For this paper, six frameworks for quality assessment of technological enhanced learning were examined and compared regarding similarities and differences. These frameworks aim at the same global objective: the quality of e-learning environment/products. They present different perspectives but also many common issues. Some of them are more specific and related to the course and other are more global and related to institutional aspects. In this work we collected and arrange all the quality criteria identified in order to get a more complete framework and determine if it fits our b-learning environment. We also included elements related to our own b-learning research and experience, acquired during more than 10 years of experience. As a result we have create a new quality reference with a set of dimensions and criteria that should be taken into account when you are analyzing, designing, developing, implementing and evaluating a b-learning environment. Besides these perspectives on what to do when you are developing a b-learning environment we have also included pedagogical issues in order to give directions on how to do it to reach the success of the learning. The information, concepts and procedures here presented give support to teachers and instructors, which intend to validate the quality of their blended learning courses.

Dynamic group formation in mobile computer supported collaborative learning environment

Forming suitable learning groups is one of the factors that determine the efficiency of collaborative learning activities. However, only a few studies were carried out to address this problem in the mobile learning environments. In this paper, we propose a new approach for an automatic, customized, and dynamic group formation in Mobile Computer Supported Collaborative Learning (MCSCL) contexts. The proposed solution is based on the combination of three types of grouping criteria: learner’s personal characteristics, learner’s behaviours, and context information. The instructors can freely select the type, the number, and the weight of grouping criteria, together with other settings such as the number, the size, and the type of learning groups (homogeneous or heterogeneous). Apart from a grouping mechanism, the proposed approach represents a flexible tool to control each learner, and to manage the learning processes from the beginning to the end of collaborative learning activities. In order to evaluate the quality of the implemented group formation algorithm, we compare its Average Intra-cluster Distance (AID) with the one of a random group formation method. The results show a higher effectiveness of the proposed algorithm in forming homogenous and heterogeneous groups compared to the random method.

O desenvolvimento do pensamento abstrato através de game-based learning e do Scratch

Relatório de estágio de mestrado em Ensino de Informática