Evaluation of an eLearning pilot course based on user experiences: corporate case study

Diplomityön tavoitteena oli arvioida sähköisen oppimisen soveltuvuutta kohdeyrityksessä ja selvittää, voidaanko luokkahuonekoulutusta korvata sähköisen oppimisen kursseilla. Tietojärjestelmän raportoinnista tehtiin sähköisen oppimisen kurssi, joka oli koekäytössä. Koekäytön jälkeen tehtiin käyttäjäkysely, kerättiin käyttötietoja kurssista ja tehtiin haastatteluja. Koekäyttäjien kokemuksista tehdyn arvioinnin perusteella sähköinen oppiminen soveltuu käytettäväksi selkeiden asioiden koulutukseen kohdeyrityksessä, mutta se ei voi kokonaan korvata luokkahuonekoulutusta. Luokkahuonekoulutuksessa tulisi keskittyä monimutkaisempiin asioihin ja ongelmanratkaisuun. Positiivisten tulosten perusteella sähköisen oppimisen kehittämistä päätettiin jatkaa yrityksessä. Sähköisen oppimisen kurssin avulla saadaan kustannussäästöjä kohdeyrityksessä, kun käyttäjämäärä on suurempi kuin 66. Jos koko koekäytössä olleen kurssin kohdeyleisö suorittaa kurssin sähköisesti, ovat kustannukset vain noin 15% vastaavista kustannuksista luokkahuoneessa järjestettynä. Lisäksi sähköisen oppimisen tehokkuutta tutkittiin ja koekäytössä olleen kurssin arvioitiin olevan positiivinen työssä kehitetyn Consensus-mallin mukaan.

L'Aprenentatge virtual com a una nova forma d'ensenyar i d'aprendre a través de les tecnologies de la informació i la comunicació

Els avenços tecnològics de les àrees de la informació i la comunicació estan propiciant un canvi cultural important que repercuteix directament en el món de l'aprenentatge i de l¿ensenyament. L'aprenentatge instrumental d'aquestes tecnologies de la informació i la comunicació (TIC) a priori i l'aprenentatge a través d'aquestes tecnologies amb la finalitat d'accedir a un major coneixement ha provocat que el procés d'ensenyament i aprenentatge s'estengui al llarg de la vida («Life long learning») de qualsevol persona que, per la seva professió, necessiti actualitzar els seus coneixements. Per això, com es podrà apreciar en el present article, les noves línies d'investigació s¿orienten envers dos tipus d'estudi: optimitzar el disseny dels sistemes d'e-learning i analitzar els aspectes diferencials dels e-learners. A més, en l¿article, se¿ns dóna a conèixer com s'està desenvolupant el camp de l'aprenentatge virtual en aquest moment, en particular en l'àmbit de les universitats europees.

Automatización de los procesos para la generación, ensamblaje y reutilización de objetos de aprendizaje.

La carencia de modelos conceptuales en el diseño y construcción de los actuales sistemas para la gestión de contenido de aprendizaje (LCMSs) causa problemas relacionados con la generación, ensamblaje y reutilización de objetos de aprendizaje, recursos electrónicos con fines educativos. La investigación tiene como objetivos facilitar un modelo conceptual que proporcione pautas para evitar los problemas mencionados; implementar un mecanismo para el ensamblaje de diferentes tipos de objetos de aprendizaje; y un procedimiento para la descripción de objetos de aprendizaje resultantes de los procesos de embalaje.. Este trabajo, en primer lugar, expone una propuesta de modelo conceptual, a continuación analiza la plataforma para la evaluación de objetos de aprendizaje y describe el proceso de evaluación del modelo propuesto. La investigación tiene una perspectiva incremental y consta de las siguientes etapas: un estudio del estado de la cuestión, la definición del modelo conceptual y un análisis para la implementación del mecanismo de ensamblaje de los objetos para verificar su viabilidad.. Esta investigación propone, una definición del modelo conceptual y aspectos relacionados con el ensamblaje, descripción y reutilización de objetos electronicos de aprendizaje (ELOs, Electronic Learning Objects). Propone soluciones a los problemas relacionados con la carencia de modelos conceptuales y plantea nuevas líneas de trabajo..

eLEARNING

eLearning through its flexibility and facility of access is seen as a major enabler of lifelong learning (LLL), as a catalyst of change and a chance for small and medium-sized enterprises (SMEs) to improve their business and to integrate into European market. But so far eLearning in the context of vocational educational training mainly has been adopted by large enterprises, while only little activity can be observed in SMEs. The question arises what the chances and challenges for SMEs are and what are the experience with its usage. In this paper after a presentation of key issues in eLearning chances and challenges of eLearning for SMEs are discussed and experiences are exemplified by three EU-funded eLearning projects. The focus lies on the ongoing project ARIEL - Analysing and Reporting the Implementation of Electronic Learning in Europe – coordinated by the Institut Arbeit und Technik (IAT).

eLEARNING - A CHANCE FOR SMALL AND MEDIUM SIZED ENTERPRISES

eLearning through its flexibility and facility of access is seen as a major enabler of lifelong learning (LLL), as a catalyst of change and a chance for small and medium-sized enterprises (SMEs) to improve their business and to integrate into European market. But so far the eLearning in the context of vocational educational training has been mainly adopted by large enterprises, while only little activity can be observed in SMEs. The question arises what the chances and challenges for SMEs are and what is the experience with its usage. In this paper after a presentation of key issues in eLearning chances and challenges of eLearning for SMEs are discussed and experiences are exemplified by three EU-funded eLearning projects. The focus lies on the ongoing project ARIEL - Analysing and Reporting the Implementation of Electronic Learning in Europe - coordinated by the Institut Arbeit und Technik (IAT).

eLEARNING - EINE CHANCE FÜR KLEINE UND MITTLERE UNTERNEHMEN

eLearning wird durch seine Flexibilität und Zugänglichkeit als bedeutendes Instrument für die Implementierung lebenslangen Lernens (LLL) angesehen. Es kann für kleine und mittelgroße Unternehmen (KMU) einen Katalysator des Wandels sein und bietet damit die Chance zur Verbesserung der wirtschaftlichen Leistungsfähigkeit. Darüber hinaus kann eLearning dazu dienen, die Integration von KMU in den europäischen Markt zu fördern. Bis jetzt wird eLearning im Rahmen der beruflichen Aus- und Weiterbildung jedoch nahezu ausschließlich in Großunternehmen genutzt, während es in KMU allenfalls eine marginale Rolle spielt. Im ersten Kapitel dieses Artikels wird auf den Perspektivenwechsel in der beruflichen Aus- und Weiterbildung eingegangen. Im Anschluss daran werden die zentralen Elemente von eLearning vorgestellt (Kap. 2). Die mit eLearning verbundenen Chancen und Herausforderungen für KMU diskutiert (Kap. 3). Abschließend wird auf Erfahrungen mit eLearning in der Praxis am Beispiel von drei EU-finanzierten Projekten eingegangen. Das Hauptaugenmerk liegt dabei auf dem laufenden Projekt ARIEL -Analysing and Reporting the Implementation of Electronic Learning in Europe -, das vom Institut Arbeit und Technik, Gelsenkirchen, (IAT) koordiniert wird.

Stability criteria for unsupervised temporal association networks

A biologically realizable, unsupervised learning rule is described for the online extraction of object features, suitable for solving a range of object recognition tasks. Alterations to the basic learning rule are proposed which allow the rule to better suit the parameters of a given input space. One negative consequence of such modifications is the potential for learning instability. The criteria for such instability are modeled using digital filtering techniques and predicted regions of stability and instability tested. The result is a family of learning rules which can be tailored to the specific environment, improving both convergence times and accuracy over the standard learning rule, while simultaneously insuring learning stability.

Developing Collective Teaching Computer Software for the Course “Decision Theory”

Improvement of training students using modern information technologies, like collective developing teaching computer software, is discussed. Organizational, technical, technological advices are given. Experience of using information technologies in educational course “Decision Theory” is described.

Integrated and Personalized Digital Information Services

Digital information services are gradually becoming integrated with other systems and services such as library automation systems, student information services, and electronic learning systems. Users demand seamless access to a multitude of digital information services without leaving their desktop computers. They prefer using systems that recognize them when they log on, acknowledge their rights and privileges, and thus provide personalized information services. This paper summarizes the recent developments concerning integrated and personalized digital information services. It first emphasizes the role of the Internet in providing information services and then goes on to discuss the integration and personalization issues by emphasizing their importance for digital information services.

Learning business strategies for competitive electronic marketplaces

This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.

Development of a semi-automatic self learning pattern recognition system for the control of electronic boards

This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway - Mayo Institute of Technology and an industrial company, Tyco/Mallinckrodt Galway. The project aimed to develop a semi - automatic, self - learning pattern recognition system capable of detecting defects on the printed circuits boards such as component vacancy, component misalignment, component orientation, component error, and component weld. The research was conducted in three directions: image acquisition, image filtering/recognition and software development. Image acquisition studied the process of forming and digitizing images and some fundamental aspects regarding the human visual perception. The importance of choosing the right camera and illumination system for a certain type of problem has been highlighted. Probably the most important step towards image recognition is image filtering, The filters are used to correct and enhance images in order to prepare them for recognition. Convolution, histogram equalisation, filters based on Boolean mathematics, noise reduction, edge detection, geometrical filters, cross-correlation filters and image compression are some examples of the filters that have been studied and successfully implemented in the software application. The software application developed during the research is customized in order to meet the requirements of the industrial partner. The application is able to analyze pictures, perform the filtering, build libraries, process images and generate log files. It incorporates most of the filters studied and together with the illumination system and the camera it provides a fully integrated framework able to analyze defects on printed circuit boards.

Electronic voting system for computer supported collaborative learning

The EVS4CSCL project starts in the context of a Computer Supported Collaborative Learning environment (CSCL). Previous UOC projects created a CSCL generic platform (CLPL) to facilitate the development of CSCL applications. A discussion forum (DF) was the first application developed over the framework. This discussion forum was different from other products on the marketplace because of its focus on the learning process. The DF carried out the specification and elaboration phases from the discussion learning process but there was a lack in the consensus phase. The consensus phase in a learning environment is not something to be achieved but tested. Common tests are done by Electronic Voting System (EVS) tools, but consensus test is not an assessment test. We are not evaluating our students by their answers but by their discussion activity. Our educational EVS would be used as a discussion catalyst proposing a discussion about the results after an initial query or it would be used after a discussion period in order to manifest how the discussion changed the students mind (consensus). It should be also used by the teacher as a quick way to know where the student needs some reinforcement. That is important in a distance-learning environment where there is no direct contact between the teacher and the student and it is difficult to detect the learning lacks. In an educational environment, assessment it is a must and the EVS will provide direct assessment by peer usefulness evaluation, teacher marks on every query created and indirect assessment from statistics regarding the user activity.

The assessment of the quality of sugar using electronic tongue and machine learning algorithms

The correct classification of sugar according to its physico-chemical characteristics directly influences the value of the product and its acceptance by the market. This study shows that using an electronic tongue system along with established techniques of supervised learning leads to the correct classification of sugar samples according to their qualities. In this paper, we offer two new real, public and non-encoded sugar datasets whose attributes were automatically collected using an electronic tongue, with and without pH controlling. Moreover, we compare the performance achieved by several established machine learning methods. Our experiments were diligently designed to ensure statistically sound results and they indicate that k-nearest neighbors method outperforms other evaluated classifiers and, hence, it can be used as a good baseline for further comparison. © 2012 IEEE.

Availability and Use of Audiovisual and Electronic Resources by Distance Learning Students in Nigerian Universities: a Case Study of National Open University of Nigeria (NOUN), Ibadan Study Centre

This study investigated the availability and use of audiovisual and electronic resources by distance learning students at the National Open University of Nigeria (NOUN). A questionnaire was administered tothe distance learning students selected across the various departments of the NOUN. The findings revealed that even though NOUN made provision for audiovisual and electronic resources for students' use, a majority of the audiovisual and electronic resources are available through personal provision by the students.The study also revealed regular use of audiovisual and electronic resources by the distance learning students. Constraints on use include poor power supply, poor infrastructure, lack of adequate skill, and high cost of access.

Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records

Surveillance Levels (SLs) are categories for medical patients (used in Brazil) that represent different types of medical recommendations. SLs are defined according to risk factors and the medical and developmental history of patients. Each SL is associated with specific educational and clinical measures. The objective of the present paper was to verify computer-aided, automatic assignment of SLs. The present paper proposes a computer-aided approach for automatic recommendation of SLs. The approach is based on the classification of information from patient electronic records. For this purpose, a software architecture composed of three layers was developed. The architecture is formed by a classification layer that includes a linguistic module and machine learning classification modules. The classification layer allows for the use of different classification methods, including the use of preprocessed, normalized language data drawn from the linguistic module. We report the verification and validation of the software architecture in a Brazilian pediatric healthcare institution. The results indicate that selection of attributes can have a great effect on the performance of the system. Nonetheless, our automatic recommendation of surveillance level can still benefit from improvements in processing procedures when the linguistic module is applied prior to classification. Results from our efforts can be applied to different types of medical systems. The results of systems supported by the framework presented in this paper may be used by healthcare and governmental institutions to improve healthcare services in terms of establishing preventive measures and alerting authorities about the possibility of an epidemic.